mirror of
https://github.com/ROCm/composable_kernel.git
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abf4bdb9a9
* Convolution ND * Code unification across dimensions for generating tensor descriptors. * Example * Instances * Move convnd f32 instance file to comply with repo structure. * Conv 1D tensor layouts. * Formatting and use ReferenceConv * Reference ConvFwd supporting 1D and 2D convolution. * Debug printing TensorLayout name. * Conv fwd 1D instance f32 * Refactor conv ND example. Needed to support various conv dimensio. Needed to support various conv dimensions * Rename conv nd example director to prevent conflicts. * Refactor some common utility to single file. Plus some tests. * Refactor GetHostTensorDescriptor + UT. * Add 1D test case. * Test reference convolution 1d/2d * Remove some leftovers. * Fix convolution example error for 1D * Refactor test check errors utility function. * Test Conv2D Fwd XDL * More UT for 1D case. * Parameterize input & weight initializers. * Rename example to prevent conflicts. * Split convnd instance into separate files for 1d/2d * Address review comments. * Fix data type for flops/gbytes calculations. * Assign example number 11. * 3D cases for convolution utility functions. * 3D reference convolution. * Add support for 3D convolution. * Check for inputs bigger than 2GB. * Formatting * Support for bf16/f16/f32/i8 - conv instances + UT. * Use check_err from test_util.hpp. * Split convnd test into separate files for each dim. * Fix data generation and use proper instances. * Formatting * Skip tensor initialization if not necessary. * Fix CMakefiles. * Remove redundant conv2d_fwd test. * Lower problem size for conv3D UT. * 3D case for convnd example. * Remove leftovers after merge. * Add Conv Specialization string to GetTypeString * Skip instance causing numerical errors. * Small fixes. * Remove redundant includes. * Fix namespace name error. * Script for automatic testing and logging convolution fwd UTs * Comment out numactl cmd. * Refine weights initalization and relax rtol for fp16 * Move test_util.hpp to check_err.hpp * Refine weights initalization and relax rtol for fp16 * Refactor common part of test conv utils. * Move utility function to single common place. * Add additional common functions to utility. * Refactor convnd_fwd_xdl examples. * Remove redundant files. * Unify structure. * Add constructor to ConvParams. * And add input parameters validation. * Modify conv examples to use single utility file. * Remove check_error from host_tensor.hpp * Get rid of check_indices function. * Remove bf16_to_f32 function overload for scalars. * Fix namespace. * Add half_float::half for check_err. * Fix conv params size in UT. * Fix weights initialization for int8. * Fix weights initialization for int8. * Add type_convert when store output in ref conv 1D. * Get back old conv2d_fwd_xdl operation. * Silence conv debug print. * format * clean * clean * Fix merge. * Fix namespace for check_err * Formatting. * Fix merge artifacts. * Remove deleted header. * Fix some includes and use ck::utils::check_err. * Remove unused check_indices restored by previous merge. * Fix namespaces after merge. * Fix compilation error. * Small fixes. * Use common functions. * Fix filename * Fix namespaces. * Fix merge artifact - retrieve removed by accident fun. * Fix ConvForwardSpecialization. * Adhere to coding style rules. * Fix merge artifacts. Co-authored-by: Adam Osewski <aosewski@amd.com> Co-authored-by: Chao Liu <chao.liu2@amd.com>
331 lines
14 KiB
C++
331 lines
14 KiB
C++
#include <iostream>
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#include <numeric>
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#include <initializer_list>
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#include <cstdlib>
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#include <stdlib.h>
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#include <half.hpp>
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#include <vector>
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#include "profile_convnd_bwd_data_impl.hpp"
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int main()
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{
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bool pass = true;
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// check 1d
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std::vector<ck::utils::conv::ConvParams> params;
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params.push_back({1, 128, 128, 256, {1}, {14}, {2}, {1}, {0}, {0}});
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params.push_back({1, 128, 128, 256, {3}, {28}, {1}, {1}, {1}, {1}});
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params.push_back({1, 128, 128, 256, {1}, {3}, {1}, {1}, {0}, {0}});
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for(auto& param : params)
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{
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pass &= ck::profiler::profile_convnd_bwd_data_impl<1,
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float,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<1,
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ck::half_t,
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ck::half_t,
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ck::half_t,
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float,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<1,
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ck::bhalf_t,
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ck::bhalf_t,
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ck::bhalf_t,
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float,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<1,
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int8_t,
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int8_t,
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int8_t,
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int,
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ck::tensor_layout::convolution::NWC,
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ck::tensor_layout::convolution::KXC,
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ck::tensor_layout::convolution::NWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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}
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// check 2d
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params.clear();
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params.push_back({2, 128, 128, 256, {1, 1}, {7, 7}, {2, 2}, {1, 1}, {0, 0}, {0, 0}});
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params.push_back({2, 128, 128, 256, {3, 3}, {14, 14}, {1, 1}, {1, 1}, {1, 1}, {1, 1}});
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params.push_back({2, 128, 128, 256, {1, 1}, {3, 3}, {1, 1}, {1, 1}, {0, 0}, {0, 0}});
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for(auto& param : params)
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{
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pass &= ck::profiler::profile_convnd_bwd_data_impl<2,
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float,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NHWC,
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ck::tensor_layout::convolution::KYXC,
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ck::tensor_layout::convolution::NHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<2,
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ck::half_t,
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ck::half_t,
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ck::half_t,
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float,
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ck::tensor_layout::convolution::NHWC,
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ck::tensor_layout::convolution::KYXC,
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ck::tensor_layout::convolution::NHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<2,
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ck::bhalf_t,
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ck::bhalf_t,
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ck::bhalf_t,
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float,
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ck::tensor_layout::convolution::NHWC,
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ck::tensor_layout::convolution::KYXC,
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ck::tensor_layout::convolution::NHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<2,
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int8_t,
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int8_t,
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int8_t,
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int,
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ck::tensor_layout::convolution::NHWC,
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ck::tensor_layout::convolution::KYXC,
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ck::tensor_layout::convolution::NHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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}
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// check 3d
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params.clear();
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params.push_back(
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{3, 128, 128, 256, {1, 1, 1}, {7, 7, 7}, {2, 2, 2}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
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params.push_back(
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{3, 128, 128, 256, {3, 3, 3}, {14, 14, 14}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}});
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params.push_back(
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{3, 128, 128, 256, {1, 1, 1}, {3, 3, 3}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}});
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for(auto& param : params)
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{
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pass &= ck::profiler::profile_convnd_bwd_data_impl<3,
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float,
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float,
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float,
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float,
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ck::tensor_layout::convolution::NDHWC,
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ck::tensor_layout::convolution::KZYXC,
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ck::tensor_layout::convolution::NDHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<3,
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ck::half_t,
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ck::half_t,
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ck::half_t,
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float,
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ck::tensor_layout::convolution::NDHWC,
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ck::tensor_layout::convolution::KZYXC,
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ck::tensor_layout::convolution::NDHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<3,
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ck::bhalf_t,
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ck::bhalf_t,
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ck::bhalf_t,
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float,
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ck::tensor_layout::convolution::NDHWC,
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ck::tensor_layout::convolution::KZYXC,
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ck::tensor_layout::convolution::NDHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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pass &= ck::profiler::profile_convnd_bwd_data_impl<3,
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int8_t,
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int8_t,
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int8_t,
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int,
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ck::tensor_layout::convolution::NDHWC,
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ck::tensor_layout::convolution::KZYXC,
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ck::tensor_layout::convolution::NDHWK>(
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1, // do_verification,
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1, // init_method,
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0, // do_log,
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1, // nrepeat,
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param.N,
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param.K,
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param.C,
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param.input_spatial_lengths,
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param.filter_spatial_lengths,
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param.GetOutputSpatialLengths(),
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param.conv_filter_strides,
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param.conv_filter_dilations,
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param.input_left_pads,
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param.input_right_pads);
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}
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if(pass)
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{
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std::cout << "test convnd bwd : Pass" << std::endl;
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return 0;
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}
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else
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{
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std::cout << "test convnd bwd: Fail " << std::endl;
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return -1;
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}
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}
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