mirror of
https://github.com/ROCm/composable_kernel.git
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NHWC conv 2d: bwd fp32/fp16/bfp16/int8, Device level tuning and host API (#92)
* start conv2d bwd api * kernel running * add bwd reference * change to no shuffle * fix bwd reference * pass verification * add Filter1x1Stride1Pad0 and start testing * change some tuning parameter * fix test error * add fp16 tuning parameter * add bf16 tuning parameter * add int8 tuning parameters * change fp32 tuning parameter * add bwd to profiler * fix bug for bwd profiler * fix ckProfiler bug * change conv2d_bwd_xdl to fp16 * fix bug in comments * fix precompile id * fix enum conv name * chage _bwd_ to _bwd_data_ * change conv2d_bwd example id * bwd to bwd data * fix prehead * fix MakeDefaultBlock2CTileMap ,import form merge develop * format bwd instance * bwd to bwd data * change name bwd to bwd data * change name bwd to bwd data in example * formate code * change conv2d bwd data id in example * rewrite readme for example * fix CalculateMagicNumbers about div zero * add workaround CK_WORKAROUND_SWDEV_325164 * change test_conf2d_bwd_data show info * format * fix bug for workaround:CK_WORKAROUND_SWDEV_325164 * formate tuning parameters * formate tuning parameters again * formate tuning parameters 3 * formate tuning parameters 4 * remove add function template * format * update comment Co-authored-by: ltqin <letaoqin@amd.com> Co-authored-by: Chao Liu <chao.liu2@amd.com>
This commit is contained in:
ltqin
@@ -151,6 +151,12 @@
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#define CK_WORKAROUND_SWDEV_XXXXXX_THREAD_WISE_COPY_V1R5_TYPE_CONVERT_ISSUE 1
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#endif
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// workaround for verifaction failure, due to compiler regression, for conv bwd-data fp16 using some
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// tuning parameter
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#ifndef CK_WORKAROUND_SWDEV_325164
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#define CK_WORKAROUND_SWDEV_325164 1
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#endif
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namespace ck {
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enum InMemoryDataOperationEnum_t
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@@ -1,5 +1,6 @@
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#ifndef CK_ELEMENT_WISE_OPERATION_HPP
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#define CK_ELEMENT_WISE_OPERATION_HPP
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#include "data_type.hpp"
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#include "data_type.hpp"
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@@ -25,21 +25,30 @@ struct MagicDivision
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// uint32_t
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__host__ __device__ static constexpr auto CalculateMagicNumbers(uint32_t divisor)
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{
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// assert(divisior >= 1 && divisior <= INT32_MAX);
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uint32_t shift = 0;
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for(shift = 0; shift < 32; ++shift)
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// WARNING: magic division is only applicable for division inside this range.
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// You should use the return value of CalculateMagicNumbers, if division is not inside this
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// range. The "else" logic below is to quiet down run-time error.
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if(divisor >= 1 && divisor <= INT32_MAX)
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{
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if((1U << shift) >= divisor)
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uint32_t shift = 0;
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for(shift = 0; shift < 32; ++shift)
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{
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break;
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if((1U << shift) >= divisor)
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{
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break;
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}
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}
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uint64_t one = 1;
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uint64_t multiplier = ((one << 32) * ((one << shift) - divisor)) / divisor + 1;
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// assert(multiplier <= 0xffffffffUL);
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return make_tuple(uint32_t(multiplier), shift);
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}
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else
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{
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return make_tuple(uint32_t(0), uint32_t(0));
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}
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uint64_t one = 1;
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uint64_t multiplier = ((one << 32) * ((one << shift) - divisor)) / divisor + 1;
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// assert(multiplier <= 0xffffffffUL);
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return make_tuple(uint32_t(multiplier), shift);
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}
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__host__ __device__ static constexpr uint32_t CalculateMagicMultiplier(uint32_t divisor)
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@@ -101,16 +101,25 @@ set(DEVICE_CONV2D_FWD_BIAS_RELU_ATOMIC_ADD_INSTANCE_SOURCE
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${PROJECT_SOURCE_DIR}/device_operation/src/device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instance.cpp;
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)
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add_library(device_gemm_instance SHARED ${DEVICE_GEMM_INSTANCE_SOURCE})
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add_library(device_gemm_bias_2d_instance SHARED ${DEVICE_GEMM_BIAS_2D_INSTANCE_SOURCE})
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add_library(device_gemm_bias_relu_instance SHARED ${DEVICE_GEMM_BIAS_RELU_INSTANCE_SOURCE})
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add_library(device_gemm_bias_relu_add_instance SHARED ${DEVICE_GEMM_BIAS_RELU_ADD_INSTANCE_SOURCE})
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# device_conv2d_bwd_data_instance
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set(DEVICE_CONV2D_BWD_DATA_INSTANCE_SOURCE
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${PROJECT_SOURCE_DIR}/device_operation/src/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instance.cpp;
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${PROJECT_SOURCE_DIR}/device_operation/src/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instance.cpp;
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${PROJECT_SOURCE_DIR}/device_operation/src/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instance.cpp;
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${PROJECT_SOURCE_DIR}/device_operation/src/device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instance.cpp;
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)
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add_library(device_gemm_instance SHARED ${DEVICE_GEMM_INSTANCE_SOURCE})
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add_library(device_gemm_bias_relu_instance SHARED ${DEVICE_GEMM_BIAS_RELU_INSTANCE_SOURCE})
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add_library(device_gemm_bias_relu_add_instance SHARED ${DEVICE_GEMM_BIAS_RELU_ADD_INSTANCE_SOURCE})
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add_library(device_batched_gemm_instance SHARED ${DEVICE_BATCHED_GEMM_INSTANCE_SOURCE})
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add_library(device_conv1d_fwd_instance SHARED ${DEVICE_CONV1D_FWD_INSTANCE_SOURCE})
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add_library(device_conv2d_fwd_instance SHARED ${DEVICE_CONV2D_FWD_INSTANCE_SOURCE})
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add_library(device_conv2d_fwd_bias_relu_instance SHARED ${DEVICE_CONV2D_FWD_BIAS_RELU_INSTANCE_SOURCE})
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add_library(device_conv2d_fwd_bias_relu_add_instance SHARED ${DEVICE_CONV2D_FWD_BIAS_RELU_ADD_INSTANCE_SOURCE})
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add_library(device_conv2d_fwd_bias_relu_atomic_add_instance SHARED ${DEVICE_CONV2D_FWD_BIAS_RELU_ATOMIC_ADD_INSTANCE_SOURCE})
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add_library(device_gemm_bias_2d_instance SHARED ${DEVICE_GEMM_BIAS_2D_INSTANCE_SOURCE})
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add_library(device_conv2d_bwd_data_instance SHARED ${DEVICE_CONV2D_BWD_DATA_INSTANCE_SOURCE})
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target_include_directories(device_gemm_instance SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
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target_include_directories(device_gemm_bias_2d_instance SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
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@@ -122,6 +131,7 @@ target_include_directories(device_conv2d_fwd_instance SYSTEM PUBLIC $<BUILD_INTE
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target_include_directories(device_conv2d_fwd_bias_relu_instance SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
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target_include_directories(device_conv2d_fwd_bias_relu_add_instance SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
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target_include_directories(device_conv2d_fwd_bias_relu_atomic_add_instance SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
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target_include_directories(device_conv2d_bwd_data_instance SYSTEM PUBLIC $<BUILD_INTERFACE:${HALF_INCLUDE_DIR}>)
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target_compile_features(device_gemm_instance PUBLIC)
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target_compile_features(device_gemm_bias_2d_instance PUBLIC)
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@@ -133,6 +143,7 @@ target_compile_features(device_conv2d_fwd_instance PUBLIC)
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target_compile_features(device_conv2d_fwd_bias_relu_instance PUBLIC)
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target_compile_features(device_conv2d_fwd_bias_relu_add_instance PUBLIC)
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target_compile_features(device_conv2d_fwd_bias_relu_atomic_add_instance PUBLIC)
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target_compile_features(device_conv2d_bwd_data_instance PUBLIC)
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set_target_properties(device_gemm_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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set_target_properties(device_gemm_bias_2d_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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@@ -144,6 +155,7 @@ set_target_properties(device_conv2d_fwd_instance PROPERTIES POSITION_INDEPENDENT
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set_target_properties(device_conv2d_fwd_bias_relu_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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set_target_properties(device_conv2d_fwd_bias_relu_add_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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set_target_properties(device_conv2d_fwd_bias_relu_atomic_add_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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set_target_properties(device_conv2d_bwd_data_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
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install(TARGETS device_gemm_instance LIBRARY DESTINATION lib)
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install(TARGETS device_gemm_bias_2d_instance LIBRARY DESTINATION lib)
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@@ -155,3 +167,4 @@ install(TARGETS device_conv2d_fwd_instance LIBRARY DESTINATION lib)
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install(TARGETS device_conv2d_fwd_bias_relu_instance LIBRARY DESTINATION lib)
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install(TARGETS device_conv2d_fwd_bias_relu_add_instance LIBRARY DESTINATION lib)
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install(TARGETS device_conv2d_fwd_bias_relu_atomic_add_instance LIBRARY DESTINATION lib)
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install(TARGETS device_conv2d_bwd_data_instance LIBRARY DESTINATION lib)
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@@ -0,0 +1,17 @@
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#ifndef CONVOLUTION_BACKWARD_DATA_SPECIALIZATION
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#define CONVOLUTION_BACKWARD_DATA_SPECIALIZATION
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namespace ck {
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namespace tensor_operation {
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namespace device {
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enum ConvolutionBackwardDataSpecialization_t
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{
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Default,
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Filter1x1Stride1Pad0,
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};
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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#endif
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@@ -0,0 +1,814 @@
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#ifndef DEVICE_CONV2D_BWD_DATA_XDL_NHWC_KYXC_NHWK_HPP
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#define DEVICE_CONV2D_BWD_DATA_XDL_NHWC_KYXC_NHWK_HPP
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#include <iostream>
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#include <sstream>
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#include "device.hpp"
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#include "device_base.hpp"
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#include "device_conv_bwd_data.hpp"
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#include "convolution_backward_data_specialization.hpp"
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#include "common_header.hpp"
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#include "tensor_layout.hpp"
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#include "tensor_descriptor.hpp"
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#include "tensor_descriptor_helper.hpp"
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#include "gridwise_gemm_xdlops_v2r3.hpp"
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namespace ck {
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namespace tensor_operation {
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namespace device {
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// out[N, Ho, Wo, K] = in[N, Hi, Wi, C] * wei[K, Y, X, C]
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template <typename InDataType,
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typename WeiDataType,
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typename OutDataType,
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typename AccDataType,
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typename InElementwiseOperation,
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typename WeiElementwiseOperation,
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typename OutElementwiseOperation,
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ConvolutionBackwardDataSpecialization_t ConvBackwardDataSpecialization,
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ck::index_t BlockSize,
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ck::index_t MPerBlock,
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ck::index_t NPerBlock,
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ck::index_t K0PerBlock,
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ck::index_t K1,
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ck::index_t MPerXdl,
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ck::index_t NPerXdl,
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ck::index_t MXdlPerWave,
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ck::index_t NXdlPerWave,
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typename ABlockTransferThreadClusterLengths_K0_M_K1,
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typename ABlockTransferThreadClusterArrangeOrder,
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typename ABlockTransferSrcAccessOrder,
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ck::index_t ABlockTransferSrcVectorDim,
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ck::index_t ABlockTransferSrcScalarPerVector,
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ck::index_t ABlockTransferDstScalarPerVector_K1,
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bool ABlockLdsAddExtraM,
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typename BBlockTransferThreadClusterLengths_K0_N_K1,
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typename BBlockTransferThreadClusterArrangeOrder,
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typename BBlockTransferSrcAccessOrder,
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ck::index_t BBlockTransferSrcVectorDim,
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ck::index_t BBlockTransferSrcScalarPerVector,
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ck::index_t BBlockTransferDstScalarPerVector_K1,
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bool BBlockLdsAddExtraN,
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ck::index_t CThreadTransferSrcDstVectorDim,
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ck::index_t CThreadTransferDstScalarPerVector>
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struct DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
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: public DeviceConvBwdData<InElementwiseOperation,
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WeiElementwiseOperation,
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OutElementwiseOperation>
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{
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using DeviceOp = DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K;
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using ADataType = OutDataType;
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using BDataType = WeiDataType;
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using CDataType = InDataType;
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// TODO make A/B datatype different
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using ABDataType = InDataType;
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static constexpr index_t NDimSpatial = 2;
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static constexpr auto I0 = Number<0>{};
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static constexpr auto I1 = Number<1>{};
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static constexpr auto I2 = Number<2>{};
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static constexpr auto I3 = Number<3>{};
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static constexpr auto I4 = Number<4>{};
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static constexpr auto I5 = Number<5>{};
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static_assert((K1 % ABlockTransferThreadClusterLengths_K0_M_K1{}[I2]) %
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ABlockTransferSrcScalarPerVector ==
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0);
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static_assert((NPerBlock / BBlockTransferThreadClusterLengths_K0_N_K1{}[I1]) %
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BBlockTransferSrcScalarPerVector ==
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0);
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static constexpr auto K1Number = Number<K1>{};
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static constexpr auto GemmK1Number = K1Number;
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static auto
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MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(ck::index_t N,
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ck::index_t K,
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ck::index_t C,
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std::vector<ck::index_t> input_spatial_lengths,
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std::vector<ck::index_t> filter_spatial_lengths,
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std::vector<ck::index_t> output_spatial_lengths,
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std::vector<ck::index_t> conv_filter_strides,
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std::vector<ck::index_t> conv_filter_dilations,
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std::vector<ck::index_t> input_left_pads,
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std::vector<ck::index_t> input_right_pads,
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index_t i_ytilda,
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index_t i_xtilda)
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{
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using namespace ck;
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const index_t Hi = input_spatial_lengths[0];
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const index_t Wi = input_spatial_lengths[1];
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const index_t Ho = output_spatial_lengths[0];
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const index_t Wo = output_spatial_lengths[1];
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const index_t Y = filter_spatial_lengths[0];
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const index_t X = filter_spatial_lengths[1];
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const index_t InLeftPadH = input_left_pads[0];
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const index_t InLeftPadW = input_left_pads[1];
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const index_t InRightPadH = input_right_pads[0];
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const index_t InRightPadW = input_right_pads[1];
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const index_t ConvStrideH = conv_filter_strides[0];
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const index_t ConvStrideW = conv_filter_strides[1];
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const index_t ConvDilationH = conv_filter_dilations[0];
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const index_t ConvDilationW = conv_filter_dilations[1];
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const auto K0 = K / K1;
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const auto out_n_ho_wo_k_grid_desc =
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make_naive_tensor_descriptor_packed(make_tuple(N, Ho, Wo, K));
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const auto wei_k_y_x_c_grid_desc =
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make_naive_tensor_descriptor_packed(make_tuple(K, Y, X, C));
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const auto in_n_hi_wi_c_grid_desc =
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make_naive_tensor_descriptor_packed(make_tuple(N, Hi, Wi, C));
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if constexpr(ConvBackwardDataSpecialization ==
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ConvolutionBackwardDataSpecialization_t::Filter1x1Stride1Pad0)
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{
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// A: output tensor
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const auto out_gemmk0_gemmm_gemmk1_grid_desc = transform_tensor_descriptor(
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make_naive_tensor_descriptor_packed(make_tuple(N * Ho * Wo, K)),
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make_tuple(make_pass_through_transform(N * Ho * Wo),
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make_unmerge_transform(make_tuple(K0, K1))),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<1>{}, Sequence<0, 2>{}));
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// B: weight tensor
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const auto wei_gemmk0_gemmn_gemmk1_grid_desc =
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transform_tensor_descriptor(make_naive_tensor_descriptor_packed(make_tuple(K, C)),
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make_tuple(make_unmerge_transform(make_tuple(K0, K1)),
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make_pass_through_transform(C)),
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make_tuple(Sequence<0>{}, Sequence<1>{}),
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make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
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// C: input tensor
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const auto in_n_y_ho_x_wo_c_grid_desc = transform_tensor_descriptor(
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in_n_hi_wi_c_grid_desc,
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make_tuple(make_pass_through_transform(N),
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make_embed_transform(make_tuple(I1, Ho), make_tuple(I1, ConvStrideH)),
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make_embed_transform(make_tuple(I1, Wo), make_tuple(I1, ConvStrideW)),
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make_pass_through_transform(C)),
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make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
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make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
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const auto in_gemmm_gemmn_grid_desc = transform_tensor_descriptor(
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in_n_y_ho_x_wo_c_grid_desc,
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make_tuple(make_freeze_transform(I0),
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make_freeze_transform(I0),
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make_merge_transform(make_tuple(N, Ho, Wo)),
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make_pass_through_transform(C)),
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make_tuple(Sequence<1>{}, Sequence<3>{}, Sequence<0, 2, 4>{}, Sequence<5>{}),
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make_tuple(Sequence<>{}, Sequence<>{}, Sequence<0>{}, Sequence<1>{}));
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return make_tuple(out_gemmk0_gemmm_gemmk1_grid_desc,
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wei_gemmk0_gemmn_gemmk1_grid_desc,
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in_gemmm_gemmn_grid_desc);
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}
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else
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{
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const auto GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
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const auto GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
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const auto YTilda = ConvStrideH / GcdStrideDilationH;
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const auto XTilda = ConvStrideW / GcdStrideDilationW;
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const auto YDot = math::integer_divide_ceil(Y, YTilda);
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const auto XDot = math::integer_divide_ceil(X, XTilda);
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const auto HTilda =
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Ho + math::integer_divide_ceil(ConvDilationH * (Y - I1), ConvStrideH);
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const auto WTilda =
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Wo + math::integer_divide_ceil(ConvDilationW * (X - I1), ConvStrideW);
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// only work on HTilda and WTilda that contribute to non-padding area of input tensor
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const auto IHTildaSliceBegin = math::integer_divide_floor(
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math::max(I0, InLeftPadH - ConvDilationH * (YTilda - I1)), ConvStrideH);
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const auto IWTildaSliceBegin = math::integer_divide_floor(
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math::max(I0, InLeftPadW - ConvDilationW * (XTilda - I1)), ConvStrideW);
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const auto IHTildaSliceEnd = math::min(
|
||||
HTilda, math::integer_divide_ceil(InLeftPadH + Hi - I1, ConvStrideH) + I1);
|
||||
const auto IWTildaSliceEnd = math::min(
|
||||
WTilda, math::integer_divide_ceil(InLeftPadW + Wi - I1, ConvStrideW) + I1);
|
||||
|
||||
const auto HTildaSlice = IHTildaSliceEnd - IHTildaSliceBegin;
|
||||
const auto WTildaSlice = IWTildaSliceEnd - IWTildaSliceBegin;
|
||||
|
||||
// GemmK is different for each GEMM
|
||||
const auto YDotSlice = math::integer_divide_ceil(Y - i_ytilda, YTilda);
|
||||
const auto XDotSlice = math::integer_divide_ceil(X - i_xtilda, XTilda);
|
||||
|
||||
// A: output tensor
|
||||
const auto out_n_hop_wop_k_grid_desc = transform_tensor_descriptor(
|
||||
out_n_ho_wo_k_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N),
|
||||
make_pad_transform(Ho, I0, I0),
|
||||
make_pad_transform(Wo, I0, I0),
|
||||
make_pass_through_transform(K)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
|
||||
|
||||
const auto out_n_ydot_htilda_xdot_wtilda_k_grid_desc = transform_tensor_descriptor(
|
||||
out_n_hop_wop_k_grid_desc,
|
||||
make_tuple(
|
||||
make_pass_through_transform(N),
|
||||
make_embed_transform(make_tuple(YDot, HTilda),
|
||||
make_tuple(-ConvDilationH / GcdStrideDilationH, I1)),
|
||||
make_embed_transform(make_tuple(XDot, WTilda),
|
||||
make_tuple(-ConvDilationW / GcdStrideDilationW, I1)),
|
||||
make_pass_through_transform(K)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
|
||||
|
||||
const auto out_n_ydotslice_htildaslice_xdotslice_wtildaslice_k0_k1_grid_desc =
|
||||
transform_tensor_descriptor(
|
||||
out_n_ydot_htilda_xdot_wtilda_k_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N),
|
||||
make_slice_transform(YDot, I0, YDotSlice),
|
||||
make_slice_transform(HTilda, IHTildaSliceBegin, HTildaSlice),
|
||||
make_slice_transform(XDot, I0, XDotSlice),
|
||||
make_slice_transform(WTilda, IWTildaSliceBegin, WTildaSlice),
|
||||
make_unmerge_transform(make_tuple(K0, K1))),
|
||||
make_tuple(Sequence<0>{},
|
||||
Sequence<1>{},
|
||||
Sequence<2>{},
|
||||
Sequence<3>{},
|
||||
Sequence<4>{},
|
||||
Sequence<5>{}),
|
||||
make_tuple(Sequence<0>{},
|
||||
Sequence<1>{},
|
||||
Sequence<2>{},
|
||||
Sequence<3>{},
|
||||
Sequence<4>{},
|
||||
Sequence<5, 6>{}));
|
||||
|
||||
const auto out_gemmk0_gemmm_gemmk1_grid_desc = transform_tensor_descriptor(
|
||||
out_n_ydotslice_htildaslice_xdotslice_wtildaslice_k0_k1_grid_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(YDotSlice, XDotSlice, K0)),
|
||||
make_merge_transform(make_tuple(N, HTildaSlice, WTildaSlice)),
|
||||
make_pass_through_transform(K1)),
|
||||
make_tuple(Sequence<1, 3, 5>{}, Sequence<0, 2, 4>{}, Sequence<6>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
|
||||
|
||||
// B weight tensor
|
||||
const auto wei_k_ydot_ytilda_xdot_xtilda_c_grid_desc = transform_tensor_descriptor(
|
||||
wei_k_y_x_c_grid_desc,
|
||||
make_tuple(make_pass_through_transform(K),
|
||||
make_embed_transform(make_tuple(YDot, YTilda),
|
||||
make_tuple(ConvStrideH / GcdStrideDilationH, I1)),
|
||||
make_embed_transform(make_tuple(XDot, XTilda),
|
||||
make_tuple(ConvStrideW / GcdStrideDilationW, I1)),
|
||||
make_pass_through_transform(C)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
|
||||
|
||||
const auto wei_k0_k1_ydotslice_xdotslice_c_grid_desc =
|
||||
transform_tensor_descriptor(wei_k_ydot_ytilda_xdot_xtilda_c_grid_desc,
|
||||
make_tuple(make_unmerge_transform(make_tuple(K0, K1)),
|
||||
make_slice_transform(YDot, I0, YDotSlice),
|
||||
make_slice_transform(XDot, I0, XDotSlice),
|
||||
make_freeze_transform(i_ytilda),
|
||||
make_freeze_transform(i_xtilda),
|
||||
make_pass_through_transform(C)),
|
||||
make_tuple(Sequence<0>{},
|
||||
Sequence<1>{},
|
||||
Sequence<3>{},
|
||||
Sequence<2>{},
|
||||
Sequence<4>{},
|
||||
Sequence<5>{}),
|
||||
make_tuple(Sequence<0, 1>{},
|
||||
Sequence<2>{},
|
||||
Sequence<3>{},
|
||||
Sequence<>{},
|
||||
Sequence<>{},
|
||||
Sequence<4>{}));
|
||||
|
||||
const auto wei_gemmk0_gemmn_gemmk1_grid_desc = transform_tensor_descriptor(
|
||||
wei_k0_k1_ydotslice_xdotslice_c_grid_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(YDotSlice, XDotSlice, K0)),
|
||||
make_pass_through_transform(C),
|
||||
make_pass_through_transform(K1)),
|
||||
make_tuple(Sequence<2, 3, 0>{}, Sequence<4>{}, Sequence<1>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
|
||||
|
||||
// C: input tensor
|
||||
const auto in_n_hip_wip_c_grid_desc = transform_tensor_descriptor(
|
||||
in_n_hi_wi_c_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N),
|
||||
make_pad_transform(Hi, InLeftPadH, InRightPadH),
|
||||
make_pad_transform(Wi, InLeftPadW, InRightPadW),
|
||||
make_pass_through_transform(C)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
|
||||
|
||||
const auto in_n_ytilda_htilda_xtilda_wtilda_c_grid_desc = transform_tensor_descriptor(
|
||||
in_n_hip_wip_c_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N),
|
||||
make_embed_transform(make_tuple(YTilda, HTilda),
|
||||
make_tuple(ConvDilationH, ConvStrideH)),
|
||||
make_embed_transform(make_tuple(XTilda, WTilda),
|
||||
make_tuple(ConvDilationW, ConvStrideW)),
|
||||
make_pass_through_transform(C)),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
|
||||
|
||||
const auto in_n_htildaslice_wtildaslice_c_grid_desc = transform_tensor_descriptor(
|
||||
in_n_ytilda_htilda_xtilda_wtilda_c_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N),
|
||||
make_freeze_transform(i_ytilda),
|
||||
make_slice_transform(HTilda, IHTildaSliceBegin, HTildaSlice),
|
||||
make_freeze_transform(i_xtilda),
|
||||
make_slice_transform(WTilda, IWTildaSliceBegin, WTildaSlice),
|
||||
make_pass_through_transform(C)),
|
||||
make_tuple(Sequence<0>{},
|
||||
Sequence<1>{},
|
||||
Sequence<2>{},
|
||||
Sequence<3>{},
|
||||
Sequence<4>{},
|
||||
Sequence<5>{}),
|
||||
make_tuple(Sequence<0>{},
|
||||
Sequence<>{},
|
||||
Sequence<1>{},
|
||||
Sequence<>{},
|
||||
Sequence<2>{},
|
||||
Sequence<3>{}));
|
||||
|
||||
const auto in_gemmm_gemmn_grid_desc = transform_tensor_descriptor(
|
||||
in_n_htildaslice_wtildaslice_c_grid_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(N, HTildaSlice, WTildaSlice)),
|
||||
make_pass_through_transform(C)),
|
||||
make_tuple(Sequence<0, 1, 2>{}, Sequence<3>{}),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
return make_tuple(out_gemmk0_gemmm_gemmk1_grid_desc,
|
||||
wei_gemmk0_gemmn_gemmk1_grid_desc,
|
||||
in_gemmm_gemmn_grid_desc);
|
||||
}
|
||||
|
||||
} // function end
|
||||
|
||||
using ABCGridDescs = decltype(MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
|
||||
1, 1, 1, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, 0, 0));
|
||||
|
||||
using AGridDesc_K0_M_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I0])>;
|
||||
using BGridDesc_K0_N_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I1])>;
|
||||
using CGridDesc_M_N = remove_cvref_t<decltype(ABCGridDescs{}[I2])>;
|
||||
|
||||
// GridwiseGemm
|
||||
using GridwiseGemm = GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3<
|
||||
BlockSize,
|
||||
ABDataType, // TODO: distinguish A/B datatype
|
||||
AccDataType,
|
||||
CDataType,
|
||||
InMemoryDataOperationEnum_t::Set,
|
||||
AGridDesc_K0_M_K1,
|
||||
BGridDesc_K0_N_K1,
|
||||
CGridDesc_M_N,
|
||||
InElementwiseOperation,
|
||||
WeiElementwiseOperation,
|
||||
OutElementwiseOperation,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
K0PerBlock,
|
||||
MPerXdl,
|
||||
NPerXdl,
|
||||
K1,
|
||||
MXdlPerWave,
|
||||
NXdlPerWave,
|
||||
ABlockTransferThreadClusterLengths_K0_M_K1,
|
||||
ABlockTransferThreadClusterArrangeOrder,
|
||||
ABlockTransferSrcAccessOrder,
|
||||
ABlockTransferSrcVectorDim,
|
||||
ABlockTransferSrcScalarPerVector,
|
||||
ABlockTransferDstScalarPerVector_K1,
|
||||
false, // AThreadTransferSrcResetCoordinateAfterRun,
|
||||
ABlockLdsAddExtraM,
|
||||
BBlockTransferThreadClusterLengths_K0_N_K1,
|
||||
BBlockTransferThreadClusterArrangeOrder,
|
||||
BBlockTransferSrcAccessOrder,
|
||||
BBlockTransferSrcVectorDim,
|
||||
BBlockTransferSrcScalarPerVector,
|
||||
BBlockTransferDstScalarPerVector_K1,
|
||||
false, // BThreadTransferSrcResetCoordinateAfterRun,
|
||||
BBlockLdsAddExtraN,
|
||||
Sequence<2, 3, 0, 1, 7, 5, 4, 6>, // CThreadTransferSrcDstAccessOrder,
|
||||
7, // CThreadTransferSrcDstVectorDim,
|
||||
CThreadTransferDstScalarPerVector>;
|
||||
|
||||
// Argument
|
||||
struct Argument : public BaseArgument
|
||||
{
|
||||
Argument(InDataType* p_in_grid,
|
||||
const WeiDataType* p_wei_grid,
|
||||
const OutDataType* p_out_grid,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t C,
|
||||
std::vector<ck::index_t> input_spatial_lengths,
|
||||
std::vector<ck::index_t> filter_spatial_lengths,
|
||||
std::vector<ck::index_t> output_spatial_lengths,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
ck::index_t M01,
|
||||
ck::index_t N01,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
: p_a_grid_{p_out_grid},
|
||||
p_b_grid_{p_wei_grid},
|
||||
p_c_grid_{p_in_grid},
|
||||
M01_{M01},
|
||||
N01_{N01},
|
||||
a_element_op_{out_element_op},
|
||||
b_element_op_{wei_element_op},
|
||||
c_element_op_{in_element_op},
|
||||
Conv_N_{N},
|
||||
Conv_K_{K},
|
||||
Conv_C_{C},
|
||||
input_spatial_lengths_{input_spatial_lengths},
|
||||
filter_spatial_lengths_{filter_spatial_lengths},
|
||||
output_spatial_lengths_{output_spatial_lengths},
|
||||
conv_filter_strides_{conv_filter_strides},
|
||||
conv_filter_dilations_{conv_filter_dilations},
|
||||
input_left_pads_{input_left_pads},
|
||||
input_right_pads_{input_right_pads}
|
||||
{
|
||||
const index_t ConvStrideH = conv_filter_strides[0];
|
||||
const index_t ConvStrideW = conv_filter_strides[1];
|
||||
|
||||
const index_t ConvDilationH = conv_filter_dilations[0];
|
||||
const index_t ConvDilationW = conv_filter_dilations[1];
|
||||
|
||||
const auto GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
|
||||
const auto GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
|
||||
|
||||
const auto YTilda = ConvStrideH / GcdStrideDilationH;
|
||||
const auto XTilda = ConvStrideW / GcdStrideDilationW;
|
||||
|
||||
for(index_t i_ytilda = 0; i_ytilda < YTilda; ++i_ytilda)
|
||||
{
|
||||
for(index_t i_xtilda = 0; i_xtilda < XTilda; ++i_xtilda)
|
||||
{
|
||||
const auto descs = DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
input_spatial_lengths,
|
||||
filter_spatial_lengths,
|
||||
output_spatial_lengths,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
i_ytilda,
|
||||
i_xtilda);
|
||||
a_grid_desc_k0_m_k1_container_.push_back(descs[I0]);
|
||||
b_grid_desc_k0_n_k1_container_.push_back(descs[I1]);
|
||||
c_grid_desc_m_n_container_.push_back(descs[I2]);
|
||||
|
||||
if(GridwiseGemm::CheckValidity(descs[I0], descs[I1], descs[I2], M01_, N01_))
|
||||
{
|
||||
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_.push_back(
|
||||
GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(descs[I2]));
|
||||
|
||||
block_2_ctile_map_container_.push_back(
|
||||
GridwiseGemm::MakeDefaultBlock2CTileMap(descs[I2], M01, N01));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const ADataType* p_a_grid_;
|
||||
const BDataType* p_b_grid_;
|
||||
CDataType* p_c_grid_;
|
||||
std::vector<AGridDesc_K0_M_K1> a_grid_desc_k0_m_k1_container_;
|
||||
std::vector<BGridDesc_K0_N_K1> b_grid_desc_k0_n_k1_container_;
|
||||
std::vector<CGridDesc_M_N> c_grid_desc_m_n_container_;
|
||||
std::vector<typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2>
|
||||
c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_;
|
||||
std::vector<typename GridwiseGemm::DefaultBlock2CTileMap> block_2_ctile_map_container_;
|
||||
index_t M01_;
|
||||
index_t N01_;
|
||||
OutElementwiseOperation a_element_op_;
|
||||
WeiElementwiseOperation b_element_op_;
|
||||
InElementwiseOperation c_element_op_;
|
||||
// for checking IsSupportedArgument()
|
||||
index_t Conv_N_;
|
||||
index_t Conv_K_;
|
||||
index_t Conv_C_;
|
||||
|
||||
std::vector<ck::index_t> input_spatial_lengths_;
|
||||
std::vector<ck::index_t> filter_spatial_lengths_;
|
||||
std::vector<ck::index_t> output_spatial_lengths_;
|
||||
std::vector<ck::index_t> conv_filter_strides_;
|
||||
std::vector<ck::index_t> conv_filter_dilations_;
|
||||
std::vector<ck::index_t> input_left_pads_;
|
||||
std::vector<ck::index_t> input_right_pads_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public BaseInvoker
|
||||
{
|
||||
using Argument = DeviceOp::Argument;
|
||||
|
||||
float Run(const Argument& arg, int nrepeat = 1)
|
||||
{
|
||||
nrepeat = 1;
|
||||
float ave_time = 0;
|
||||
for(size_t i = 0; i < arg.a_grid_desc_k0_m_k1_container_.size(); i++)
|
||||
{
|
||||
{
|
||||
std::cout << "arg.a_grid_desc_k0_m_k1_container_{"
|
||||
<< arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I0) << ", "
|
||||
<< arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I1) << ", "
|
||||
<< arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I2) << "}"
|
||||
<< std::endl;
|
||||
|
||||
std::cout << "arg.b_grid_desc_k0_n_k1_container_{"
|
||||
<< arg.b_grid_desc_k0_n_k1_container_[i].GetLength(I0) << ", "
|
||||
<< arg.b_grid_desc_k0_n_k1_container_[i].GetLength(I1) << ", "
|
||||
<< arg.b_grid_desc_k0_n_k1_container_[i].GetLength(I2) << "}"
|
||||
<< std::endl;
|
||||
|
||||
std::cout << "arg.c_grid_desc_m_n_container_{ "
|
||||
<< arg.c_grid_desc_m_n_container_[i].GetLength(I0) << ", "
|
||||
<< arg.c_grid_desc_m_n_container_[i].GetLength(I1) << "}"
|
||||
<< std::endl;
|
||||
|
||||
std::cout << "arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_( "
|
||||
<< arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i].GetLength(I0)
|
||||
<< ", "
|
||||
<< arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i].GetLength(I1)
|
||||
<< ", "
|
||||
<< arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i].GetLength(I2)
|
||||
<< ", "
|
||||
<< arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i].GetLength(I3)
|
||||
<< ", "
|
||||
<< arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i].GetLength(I4)
|
||||
<< ", "
|
||||
<< arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i].GetLength(I5)
|
||||
<< " ) " << std::endl;
|
||||
}
|
||||
|
||||
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_container_[i],
|
||||
arg.b_grid_desc_k0_n_k1_container_[i],
|
||||
arg.c_grid_desc_m_n_container_[i],
|
||||
arg.M01_,
|
||||
arg.N01_))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v3r1 has invalid setting");
|
||||
}
|
||||
|
||||
const index_t grid_size =
|
||||
GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_container_[i]);
|
||||
|
||||
const auto K0 = arg.a_grid_desc_k0_m_k1_container_[i].GetLength(I0);
|
||||
|
||||
const bool has_main_k0_block_loop = GridwiseGemm::CalculateHasMainK0BlockLoop(K0);
|
||||
|
||||
if(has_main_k0_block_loop)
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdlops_v2r3<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
remove_reference_t<DeviceOp::AGridDesc_K0_M_K1>,
|
||||
remove_reference_t<DeviceOp::BGridDesc_K0_N_K1>,
|
||||
remove_reference_t<
|
||||
typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2>,
|
||||
OutElementwiseOperation,
|
||||
WeiElementwiseOperation,
|
||||
InElementwiseOperation,
|
||||
remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
|
||||
true>;
|
||||
|
||||
ave_time += launch_and_time_kernel(
|
||||
kernel,
|
||||
nrepeat,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.a_grid_desc_k0_m_k1_container_[i],
|
||||
arg.b_grid_desc_k0_n_k1_container_[i],
|
||||
arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i],
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.block_2_ctile_map_container_[i]);
|
||||
}
|
||||
else
|
||||
{
|
||||
const auto kernel = kernel_gemm_xdlops_v2r3<
|
||||
GridwiseGemm,
|
||||
ADataType, // TODO: distiguish A/B datatype
|
||||
CDataType,
|
||||
remove_reference_t<DeviceOp::AGridDesc_K0_M_K1>,
|
||||
remove_reference_t<DeviceOp::BGridDesc_K0_N_K1>,
|
||||
remove_reference_t<
|
||||
typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2>,
|
||||
OutElementwiseOperation,
|
||||
WeiElementwiseOperation,
|
||||
InElementwiseOperation,
|
||||
remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
|
||||
false>;
|
||||
|
||||
ave_time += launch_and_time_kernel(
|
||||
kernel,
|
||||
nrepeat,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_a_grid_,
|
||||
arg.p_b_grid_,
|
||||
arg.p_c_grid_,
|
||||
arg.a_grid_desc_k0_m_k1_container_[i],
|
||||
arg.b_grid_desc_k0_n_k1_container_[i],
|
||||
arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_[i],
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.c_element_op_,
|
||||
arg.block_2_ctile_map_container_[i]);
|
||||
}
|
||||
}
|
||||
return ave_time;
|
||||
}
|
||||
|
||||
float Run(const BaseArgument* p_arg, int nrepeat = 1) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
|
||||
}
|
||||
};
|
||||
|
||||
static constexpr bool IsValidCompilationParameter()
|
||||
{
|
||||
// TODO: properly implement this check
|
||||
return true;
|
||||
}
|
||||
|
||||
static bool IsSupportedArgument(const Argument& arg)
|
||||
{
|
||||
if constexpr(ConvBackwardDataSpecialization ==
|
||||
ConvolutionBackwardDataSpecialization_t::Filter1x1Stride1Pad0)
|
||||
{
|
||||
// check if it's 1x1, stride=1 pad = 0 conv
|
||||
if(!(arg.filter_spatial_lengths_[0] == 1 && arg.filter_spatial_lengths_[1] == 1 &&
|
||||
arg.conv_filter_strides_[0] == 1 && arg.conv_filter_strides_[1] == 1 &&
|
||||
arg.input_left_pads_[0] == 0 && arg.input_left_pads_[1] == 0 &&
|
||||
arg.input_right_pads_[0] == 0 && arg.input_right_pads_[1] == 0))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// vector load A/B matrix from global memory
|
||||
if(!(ABlockTransferSrcVectorDim == 2 && BBlockTransferSrcVectorDim == 1 &&
|
||||
arg.Conv_K_ % ABlockTransferSrcScalarPerVector == 0 &&
|
||||
arg.Conv_C_ % BBlockTransferSrcScalarPerVector == 0))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
// vector store C matrix into global memory
|
||||
if(!(arg.Conv_C_ % CThreadTransferDstScalarPerVector == 0))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
// Gridwise GEMM size
|
||||
for(int i = 0; i < arg.a_grid_desc_k0_m_k1_container_.size(); i++)
|
||||
{
|
||||
if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_container_[i],
|
||||
arg.b_grid_desc_k0_n_k1_container_[i],
|
||||
arg.c_grid_desc_m_n_container_[i],
|
||||
arg.M01_,
|
||||
arg.N01_))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
|
||||
static auto MakeArgument(InDataType* p_in_grid,
|
||||
const WeiDataType* p_wei_grid,
|
||||
const OutDataType* p_out_grid,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t C,
|
||||
std::vector<ck::index_t> input_spatial_lengths,
|
||||
std::vector<ck::index_t> filter_spatial_lengths,
|
||||
std::vector<ck::index_t> output_spatial_lengths,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
{
|
||||
return Argument{p_in_grid,
|
||||
p_wei_grid,
|
||||
p_out_grid,
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
input_spatial_lengths,
|
||||
filter_spatial_lengths,
|
||||
output_spatial_lengths,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
1,
|
||||
1,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(void* p_in_grid,
|
||||
const void* p_wei_grid,
|
||||
const void* p_out_grid,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t C,
|
||||
std::vector<ck::index_t> input_spatial_lengths,
|
||||
std::vector<ck::index_t> filter_spatial_lengths,
|
||||
std::vector<ck::index_t> output_spatial_lengths,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op) override
|
||||
{
|
||||
return std::make_unique<Argument>(static_cast<InDataType*>(p_in_grid),
|
||||
static_cast<const WeiDataType*>(p_wei_grid),
|
||||
static_cast<const OutDataType*>(p_out_grid),
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
input_spatial_lengths,
|
||||
filter_spatial_lengths,
|
||||
output_spatial_lengths,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
1,
|
||||
1,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op);
|
||||
}
|
||||
|
||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< K0PerBlock
|
||||
<< ">";
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
47
device_operation/include/device_conv_bwd_data.hpp
Normal file
47
device_operation/include/device_conv_bwd_data.hpp
Normal file
@@ -0,0 +1,47 @@
|
||||
#ifndef DEVICE_CONV_BWD_DATA_HPP
|
||||
#define DEVICE_CONV_BWD_DATA_HPP
|
||||
|
||||
#include <iostream>
|
||||
#include "device_base.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
template <typename InElementwiseOperation,
|
||||
typename WeiElementwiseOperation,
|
||||
typename OutElementwiseOperation>
|
||||
struct DeviceConvBwdData : public BaseOperator
|
||||
{
|
||||
virtual std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(void* p_in,
|
||||
const void* p_wei,
|
||||
const void* p_out,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t C,
|
||||
std::vector<ck::index_t> input_spatial_lengths,
|
||||
std::vector<ck::index_t> filter_spatial_lengths,
|
||||
std::vector<ck::index_t> output_spatial_lengths,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op) = 0;
|
||||
|
||||
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
|
||||
};
|
||||
|
||||
template <typename InElementwiseOperation,
|
||||
typename WeiElementwiseOperation,
|
||||
typename OutElementwiseOperation>
|
||||
using DeviceConvBwdDataPtr = std::unique_ptr<
|
||||
DeviceConvBwdData<InElementwiseOperation, WeiElementwiseOperation, OutElementwiseOperation>>;
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
@@ -0,0 +1,83 @@
|
||||
#include <stdlib.h>
|
||||
#include "config.hpp"
|
||||
#include "device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "device_operation_instance.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace device_conv2d_bwd_data_instance {
|
||||
|
||||
using BF16 = ushort;
|
||||
using F32 = float;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
static constexpr auto ConvBwdDataDefault =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
|
||||
|
||||
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Filter1x1Stride1Pad0;
|
||||
|
||||
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances = std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_bf16_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(
|
||||
std::vector<DeviceConvBwdDataPtr<PassThrough, PassThrough, PassThrough>>& instances)
|
||||
{
|
||||
add_device_operation_instances(instances,
|
||||
device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances{});
|
||||
add_device_operation_instances(
|
||||
instances, device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_bf16_instances{});
|
||||
}
|
||||
|
||||
} // namespace device_conv2d_bwd_data_instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,85 @@
|
||||
#include <stdlib.h>
|
||||
#include "config.hpp"
|
||||
#include "device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "device_operation_instance.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace device_conv2d_bwd_data_instance {
|
||||
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
static constexpr auto ConvBwdDataDefault =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
|
||||
|
||||
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Filter1x1Stride1Pad0;
|
||||
|
||||
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances = std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
#if !CK_WORKAROUND_SWDEV_325164
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
#endif
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f16_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(
|
||||
std::vector<DeviceConvBwdDataPtr<PassThrough, PassThrough, PassThrough>>& instances)
|
||||
{
|
||||
add_device_operation_instances(instances,
|
||||
device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances{});
|
||||
add_device_operation_instances(
|
||||
instances, device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f16_instances{});
|
||||
}
|
||||
|
||||
} // namespace device_conv2d_bwd_data_instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,82 @@
|
||||
#include <stdlib.h>
|
||||
#include "config.hpp"
|
||||
#include "device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "device_operation_instance.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace device_conv2d_bwd_data_instance {
|
||||
|
||||
using F32 = float;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
static constexpr auto ConvBwdDataDefault =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
|
||||
|
||||
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Filter1x1Stride1Pad0;
|
||||
|
||||
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances = std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 4, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 4, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 4, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 4, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 4, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f32_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 4, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 4, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 4, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 4, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 4, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F32, F32, F32, F32, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 4, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 4, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(
|
||||
std::vector<DeviceConvBwdDataPtr<PassThrough, PassThrough, PassThrough>>& instances)
|
||||
{
|
||||
add_device_operation_instances(instances,
|
||||
device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances{});
|
||||
add_device_operation_instances(
|
||||
instances, device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f32_instances{});
|
||||
}
|
||||
|
||||
} // namespace device_conv2d_bwd_data_instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -0,0 +1,83 @@
|
||||
#include <stdlib.h>
|
||||
#include "config.hpp"
|
||||
#include "device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "device_operation_instance.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace device_conv2d_bwd_data_instance {
|
||||
|
||||
using DataType = int8_t;
|
||||
using AccType = int32_t;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
static constexpr auto ConvBwdDataDefault =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
|
||||
|
||||
static constexpr auto ConvBwdDataFilter1x1Stride1Pad0 =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Filter1x1Stride1Pad0;
|
||||
|
||||
// Compilation parameters for in[n, hi, wi, c] * wei[k, y, x, c] = out[n, ho, wo, k]
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances = std::tuple<
|
||||
// clang-format off
|
||||
//####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataDefault, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
using device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_int8_instances =
|
||||
std::tuple<
|
||||
// clang-format off
|
||||
//#####################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
|
||||
//#####################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Data| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//#####################################################################| | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//#####################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 1, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 2, 16, true, 7, 1>,
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< DataType, DataType, DataType, AccType, PassThrough, PassThrough, PassThrough, ConvBwdDataFilter1x1Stride1Pad0, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<2, 0, 1>, S<0, 2, 1>, 1, 4, 16, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(
|
||||
std::vector<DeviceConvBwdDataPtr<PassThrough, PassThrough, PassThrough>>& instances)
|
||||
{
|
||||
add_device_operation_instances(instances,
|
||||
device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances{});
|
||||
add_device_operation_instances(
|
||||
instances, device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_int8_instances{});
|
||||
}
|
||||
|
||||
} // namespace device_conv2d_bwd_data_instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -32,19 +32,19 @@ using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances = std::tuple<
|
||||
//################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//################################################################| | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
@@ -54,19 +54,19 @@ using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_bf16_instances = std::tuple<
|
||||
//################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//################################################################| | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
@@ -76,19 +76,19 @@ using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_bf16_instances = std::tuple
|
||||
//################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//################################################################| | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< ushort, ushort, ushort, F32, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
|
||||
@@ -32,19 +32,19 @@ using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances = std::tuple<
|
||||
//################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//################################################################| | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwdDefault, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
@@ -54,19 +54,19 @@ using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_int8_instances = std::tuple<
|
||||
//################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//################################################################| | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1P0, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
@@ -76,19 +76,19 @@ using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_int8_instances = std::tuple
|
||||
//################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
|
||||
//################################################################| | | | | Operation| Operation| Operation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
|
||||
//################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
|
||||
DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< int8_t, int8_t, int8_t, int32_t, PassThrough, PassThrough, PassThrough, ConvFwd1x1S1P0, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
|
||||
// clang-format on
|
||||
>;
|
||||
|
||||
|
||||
79
example/12_conv2d_bwd_data_xdl/README.md
Normal file
79
example/12_conv2d_bwd_data_xdl/README.md
Normal file
@@ -0,0 +1,79 @@
|
||||
# Instructions for ```conv2d_bwd_data_xdl``` Example
|
||||
|
||||
## Docker script
|
||||
```bash
|
||||
docker run \
|
||||
-it \
|
||||
--rm \
|
||||
--privileged \
|
||||
--group-add sudo \
|
||||
-w /root/workspace \
|
||||
-v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace \
|
||||
rocm/tensorflow:rocm4.3.1-tf2.6-dev \
|
||||
/bin/bash
|
||||
```
|
||||
|
||||
## Build ```conv2d_bwd_data_xdl```
|
||||
```bash
|
||||
mkdir build && cd build
|
||||
```
|
||||
|
||||
```bash
|
||||
# Need to specify target ID, example below is gfx908
|
||||
cmake \
|
||||
-D BUILD_DEV=OFF \
|
||||
-D CMAKE_BUILD_TYPE=Release \
|
||||
-D CMAKE_CXX_FLAGS="-DCK_AMD_GPU_GFX908 --amdgpu-target=gfx908 -O3 " \
|
||||
-D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \
|
||||
-D CMAKE_PREFIX_PATH=/opt/rocm \
|
||||
..
|
||||
```
|
||||
|
||||
```bash
|
||||
make -j conv2d_bwd_data_xdl
|
||||
```
|
||||
|
||||
## Run ```conv2d_bwd_data_xdl```
|
||||
```bash
|
||||
#arg1: verification (0=no, 1=yes)
|
||||
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
|
||||
#arg3: run kernel # of times (>1)
|
||||
#arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
|
||||
./bin/conv2d_bwd_data_xdl 0 1 5
|
||||
```
|
||||
|
||||
Result
|
||||
```
|
||||
in_n_c_hi_wi: dim 4, lengths {128, 256, 71, 71}, strides {1290496, 1, 18176, 256}
|
||||
wei_k_c_y_x: dim 4, lengths {256, 256, 3, 3}, strides {2304, 1, 768, 256}
|
||||
out_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
|
||||
arg.a_grid_desc_k0_m_k1_container_{128, 175232, 8}
|
||||
arg.b_grid_desc_k0_n_k1_container_{128, 256, 8}
|
||||
arg.c_grid_desc_m_n_container_{ 175232, 256}
|
||||
arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_( 2738, 4, 2, 2, 4, 2 )
|
||||
launch_and_time_kernel: grid_dim {2738, 1, 1}, block_dim {256, 1, 1}
|
||||
Warm up
|
||||
Start running 1 times...
|
||||
arg.a_grid_desc_k0_m_k1_container_{64, 175232, 8}
|
||||
arg.b_grid_desc_k0_n_k1_container_{64, 256, 8}
|
||||
arg.c_grid_desc_m_n_container_{ 175232, 256}
|
||||
arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_( 2738, 4, 2, 2, 4, 2 )
|
||||
launch_and_time_kernel: grid_dim {2738, 1, 1}, block_dim {256, 1, 1}
|
||||
Warm up
|
||||
Start running 1 times...
|
||||
arg.a_grid_desc_k0_m_k1_container_{64, 175232, 8}
|
||||
arg.b_grid_desc_k0_n_k1_container_{64, 256, 8}
|
||||
arg.c_grid_desc_m_n_container_{ 175232, 256}
|
||||
arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_( 2738, 4, 2, 2, 4, 2 )
|
||||
launch_and_time_kernel: grid_dim {2738, 1, 1}, block_dim {256, 1, 1}
|
||||
Warm up
|
||||
Start running 1 times...
|
||||
arg.a_grid_desc_k0_m_k1_container_{32, 175232, 8}
|
||||
arg.b_grid_desc_k0_n_k1_container_{32, 256, 8}
|
||||
arg.c_grid_desc_m_n_container_{ 175232, 256}
|
||||
arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_container_( 2738, 4, 2, 2, 4, 2 )
|
||||
launch_and_time_kernel: grid_dim {2738, 1, 1}, block_dim {256, 1, 1}
|
||||
Warm up
|
||||
Start running 1 times...
|
||||
Perf: 2.45966 ms, 79.5597 TFlops, 169.325 GB/s
|
||||
```
|
||||
247
example/12_conv2d_bwd_data_xdl/conv2d_bwd_data_xdl.cpp
Normal file
247
example/12_conv2d_bwd_data_xdl/conv2d_bwd_data_xdl.cpp
Normal file
@@ -0,0 +1,247 @@
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
#include <initializer_list>
|
||||
#include <cstdlib>
|
||||
#include <stdlib.h>
|
||||
#include <half.hpp>
|
||||
#include "config.hpp"
|
||||
#include "print.hpp"
|
||||
#include "device.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
#include "host_tensor_generator.hpp"
|
||||
#include "device_tensor.hpp"
|
||||
#include "tensor_layout.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk.hpp"
|
||||
#include "reference_conv_bwd_data.hpp"
|
||||
|
||||
using InDataType = ck::half_t;
|
||||
using WeiDataType = ck::half_t;
|
||||
using OutDataType = ck::half_t;
|
||||
using AccDataType = float;
|
||||
|
||||
template <ck::index_t... Is>
|
||||
using S = ck::Sequence<Is...>;
|
||||
|
||||
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
static constexpr auto ConvBwdDefault =
|
||||
ck::tensor_operation::device::ConvolutionBackwardDataSpecialization_t::Default;
|
||||
|
||||
using DeviceConvBwdDataInstance = ck::tensor_operation::device::
|
||||
DeviceConv2dBwdDataXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<
|
||||
InDataType, // InDataType
|
||||
WeiDataType, // WeiDataType
|
||||
OutDataType, // OutDataType
|
||||
AccDataType, // AccDataType
|
||||
InElementOp, // InElementwiseOperation
|
||||
WeiElementOp, // WeiElementwiseOperation
|
||||
OutElementOp, // OutElementwiseOperation
|
||||
ConvBwdDefault, // ConvolutionBackwardDataSpecialization_t
|
||||
256, // BlockSize
|
||||
128, // MPerBlock
|
||||
128, // NPerBlock
|
||||
4, // K0PerBlock
|
||||
8, // K1
|
||||
32, // MPerXdl
|
||||
32, // NPerXdl
|
||||
2, // MXdlPerWave
|
||||
2, // NXdlPerWave
|
||||
S<4, 64, 1>, // ABlockTransferThreadClusterLengths_K0_M_K1
|
||||
S<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder
|
||||
S<1, 0, 2>, // ABlockTransferSrcAccessOrder
|
||||
2, // ABlockTransferSrcVectorDim
|
||||
8, // ABlockTransferSrcScalarPerVector
|
||||
8, // ABlockTransferDstScalarPerVector_K1
|
||||
true, // ABlockLdsAddExtraM
|
||||
S<4, 64, 1>, // BBlockTransferThreadClusterLengths_K0_N_K1
|
||||
S<2, 0, 1>, // BBlockTransferThreadClusterArrangeOrder
|
||||
S<0, 2, 1>, // BBlockTransferSrcAccessOrder
|
||||
1, // BBlockTransferSrcVectorDim
|
||||
2, // BBlockTransferSrcScalarPerVector
|
||||
8, // BBlockTransferDstScalarPerVector_K1
|
||||
true, // BBlockLdsAddExtraN
|
||||
7,
|
||||
1>; // GemmCThreadTransferDstScalarPerVector
|
||||
|
||||
using ReferenceConvBwdInstance = ck::tensor_operation::host::ReferenceConvBwdData<InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
OutElementOp>;
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
bool do_verification = 0;
|
||||
int init_method = 0;
|
||||
int nrepeat = 5;
|
||||
|
||||
// Conv shape
|
||||
ck::index_t N = 128;
|
||||
ck::index_t K = 256;
|
||||
ck::index_t C = 256;
|
||||
ck::index_t Y = 3;
|
||||
ck::index_t X = 3;
|
||||
ck::index_t Hi = 71;
|
||||
ck::index_t Wi = 71;
|
||||
ck::index_t conv_stride_h = 2;
|
||||
ck::index_t conv_stride_w = 2;
|
||||
ck::index_t conv_dilation_h = 1;
|
||||
ck::index_t conv_dilation_w = 1;
|
||||
ck::index_t in_left_pad_h = 1;
|
||||
ck::index_t in_left_pad_w = 1;
|
||||
ck::index_t in_right_pad_h = 1;
|
||||
ck::index_t in_right_pad_w = 1;
|
||||
|
||||
if(argc == 4)
|
||||
{
|
||||
do_verification = std::stoi(argv[1]);
|
||||
init_method = std::stoi(argv[2]);
|
||||
nrepeat = std::stoi(argv[3]);
|
||||
}
|
||||
else if(argc == 19)
|
||||
{
|
||||
do_verification = std::stoi(argv[1]);
|
||||
init_method = std::stoi(argv[2]);
|
||||
nrepeat = std::stoi(argv[3]);
|
||||
|
||||
N = std::stoi(argv[4]);
|
||||
K = std::stoi(argv[5]);
|
||||
C = std::stoi(argv[6]);
|
||||
Y = std::stoi(argv[7]);
|
||||
X = std::stoi(argv[8]);
|
||||
Hi = std::stoi(argv[9]);
|
||||
Wi = std::stoi(argv[10]);
|
||||
conv_stride_h = std::stoi(argv[11]);
|
||||
conv_stride_w = std::stoi(argv[12]);
|
||||
conv_dilation_h = std::stoi(argv[13]);
|
||||
conv_dilation_w = std::stoi(argv[14]);
|
||||
in_left_pad_h = std::stoi(argv[15]);
|
||||
in_left_pad_w = std::stoi(argv[16]);
|
||||
in_right_pad_h = std::stoi(argv[17]);
|
||||
in_right_pad_w = std::stoi(argv[18]);
|
||||
}
|
||||
else
|
||||
{
|
||||
printf("arg1: verification (0=no, 1=yes)\n");
|
||||
printf("arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n");
|
||||
printf("arg3: run kernel # of times (>1)\n");
|
||||
printf("arg4 to 18: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, "
|
||||
"RightPx\n");
|
||||
exit(0);
|
||||
}
|
||||
|
||||
const ck::index_t YEff = (Y - 1) * conv_dilation_h + 1;
|
||||
const ck::index_t XEff = (X - 1) * conv_dilation_w + 1;
|
||||
|
||||
const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - YEff) / conv_stride_h + 1;
|
||||
const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
|
||||
|
||||
const std::vector<ck::index_t> conv_filter_strides{{conv_stride_h, conv_stride_w}};
|
||||
const std::vector<ck::index_t> conv_filter_dilations{{conv_dilation_h, conv_dilation_w}};
|
||||
const std::vector<ck::index_t> input_left_pads{{in_left_pad_h, in_left_pad_w}};
|
||||
const std::vector<ck::index_t> input_right_pads{{in_right_pad_h, in_right_pad_w}};
|
||||
|
||||
// tensor layout
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W) {
|
||||
return HostTensorDescriptor(std::vector<std::size_t>({N_, C_, H, W}),
|
||||
std::vector<std::size_t>({C_ * H * W, 1, W * C_, C_}));
|
||||
};
|
||||
|
||||
Tensor<OutDataType> out_n_k_ho_wo(f_host_tensor_descriptor(N, K, Ho, Wo));
|
||||
Tensor<WeiDataType> wei_k_c_y_x(f_host_tensor_descriptor(K, C, Y, X));
|
||||
Tensor<InDataType> in_n_c_hi_wi_host_result(f_host_tensor_descriptor(N, C, Hi, Wi));
|
||||
Tensor<InDataType> in_n_c_hi_wi_device_result(f_host_tensor_descriptor(N, C, Hi, Wi));
|
||||
|
||||
std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi_host_result.mDesc << std::endl;
|
||||
std::cout << "wei_k_c_y_x: " << wei_k_c_y_x.mDesc << std::endl;
|
||||
std::cout << "out_n_k_ho_wo: " << out_n_k_ho_wo.mDesc << std::endl;
|
||||
|
||||
switch(init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
out_n_k_ho_wo.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
|
||||
wei_k_c_y_x.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
out_n_k_ho_wo.GenerateTensorValue(GeneratorTensor_1<OutDataType>{1});
|
||||
wei_k_c_y_x.GenerateTensorValue(GeneratorTensor_1<WeiDataType>{1});
|
||||
}
|
||||
|
||||
DeviceMem in_device_buf(sizeof(InDataType) *
|
||||
in_n_c_hi_wi_device_result.mDesc.GetElementSpace());
|
||||
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei_k_c_y_x.mDesc.GetElementSpace());
|
||||
DeviceMem out_device_buf(sizeof(OutDataType) * out_n_k_ho_wo.mDesc.GetElementSpace());
|
||||
|
||||
out_device_buf.ToDevice(out_n_k_ho_wo.mData.data());
|
||||
wei_device_buf.ToDevice(wei_k_c_y_x.mData.data());
|
||||
|
||||
// do GEMM
|
||||
auto conv = DeviceConvBwdDataInstance{};
|
||||
auto invoker = conv.MakeInvoker();
|
||||
auto argument = conv.MakeArgument(static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
|
||||
static_cast<WeiDataType*>(wei_device_buf.GetDeviceBuffer()),
|
||||
static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
std::vector<ck::index_t>{{Hi, Wi}},
|
||||
std::vector<ck::index_t>{{Y, X}},
|
||||
std::vector<ck::index_t>{{Ho, Wo}},
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
|
||||
if(!conv.IsSupportedArgument(argument))
|
||||
{
|
||||
throw std::runtime_error(
|
||||
"wrong! device_conv with the specified compilation parameters does "
|
||||
"not support this Conv problem");
|
||||
}
|
||||
|
||||
float ave_time = invoker.Run(argument, nrepeat);
|
||||
|
||||
std::size_t flop = std::size_t(2) * N * K * Ho * Wo * C * Y * X;
|
||||
|
||||
std::size_t num_btype = sizeof(InDataType) * (N * C * Hi * Wi) +
|
||||
sizeof(WeiDataType) * (K * C * Y * X) +
|
||||
sizeof(OutDataType) * (N * K * Ho * Wo);
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
|
||||
<< std::endl;
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
auto ref_conv = ReferenceConvBwdInstance{};
|
||||
auto ref_invoker = ref_conv.MakeInvoker();
|
||||
|
||||
auto ref_argument = ref_conv.MakeArgument(in_n_c_hi_wi_host_result,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
|
||||
in_device_buf.FromDevice(in_n_c_hi_wi_device_result.mData.data());
|
||||
|
||||
check_error(in_n_c_hi_wi_host_result, in_n_c_hi_wi_device_result);
|
||||
}
|
||||
}
|
||||
@@ -24,6 +24,7 @@ set(GEMM_XDL_ALPHA_BETA_SOURCE 8_gemm_xdl_alpha_beta/gemm_xdl_alpha_beta.cpp)
|
||||
set(CONV2D_FWD_XDL_INT8_SOURCE 9_conv2d_fwd_xdl_int8/conv2d_fwd_xdl_int8.cpp)
|
||||
set(CONV3D_FWD_XDL_SOURCE 10_conv3d_fwd_xdl/conv3d_fwd_xdl.cpp)
|
||||
set(CONVND_FWD_XDL_SOURCE 11_convnd_fwd_xdl/convnd_fwd_xdl.cpp)
|
||||
set(CONV2D_BWD_DATA_XDL_SOURCE 12_conv2d_bwd_data_xdl/conv2d_bwd_data_xdl.cpp)
|
||||
|
||||
add_executable(gemm_xdl ${GEMM_XDL_SOURCE})
|
||||
add_executable(gemm_xdl_bias_relu ${GEMM_XDL_BIAS_RELU_SOURCE})
|
||||
@@ -36,6 +37,7 @@ add_executable(gemm_xdl_alpha_beta ${GEMM_XDL_ALPHA_BETA_SOURCE})
|
||||
add_executable(conv2d_fwd_xdl_int8 ${CONV2D_FWD_XDL_INT8_SOURCE})
|
||||
add_executable(conv3d_fwd_xdl ${CONV3D_FWD_XDL_SOURCE})
|
||||
add_executable(convnd_fwd_xdl ${CONVND_FWD_XDL_SOURCE})
|
||||
add_executable(conv2d_bwd_data_xdl ${CONV2D_BWD_DATA_XDL_SOURCE})
|
||||
|
||||
target_link_libraries(gemm_xdl PRIVATE host_tensor)
|
||||
target_link_libraries(gemm_xdl_bias_relu PRIVATE host_tensor)
|
||||
@@ -48,3 +50,5 @@ target_link_libraries(gemm_xdl_alpha_beta PRIVATE host_tensor)
|
||||
target_link_libraries(conv2d_fwd_xdl_int8 PRIVATE host_tensor)
|
||||
target_link_libraries(conv3d_fwd_xdl PRIVATE host_tensor)
|
||||
target_link_libraries(convnd_fwd_xdl PRIVATE host_tensor)
|
||||
target_link_libraries(conv2d_bwd_data_xdl PRIVATE host_tensor)
|
||||
|
||||
|
||||
@@ -25,6 +25,7 @@ set(PROFILER_SOURCE
|
||||
src/profile_conv_fwd_bias_relu_add.cpp
|
||||
src/profile_conv_fwd_bias_relu_atomic_add.cpp
|
||||
src/profile_batched_gemm.cpp
|
||||
src/profile_conv_bwd_data.cpp
|
||||
)
|
||||
|
||||
add_executable(ckProfiler ${PROFILER_SOURCE})
|
||||
@@ -39,3 +40,4 @@ target_link_libraries(ckProfiler PRIVATE device_conv2d_fwd_bias_relu_instance)
|
||||
target_link_libraries(ckProfiler PRIVATE device_conv2d_fwd_bias_relu_add_instance)
|
||||
target_link_libraries(ckProfiler PRIVATE device_conv2d_fwd_bias_relu_atomic_add_instance)
|
||||
target_link_libraries(ckProfiler PRIVATE device_batched_gemm_instance)
|
||||
target_link_libraries(ckProfiler PRIVATE device_conv2d_bwd_data_instance)
|
||||
|
||||
278
profiler/include/profile_conv_bwd_data_impl.hpp
Normal file
278
profiler/include/profile_conv_bwd_data_impl.hpp
Normal file
@@ -0,0 +1,278 @@
|
||||
#pragma once
|
||||
#include "config.hpp"
|
||||
#include "device.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
#include "host_tensor_generator.hpp"
|
||||
#include "tensor_layout.hpp"
|
||||
#include "device_tensor.hpp"
|
||||
#include "device_conv_bwd_data.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "reference_conv_bwd_data.hpp"
|
||||
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
using BF16 = ushort;
|
||||
using INT8 = int8_t;
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace device_conv2d_bwd_data_instance {
|
||||
|
||||
using DeviceConvBwdDataNoOpPtr =
|
||||
DeviceConvBwdDataPtr<ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough>;
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
} // namespace device_conv2d_bwd_data_instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
|
||||
namespace ck {
|
||||
namespace profiler {
|
||||
|
||||
template <int NDimSpatial,
|
||||
typename InDataType,
|
||||
typename WeiDataType,
|
||||
typename OutDataType,
|
||||
typename InLayout,
|
||||
typename WeiLayout,
|
||||
typename OutLayout>
|
||||
void profile_conv_bwd_data_impl(int do_verification,
|
||||
int init_method,
|
||||
bool do_log,
|
||||
int nrepeat,
|
||||
ck::index_t N,
|
||||
ck::index_t K,
|
||||
ck::index_t C,
|
||||
std::vector<ck::index_t> input_spatial_lengths,
|
||||
std::vector<ck::index_t> filter_spatial_lengths,
|
||||
std::vector<ck::index_t> output_spatial_lengths,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads)
|
||||
{
|
||||
const ck::index_t Y = filter_spatial_lengths[0];
|
||||
const ck::index_t X = filter_spatial_lengths[1];
|
||||
|
||||
const ck::index_t Hi = input_spatial_lengths[0];
|
||||
const ck::index_t Wi = input_spatial_lengths[1];
|
||||
|
||||
const ck::index_t Ho = output_spatial_lengths[0];
|
||||
const ck::index_t Wo = output_spatial_lengths[1];
|
||||
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W, auto layout) {
|
||||
if constexpr(is_same<decltype(layout), ck::tensor_layout::convolution::NCHW>::value ||
|
||||
is_same<decltype(layout), ck::tensor_layout::convolution::KCYX>::value ||
|
||||
is_same<decltype(layout), ck::tensor_layout::convolution::NKHW>::value)
|
||||
{
|
||||
return HostTensorDescriptor(std::vector<std::size_t>({N_, C_, H, W}),
|
||||
std::vector<std::size_t>({C_ * H * W, H * W, W, 1}));
|
||||
}
|
||||
else if constexpr(is_same<decltype(layout), tensor_layout::convolution::NHWC>::value ||
|
||||
is_same<decltype(layout), tensor_layout::convolution::KYXC>::value ||
|
||||
is_same<decltype(layout), tensor_layout::convolution::NHWK>::value)
|
||||
{
|
||||
return HostTensorDescriptor(std::vector<std::size_t>({N_, C_, H, W}),
|
||||
std::vector<std::size_t>({C_ * H * W, 1, W * C_, C_}));
|
||||
}
|
||||
};
|
||||
|
||||
Tensor<InDataType> in_n_c_hi_wi_host_result(f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{}));
|
||||
Tensor<InDataType> in_n_c_hi_wi_device_result(
|
||||
f_host_tensor_descriptor(N, C, Hi, Wi, InLayout{}));
|
||||
Tensor<WeiDataType> wei_k_c_y_x(f_host_tensor_descriptor(K, C, Y, X, WeiLayout{}));
|
||||
Tensor<OutDataType> out_n_k_ho_wo(f_host_tensor_descriptor(N, K, Ho, Wo, OutLayout{}));
|
||||
|
||||
std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi_host_result.mDesc << std::endl;
|
||||
std::cout << "wei_k_c_y_x: " << wei_k_c_y_x.mDesc << std::endl;
|
||||
std::cout << "out_n_k_ho_wo: " << out_n_k_ho_wo.mDesc << std::endl;
|
||||
|
||||
switch(init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
out_n_k_ho_wo.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
|
||||
wei_k_c_y_x.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
out_n_k_ho_wo.GenerateTensorValue(GeneratorTensor_3<InDataType>{0.0, 1.0});
|
||||
wei_k_c_y_x.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.5, 0.5});
|
||||
}
|
||||
|
||||
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
const auto in_element_op = InElementOp{};
|
||||
const auto wei_element_op = WeiElementOp{};
|
||||
const auto out_element_op = OutElementOp{};
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
using ReferenceConvBwdDataInstance =
|
||||
ck::tensor_operation::host::ReferenceConvBwdData<InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
OutElementOp>;
|
||||
|
||||
auto ref_conv = ReferenceConvBwdDataInstance{};
|
||||
auto ref_invoker = ref_conv.MakeInvoker();
|
||||
auto ref_argument = ref_conv.MakeArgument(in_n_c_hi_wi_host_result,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op);
|
||||
|
||||
ref_invoker.Run(ref_argument);
|
||||
}
|
||||
|
||||
DeviceMem in_device_buf(sizeof(InDataType) *
|
||||
in_n_c_hi_wi_device_result.mDesc.GetElementSpace());
|
||||
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei_k_c_y_x.mDesc.GetElementSpace());
|
||||
DeviceMem out_device_buf(sizeof(OutDataType) * out_n_k_ho_wo.mDesc.GetElementSpace());
|
||||
|
||||
out_device_buf.ToDevice(out_n_k_ho_wo.mData.data());
|
||||
wei_device_buf.ToDevice(wei_k_c_y_x.mData.data());
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
using DeviceConvBwdDataNoOpPtr =
|
||||
ck::tensor_operation::device::DeviceConvBwdDataPtr<PassThrough, PassThrough, PassThrough>;
|
||||
|
||||
// add device Conv instances
|
||||
std::vector<DeviceConvBwdDataNoOpPtr> conv_ptrs;
|
||||
if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, float> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, float> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, float>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(conv_ptrs);
|
||||
}
|
||||
else if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, ck::half_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, ck::half_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, ck::half_t>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(conv_ptrs);
|
||||
}
|
||||
else if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, ushort> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, ushort> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, ushort>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(conv_ptrs);
|
||||
}
|
||||
else if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, int8_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, int8_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, int8_t>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(conv_ptrs);
|
||||
}
|
||||
|
||||
if(conv_ptrs.size() <= 0)
|
||||
{
|
||||
throw std::runtime_error("wrong! no device Conv instance found");
|
||||
}
|
||||
|
||||
std::string best_conv_name;
|
||||
float best_ave_time = 0;
|
||||
float best_tflops = 0;
|
||||
float best_gb_per_sec = 0;
|
||||
|
||||
// profile device Conv instances
|
||||
for(auto& conv_ptr : conv_ptrs)
|
||||
{
|
||||
auto argument_ptr = conv_ptr->MakeArgumentPointer(
|
||||
static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
|
||||
static_cast<WeiDataType*>(wei_device_buf.GetDeviceBuffer()),
|
||||
static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
input_spatial_lengths,
|
||||
filter_spatial_lengths,
|
||||
output_spatial_lengths,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op);
|
||||
|
||||
auto invoker_ptr = conv_ptr->MakeInvokerPointer();
|
||||
|
||||
if(conv_ptr->IsSupportedArgument(argument_ptr.get()))
|
||||
{
|
||||
std::string conv_name = conv_ptr->GetTypeString();
|
||||
|
||||
float ave_time = invoker_ptr->Run(argument_ptr.get(), nrepeat);
|
||||
|
||||
std::size_t flop = std::size_t(2) * N * K * Ho * Wo * C * Y * X;
|
||||
|
||||
std::size_t num_btype = sizeof(InDataType) * (N * C * Hi * Wi) +
|
||||
sizeof(WeiDataType) * (K * C * Y * X) +
|
||||
sizeof(OutDataType) * (N * K * Ho * Wo);
|
||||
|
||||
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
|
||||
|
||||
float gb_per_sec = num_btype / 1.E6 / ave_time;
|
||||
|
||||
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec
|
||||
<< " GB/s, " << conv_name << std::endl;
|
||||
|
||||
if(tflops > best_tflops)
|
||||
{
|
||||
best_conv_name = conv_name;
|
||||
best_tflops = tflops;
|
||||
best_ave_time = ave_time;
|
||||
best_gb_per_sec = gb_per_sec;
|
||||
}
|
||||
|
||||
if(do_verification)
|
||||
{
|
||||
in_device_buf.FromDevice(in_n_c_hi_wi_device_result.mData.data());
|
||||
|
||||
check_error(in_n_c_hi_wi_host_result, in_n_c_hi_wi_device_result);
|
||||
|
||||
if(do_log)
|
||||
{
|
||||
LogRangeAsType<float>(std::cout << "in : ", out_n_k_ho_wo.mData, ",")
|
||||
<< std::endl;
|
||||
LogRangeAsType<float>(std::cout << "wei: ", wei_k_c_y_x.mData, ",")
|
||||
<< std::endl;
|
||||
LogRangeAsType<float>(
|
||||
std::cout << "out_host : ", in_n_c_hi_wi_host_result.mData, ",")
|
||||
<< std::endl;
|
||||
LogRangeAsType<float>(
|
||||
std::cout << "out_device: ", in_n_c_hi_wi_device_result.mData, ",")
|
||||
<< std::endl;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
std::cout << "Best Perf: " << best_ave_time << " ms, " << best_tflops << " TFlops, "
|
||||
<< best_gb_per_sec << " GB/s, " << best_conv_name << std::endl;
|
||||
}
|
||||
|
||||
} // namespace profiler
|
||||
} // namespace ck
|
||||
191
profiler/src/profile_conv_bwd_data.cpp
Normal file
191
profiler/src/profile_conv_bwd_data.cpp
Normal file
@@ -0,0 +1,191 @@
|
||||
#include <iostream>
|
||||
#include <numeric>
|
||||
#include <initializer_list>
|
||||
#include <cstdlib>
|
||||
#include <stdlib.h>
|
||||
#include <half.hpp>
|
||||
#include "profile_conv_bwd_data_impl.hpp"
|
||||
|
||||
enum ConvDataType
|
||||
{
|
||||
F32_F32_F32, // 0
|
||||
F16_F16_F16, // 1
|
||||
BF16_BF16_BF16, // 2
|
||||
INT8_INT8_INT8, // 3
|
||||
};
|
||||
|
||||
enum ConvInputLayout
|
||||
{
|
||||
NCHW, // 0
|
||||
NHWC, // 1
|
||||
};
|
||||
|
||||
enum ConvWeightLayout
|
||||
{
|
||||
KCYX, // 0
|
||||
KYXC, // 1
|
||||
};
|
||||
|
||||
enum ConvOutputLayout
|
||||
{
|
||||
NKHW, // 0
|
||||
NHWK, // 1
|
||||
};
|
||||
|
||||
int profile_conv_bwd_data(int argc, char* argv[])
|
||||
{
|
||||
if(argc != 25)
|
||||
{
|
||||
printf("arg1: tensor operation (conv_bwd: BackwardConvolution)\n");
|
||||
printf("arg2: data type (0: fp32; 1: fp16)\n");
|
||||
printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
|
||||
printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
|
||||
printf("arg5: output tensor layout (0: NKHW; 1: NHWK)\n");
|
||||
printf("arg6: verification (0: no; 1: yes)\n");
|
||||
printf("arg7: initialization (0: no init; 1: integer value; 2: decimal value)\n");
|
||||
printf("arg8: print tensor value (0: no; 1: yes)\n");
|
||||
printf("arg9: run kernel # of times (>1)\n");
|
||||
printf("arg10 to 24: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, "
|
||||
"RightPx\n");
|
||||
exit(1);
|
||||
}
|
||||
|
||||
const int data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
|
||||
const int in_layout = static_cast<ConvInputLayout>(std::stoi(argv[3]));
|
||||
const int wei_layout = static_cast<ConvWeightLayout>(std::stoi(argv[4]));
|
||||
const int out_layout = static_cast<ConvOutputLayout>(std::stoi(argv[5]));
|
||||
const bool do_verification = std::stoi(argv[6]);
|
||||
const int init_method = std::stoi(argv[7]);
|
||||
const bool do_log = std::stoi(argv[8]);
|
||||
const int nrepeat = std::stoi(argv[9]);
|
||||
|
||||
const ck::index_t N = std::stoi(argv[10]);
|
||||
const ck::index_t K = std::stoi(argv[11]);
|
||||
const ck::index_t C = std::stoi(argv[12]);
|
||||
const ck::index_t Y = std::stoi(argv[13]);
|
||||
const ck::index_t X = std::stoi(argv[14]);
|
||||
const ck::index_t Hi = std::stoi(argv[15]);
|
||||
const ck::index_t Wi = std::stoi(argv[16]);
|
||||
|
||||
const ck::index_t conv_stride_h = std::stoi(argv[17]);
|
||||
const ck::index_t conv_stride_w = std::stoi(argv[18]);
|
||||
const ck::index_t conv_dilation_h = std::stoi(argv[19]);
|
||||
const ck::index_t conv_dilation_w = std::stoi(argv[20]);
|
||||
const ck::index_t in_left_pad_h = std::stoi(argv[21]);
|
||||
const ck::index_t in_left_pad_w = std::stoi(argv[22]);
|
||||
const ck::index_t in_right_pad_h = std::stoi(argv[23]);
|
||||
const ck::index_t in_right_pad_w = std::stoi(argv[24]);
|
||||
|
||||
const ck::index_t YEff = (Y - 1) * conv_dilation_h + 1;
|
||||
const ck::index_t XEff = (X - 1) * conv_dilation_w + 1;
|
||||
|
||||
const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - YEff) / conv_stride_h + 1;
|
||||
const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
|
||||
|
||||
if(data_type == ConvDataType::F32_F32_F32 && in_layout == ConvInputLayout::NHWC &&
|
||||
wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
|
||||
{
|
||||
ck::profiler::profile_conv_bwd_data_impl<2,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
ck::tensor_layout::convolution::NHWC,
|
||||
ck::tensor_layout::convolution::KYXC,
|
||||
ck::tensor_layout::convolution::NHWK>(
|
||||
do_verification,
|
||||
init_method,
|
||||
do_log,
|
||||
nrepeat,
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
std::vector<ck::index_t>{Hi, Wi},
|
||||
std::vector<ck::index_t>{Y, X},
|
||||
std::vector<ck::index_t>{Ho, Wo},
|
||||
std::vector<ck::index_t>{conv_stride_h, conv_stride_w},
|
||||
std::vector<ck::index_t>{conv_dilation_h, conv_dilation_w},
|
||||
std::vector<ck::index_t>{in_left_pad_h, in_left_pad_w},
|
||||
std::vector<ck::index_t>{in_right_pad_h, in_right_pad_w});
|
||||
}
|
||||
else if(data_type == ConvDataType::F16_F16_F16 && in_layout == ConvInputLayout::NHWC &&
|
||||
wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
|
||||
{
|
||||
ck::profiler::profile_conv_bwd_data_impl<2,
|
||||
ck::half_t,
|
||||
ck::half_t,
|
||||
ck::half_t,
|
||||
ck::tensor_layout::convolution::NHWC,
|
||||
ck::tensor_layout::convolution::KYXC,
|
||||
ck::tensor_layout::convolution::NHWK>(
|
||||
do_verification,
|
||||
init_method,
|
||||
do_log,
|
||||
nrepeat,
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
std::vector<ck::index_t>{Hi, Wi},
|
||||
std::vector<ck::index_t>{Y, X},
|
||||
std::vector<ck::index_t>{Ho, Wo},
|
||||
std::vector<ck::index_t>{conv_stride_h, conv_stride_w},
|
||||
std::vector<ck::index_t>{conv_dilation_h, conv_dilation_w},
|
||||
std::vector<ck::index_t>{in_left_pad_h, in_left_pad_w},
|
||||
std::vector<ck::index_t>{in_right_pad_h, in_right_pad_w});
|
||||
}
|
||||
else if(data_type == ConvDataType::BF16_BF16_BF16 && in_layout == ConvInputLayout::NHWC &&
|
||||
wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
|
||||
{
|
||||
ck::profiler::profile_conv_bwd_data_impl<2,
|
||||
uint16_t,
|
||||
uint16_t,
|
||||
uint16_t,
|
||||
ck::tensor_layout::convolution::NHWC,
|
||||
ck::tensor_layout::convolution::KYXC,
|
||||
ck::tensor_layout::convolution::NHWK>(
|
||||
do_verification,
|
||||
init_method,
|
||||
do_log,
|
||||
nrepeat,
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
std::vector<ck::index_t>{Hi, Wi},
|
||||
std::vector<ck::index_t>{Y, X},
|
||||
std::vector<ck::index_t>{Ho, Wo},
|
||||
std::vector<ck::index_t>{conv_stride_h, conv_stride_w},
|
||||
std::vector<ck::index_t>{conv_dilation_h, conv_dilation_w},
|
||||
std::vector<ck::index_t>{in_left_pad_h, in_left_pad_w},
|
||||
std::vector<ck::index_t>{in_right_pad_h, in_right_pad_w});
|
||||
}
|
||||
else if(data_type == ConvDataType::INT8_INT8_INT8 && in_layout == ConvInputLayout::NHWC &&
|
||||
wei_layout == ConvWeightLayout::KYXC && out_layout == ConvOutputLayout::NHWK)
|
||||
{
|
||||
ck::profiler::profile_conv_bwd_data_impl<2,
|
||||
int8_t,
|
||||
int8_t,
|
||||
int8_t,
|
||||
ck::tensor_layout::convolution::NHWC,
|
||||
ck::tensor_layout::convolution::KYXC,
|
||||
ck::tensor_layout::convolution::NHWK>(
|
||||
do_verification,
|
||||
init_method,
|
||||
do_log,
|
||||
nrepeat,
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
std::vector<ck::index_t>{Hi, Wi},
|
||||
std::vector<ck::index_t>{Y, X},
|
||||
std::vector<ck::index_t>{Ho, Wo},
|
||||
std::vector<ck::index_t>{conv_stride_h, conv_stride_w},
|
||||
std::vector<ck::index_t>{conv_dilation_h, conv_dilation_w},
|
||||
std::vector<ck::index_t>{in_left_pad_h, in_left_pad_w},
|
||||
std::vector<ck::index_t>{in_right_pad_h, in_right_pad_w});
|
||||
}
|
||||
else
|
||||
{
|
||||
throw std::runtime_error("wrong! this Conv data_type & layout is not implemented");
|
||||
}
|
||||
|
||||
return 1;
|
||||
}
|
||||
@@ -14,6 +14,7 @@ int profile_conv_fwd(int, char*[]);
|
||||
int profile_conv_fwd_bias_relu(int, char*[]);
|
||||
int profile_conv_fwd_bias_relu_add(int, char*[]);
|
||||
int profile_conv_fwd_bias_relu_atomic_add(int, char*[]);
|
||||
int profile_conv_bwd_data(int, char*[]);
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
@@ -53,6 +54,10 @@ int main(int argc, char* argv[])
|
||||
{
|
||||
return profile_conv_fwd_bias_relu_atomic_add(argc, argv);
|
||||
}
|
||||
else if(strcmp(argv[1], "conv_bwd") == 0)
|
||||
{
|
||||
return profile_conv_bwd_data(argc, argv);
|
||||
}
|
||||
else
|
||||
{
|
||||
// clang-format off
|
||||
@@ -63,7 +68,8 @@ int main(int argc, char* argv[])
|
||||
" conv_fwd: ForwardConvolution\n"
|
||||
" conv_fwd_bias_relu: ForwardConvolution+Bias+ReLU\n"
|
||||
" conv_fwd_bias_relu_add: ForwardConvolution+Bias+ReLU+Add\n"
|
||||
" conv_fwd_bias_relu_atomic_add: ForwardConvolution+Bias+ReLU+AtomicAdd\n");
|
||||
" conv_fwd_bias_relu_atomic_add: ForwardConvolution+Bias+ReLU+AtomicAdd\n"
|
||||
" conv_bwd: BackwardConvolution\n");
|
||||
// clang-format on
|
||||
|
||||
return 0;
|
||||
|
||||
192
reference_operation/include/reference_conv_bwd_data.hpp
Normal file
192
reference_operation/include/reference_conv_bwd_data.hpp
Normal file
@@ -0,0 +1,192 @@
|
||||
#ifndef REFERENCE_CONV_BWD_DATA_HPP
|
||||
#define REFERENCE_CONV_BWD_DATA_HPP
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
#include "device_base.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace host {
|
||||
|
||||
// out[N, K, Ho, Wo] = in[N, C, Hi, Wi] * wei[K, C, Y, X]
|
||||
template <typename InDataType,
|
||||
typename WeiDataType,
|
||||
typename OutDataType,
|
||||
typename InElementwiseOperation,
|
||||
typename WeiElementwiseOperation,
|
||||
typename OutElementwiseOperation>
|
||||
struct ReferenceConvBwdData : public device::BaseOperator
|
||||
{
|
||||
// Argument
|
||||
struct Argument : public device::BaseArgument
|
||||
{
|
||||
Argument(Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
const Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
: in_n_c_hi_wi_{in_n_c_hi_wi},
|
||||
wei_k_c_y_x_{wei_k_c_y_x},
|
||||
out_n_k_ho_wo_{out_n_k_ho_wo},
|
||||
conv_strides_{conv_filter_strides},
|
||||
conv_dilations_{conv_filter_dilations},
|
||||
in_left_pads_{input_left_pads},
|
||||
in_right_pads_{input_right_pads},
|
||||
in_element_op_{in_element_op},
|
||||
wei_element_op_{wei_element_op},
|
||||
out_element_op_{out_element_op}
|
||||
{
|
||||
}
|
||||
|
||||
Tensor<InDataType>& in_n_c_hi_wi_;
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x_;
|
||||
const Tensor<OutDataType>& out_n_k_ho_wo_;
|
||||
|
||||
std::vector<index_t> conv_strides_;
|
||||
std::vector<index_t> conv_dilations_;
|
||||
std::vector<index_t> in_left_pads_;
|
||||
std::vector<index_t> in_right_pads_;
|
||||
|
||||
InElementwiseOperation in_element_op_;
|
||||
WeiElementwiseOperation wei_element_op_;
|
||||
OutElementwiseOperation out_element_op_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public device::BaseInvoker
|
||||
{
|
||||
using Argument = ReferenceConvBwdData::Argument;
|
||||
|
||||
float Run(const Argument& arg)
|
||||
{
|
||||
auto f_nchw = [&](auto n, auto c, auto hi, auto wi) {
|
||||
std::size_t K = arg.wei_k_c_y_x_.mDesc.GetLengths()[0];
|
||||
std::size_t Y = arg.wei_k_c_y_x_.mDesc.GetLengths()[2];
|
||||
std::size_t X = arg.wei_k_c_y_x_.mDesc.GetLengths()[3];
|
||||
|
||||
std::size_t Ho = arg.out_n_k_ho_wo_.mDesc.GetLengths()[2];
|
||||
std::size_t Wo = arg.out_n_k_ho_wo_.mDesc.GetLengths()[3];
|
||||
|
||||
float v_acc = 0;
|
||||
|
||||
for(int y = 0; y < Y; ++y)
|
||||
{
|
||||
int h_tmp = hi + arg.in_left_pads_[0] - y * arg.conv_dilations_[0];
|
||||
if(h_tmp % arg.conv_strides_[0] == 0)
|
||||
{
|
||||
int ho = h_tmp / arg.conv_strides_[0];
|
||||
if(ho >= 0 && ho < Ho)
|
||||
{
|
||||
for(int x = 0; x < X; ++x)
|
||||
{
|
||||
int w_tmp = wi + arg.in_left_pads_[1] - x * arg.conv_dilations_[1];
|
||||
if(w_tmp % arg.conv_strides_[1] == 0)
|
||||
{
|
||||
int wo = w_tmp / arg.conv_strides_[1];
|
||||
if(wo >= 0 && wo < Wo)
|
||||
{
|
||||
for(int k = 0; k < K; ++k)
|
||||
{
|
||||
float v_out = 0;
|
||||
float v_wei = 0;
|
||||
|
||||
arg.out_element_op_(
|
||||
v_out,
|
||||
ck::type_convert<float>(
|
||||
arg.out_n_k_ho_wo_(n, k, ho, wo)));
|
||||
arg.wei_element_op_(v_wei,
|
||||
ck::type_convert<float>(
|
||||
arg.wei_k_c_y_x_(k, c, y, x)));
|
||||
|
||||
v_acc += v_out * v_wei;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
float v_in;
|
||||
arg.in_element_op_(v_in, v_acc);
|
||||
arg.in_n_c_hi_wi_(n, c, hi, wi) = ck::type_convert<InDataType>(v_in);
|
||||
};
|
||||
|
||||
make_ParallelTensorFunctor(f_nchw,
|
||||
arg.in_n_c_hi_wi_.mDesc.GetLengths()[0],
|
||||
arg.in_n_c_hi_wi_.mDesc.GetLengths()[1],
|
||||
arg.in_n_c_hi_wi_.mDesc.GetLengths()[2],
|
||||
arg.in_n_c_hi_wi_.mDesc.GetLengths()[3])(
|
||||
std::thread::hardware_concurrency());
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
float Run(const device::BaseArgument* p_arg, int) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
};
|
||||
|
||||
static constexpr bool IsValidCompilationParameter()
|
||||
{
|
||||
// TODO: properly implement this check
|
||||
return true;
|
||||
}
|
||||
|
||||
bool IsSupportedArgument(const device::BaseArgument*) override { return true; }
|
||||
|
||||
static auto MakeArgument(Tensor<InDataType>& in_n_c_hi_wi,
|
||||
const Tensor<WeiDataType>& wei_k_c_y_x,
|
||||
const Tensor<OutDataType>& out_n_k_ho_wo,
|
||||
std::vector<ck::index_t> conv_filter_strides,
|
||||
std::vector<ck::index_t> conv_filter_dilations,
|
||||
std::vector<ck::index_t> input_left_pads,
|
||||
std::vector<ck::index_t> input_right_pads,
|
||||
InElementwiseOperation in_element_op,
|
||||
WeiElementwiseOperation wei_element_op,
|
||||
OutElementwiseOperation out_element_op)
|
||||
{
|
||||
return Argument{in_n_c_hi_wi,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
in_element_op,
|
||||
wei_element_op,
|
||||
out_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
virtual std::unique_ptr<device::BaseInvoker> MakeInvokerPointer()
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
// clang-format off
|
||||
str << "ReferenceConvBwdData"
|
||||
<< std::endl;
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace host
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
#endif
|
||||
319
test/conv2d_bwd_data/main.cpp
Normal file
319
test/conv2d_bwd_data/main.cpp
Normal file
@@ -0,0 +1,319 @@
|
||||
#include "config.hpp"
|
||||
#include "device.hpp"
|
||||
#include "host_tensor.hpp"
|
||||
#include "host_tensor_generator.hpp"
|
||||
#include "host_conv.hpp"
|
||||
#include "tensor_layout.hpp"
|
||||
#include "device_tensor.hpp"
|
||||
#include "device_conv_bwd_data.hpp"
|
||||
#include "element_wise_operation.hpp"
|
||||
#include "reference_conv_bwd_data.hpp"
|
||||
|
||||
using F16 = ck::half_t;
|
||||
using F32 = float;
|
||||
using BF16 = ushort;
|
||||
using INT8 = int8_t;
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
namespace device_conv2d_bwd_data_instance {
|
||||
|
||||
using DeviceConvBwdDataNoOpPtr =
|
||||
DeviceConvBwdDataPtr<ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough,
|
||||
ck::tensor_operation::element_wise::PassThrough>;
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
void add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(
|
||||
std::vector<DeviceConvBwdDataNoOpPtr>&);
|
||||
} // namespace device_conv2d_bwd_data_instance
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
|
||||
using InElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
|
||||
|
||||
template <typename T>
|
||||
static bool check_out(const Tensor<T>& ref, const Tensor<T>& result)
|
||||
{
|
||||
float max_diff = 1e-6;
|
||||
|
||||
for(int i = 0; i < ref.mData.size(); ++i)
|
||||
{
|
||||
float diff = std::abs(double(ref.mData[i]) - double(result.mData[i]));
|
||||
if(max_diff < diff)
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
int data_type = 0;
|
||||
int init_method = 0;
|
||||
|
||||
// Conv shape
|
||||
ck::index_t N = 128;
|
||||
ck::index_t K = 256;
|
||||
ck::index_t C = 192;
|
||||
ck::index_t Y = 3;
|
||||
ck::index_t X = 3;
|
||||
ck::index_t Hi = 71;
|
||||
ck::index_t Wi = 71;
|
||||
ck::index_t conv_stride_h = 2;
|
||||
ck::index_t conv_stride_w = 2;
|
||||
ck::index_t conv_dilation_h = 1;
|
||||
ck::index_t conv_dilation_w = 1;
|
||||
ck::index_t in_left_pad_h = 1;
|
||||
ck::index_t in_left_pad_w = 1;
|
||||
ck::index_t in_right_pad_h = 1;
|
||||
ck::index_t in_right_pad_w = 1;
|
||||
|
||||
if(argc == 3)
|
||||
{
|
||||
data_type = std::stoi(argv[1]);
|
||||
init_method = std::stoi(argv[2]);
|
||||
}
|
||||
else if(argc == 18)
|
||||
{
|
||||
data_type = std::stoi(argv[1]);
|
||||
init_method = std::stoi(argv[2]);
|
||||
|
||||
N = std::stoi(argv[3]);
|
||||
K = std::stoi(argv[4]);
|
||||
C = std::stoi(argv[5]);
|
||||
Y = std::stoi(argv[6]);
|
||||
X = std::stoi(argv[7]);
|
||||
Hi = std::stoi(argv[8]);
|
||||
Wi = std::stoi(argv[9]);
|
||||
conv_stride_h = std::stoi(argv[10]);
|
||||
conv_stride_w = std::stoi(argv[11]);
|
||||
conv_dilation_h = std::stoi(argv[12]);
|
||||
conv_dilation_w = std::stoi(argv[13]);
|
||||
in_left_pad_h = std::stoi(argv[14]);
|
||||
in_left_pad_w = std::stoi(argv[15]);
|
||||
in_right_pad_h = std::stoi(argv[16]);
|
||||
in_right_pad_w = std::stoi(argv[17]);
|
||||
}
|
||||
else
|
||||
{
|
||||
printf("arg1: data type (0=fp32 )\n");
|
||||
printf("arg2: verification (0=no, 1=yes)\n");
|
||||
printf("arg3: initialization (0=no init, 1=integer value, 2=decimal value)\n");
|
||||
printf("arg4: run kernel # of times (>1)\n");
|
||||
printf("arg5 to 19: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, "
|
||||
"RightPx\n");
|
||||
exit(1);
|
||||
}
|
||||
|
||||
auto Run = [&](auto input_type, auto wei_type, auto out_type) {
|
||||
using InDataType = decltype(input_type);
|
||||
using WeiDataType = decltype(wei_type);
|
||||
using OutDataType = decltype(out_type);
|
||||
|
||||
using ReferenceConvBwdInstance =
|
||||
ck::tensor_operation::host::ReferenceConvBwdData<InDataType,
|
||||
WeiDataType,
|
||||
OutDataType,
|
||||
InElementOp,
|
||||
WeiElementOp,
|
||||
OutElementOp>;
|
||||
|
||||
const ck::index_t YEff = (Y - 1) * conv_dilation_h + 1;
|
||||
const ck::index_t XEff = (X - 1) * conv_dilation_w + 1;
|
||||
|
||||
const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - YEff) / conv_stride_h + 1;
|
||||
const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
|
||||
|
||||
const std::vector<ck::index_t> input_spatial_lengths{{Hi, Wi}};
|
||||
const std::vector<ck::index_t> filter_spatial_lengths{{Y, X}};
|
||||
const std::vector<ck::index_t> output_spatial_lengths{{Ho, Wo}};
|
||||
const std::vector<ck::index_t> conv_filter_strides{{conv_stride_h, conv_stride_w}};
|
||||
const std::vector<ck::index_t> conv_filter_dilations{{conv_dilation_h, conv_dilation_w}};
|
||||
const std::vector<ck::index_t> input_left_pads{{in_left_pad_h, in_left_pad_w}};
|
||||
const std::vector<ck::index_t> input_right_pads{{in_right_pad_h, in_right_pad_w}};
|
||||
|
||||
auto f_host_tensor_descriptor =
|
||||
[](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W) {
|
||||
return HostTensorDescriptor(std::vector<std::size_t>({N_, C_, H, W}),
|
||||
std::vector<std::size_t>({C_ * H * W, 1, W * C_, C_}));
|
||||
};
|
||||
|
||||
Tensor<OutDataType> out_n_k_ho_wo(f_host_tensor_descriptor(N, K, Ho, Wo));
|
||||
Tensor<WeiDataType> wei_k_c_y_x(f_host_tensor_descriptor(K, C, Y, X));
|
||||
Tensor<InDataType> in_n_c_hi_wi_host_result(f_host_tensor_descriptor(N, C, Hi, Wi));
|
||||
Tensor<InDataType> in_n_c_hi_wi_device_result(f_host_tensor_descriptor(N, C, Hi, Wi));
|
||||
|
||||
std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi_host_result.mDesc << std::endl;
|
||||
std::cout << "wei_k_c_y_x: " << wei_k_c_y_x.mDesc << std::endl;
|
||||
std::cout << "out_n_k_ho_wo: " << out_n_k_ho_wo.mDesc << std::endl;
|
||||
|
||||
switch(init_method)
|
||||
{
|
||||
case 0: break;
|
||||
case 1:
|
||||
out_n_k_ho_wo.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
|
||||
wei_k_c_y_x.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-5, 5});
|
||||
break;
|
||||
default:
|
||||
out_n_k_ho_wo.GenerateTensorValue(GeneratorTensor_1<OutDataType>{1});
|
||||
wei_k_c_y_x.GenerateTensorValue(GeneratorTensor_1<WeiDataType>{1});
|
||||
}
|
||||
|
||||
DeviceMem in_device_buf(sizeof(InDataType) *
|
||||
in_n_c_hi_wi_device_result.mDesc.GetElementSpace());
|
||||
DeviceMem wei_device_buf(sizeof(WeiDataType) * wei_k_c_y_x.mDesc.GetElementSpace());
|
||||
DeviceMem out_device_buf(sizeof(OutDataType) * out_n_k_ho_wo.mDesc.GetElementSpace());
|
||||
|
||||
out_device_buf.ToDevice(out_n_k_ho_wo.mData.data());
|
||||
wei_device_buf.ToDevice(wei_k_c_y_x.mData.data());
|
||||
|
||||
in_n_c_hi_wi_device_result.GenerateTensorValue(GeneratorTensor_1<InDataType>{5});
|
||||
in_device_buf.ToDevice(in_n_c_hi_wi_device_result.mData.data());
|
||||
|
||||
// get host result
|
||||
{
|
||||
auto ref_conv = ReferenceConvBwdInstance{};
|
||||
auto ref_invoker = ref_conv.MakeInvoker();
|
||||
|
||||
auto ref_argument = ref_conv.MakeArgument(in_n_c_hi_wi_host_result,
|
||||
wei_k_c_y_x,
|
||||
out_n_k_ho_wo,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
ref_invoker.Run(ref_argument);
|
||||
}
|
||||
|
||||
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
|
||||
using DeviceConvBwdDataNoOpPtr = ck::tensor_operation::device::
|
||||
DeviceConvBwdDataPtr<PassThrough, PassThrough, PassThrough>;
|
||||
|
||||
// add device Conv instances
|
||||
std::vector<DeviceConvBwdDataNoOpPtr> conv_ptrs;
|
||||
|
||||
if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, float> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, float> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, float>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f32_instances(conv_ptrs);
|
||||
}
|
||||
else if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, ck::half_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, ck::half_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, ck::half_t>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_f16_instances(conv_ptrs);
|
||||
}
|
||||
else if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, ushort> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, ushort> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, ushort>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_bf16_instances(conv_ptrs);
|
||||
}
|
||||
else if constexpr(ck::is_same_v<ck::remove_cv_t<InDataType>, int8_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<WeiDataType>, int8_t> &&
|
||||
ck::is_same_v<ck::remove_cv_t<OutDataType>, int8_t>)
|
||||
{
|
||||
ck::tensor_operation::device::device_conv2d_bwd_data_instance::
|
||||
add_device_conv2d_bwd_data_xdl_nhwc_kyxc_nhwk_int8_instances(conv_ptrs);
|
||||
}
|
||||
|
||||
if(conv_ptrs.size() <= 0)
|
||||
{
|
||||
throw std::runtime_error("wrong! no device Conv instance found");
|
||||
}
|
||||
|
||||
// profile device Conv instances
|
||||
bool success = true;
|
||||
for(auto& conv_ptr : conv_ptrs)
|
||||
{
|
||||
auto argument_ptr = conv_ptr->MakeArgumentPointer(
|
||||
static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
|
||||
static_cast<WeiDataType*>(wei_device_buf.GetDeviceBuffer()),
|
||||
static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
|
||||
N,
|
||||
K,
|
||||
C,
|
||||
input_spatial_lengths,
|
||||
filter_spatial_lengths,
|
||||
output_spatial_lengths,
|
||||
conv_filter_strides,
|
||||
conv_filter_dilations,
|
||||
input_left_pads,
|
||||
input_right_pads,
|
||||
InElementOp{},
|
||||
WeiElementOp{},
|
||||
OutElementOp{});
|
||||
|
||||
if(conv_ptr->IsSupportedArgument(argument_ptr.get()))
|
||||
{
|
||||
auto invoker_ptr = conv_ptr->MakeInvokerPointer();
|
||||
invoker_ptr->Run(argument_ptr.get(), 1);
|
||||
|
||||
in_device_buf.FromDevice(in_n_c_hi_wi_device_result.mData.data());
|
||||
|
||||
if(!check_out(in_n_c_hi_wi_host_result, in_n_c_hi_wi_device_result))
|
||||
{
|
||||
std::cout << "Fail Info: " << conv_ptr->GetTypeString() << std::endl;
|
||||
success = false;
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "Pass Info: " << conv_ptr->GetTypeString() << std::endl;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "Not support Info: " << conv_ptr->GetTypeString() << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
if(success)
|
||||
{
|
||||
std::cout << "test conv2d bwd : Pass" << std::endl;
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "test conv2d bwd: Fail " << std::endl;
|
||||
}
|
||||
};
|
||||
|
||||
if(data_type == 0)
|
||||
{
|
||||
Run(float(), float(), F32());
|
||||
}
|
||||
else if(data_type == 1)
|
||||
{
|
||||
Run(F16(), F16(), F16());
|
||||
}
|
||||
else if(data_type == 2)
|
||||
{
|
||||
Run(BF16(), BF16(), BF16());
|
||||
}
|
||||
else if(data_type == 3)
|
||||
{
|
||||
Run(INT8(), INT8(), INT8());
|
||||
}
|
||||
else
|
||||
{
|
||||
return 1;
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
Reference in New Issue
Block a user