mirror of
https://github.com/ROCm/composable_kernel.git
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[CK_TILE] Grouped Convolution Backward Weight Kernel (#2357)
* [CK TILE] Grouped Convolution Forward Kernel * custom vector size * fixes * refactor * resolved conflicts * rebase fixes * fixes * tmp * add working support for splitk * minor fix * fixes * fixes * minor fix * small fix * Split K and preprocessing fixes --------- Co-authored-by: Bartlomiej Kocot <barkocot@amd.com>
This commit is contained in:
jakpiase
@@ -14,14 +14,15 @@ namespace ck_tile {
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/// This structure is passed to Grouped Convolution Kernels when creating kernel
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/// arguments object. It contain all necessary information required to
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/// build proper kernel argument and launch kernel on GPU.
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template <typename InPtr, typename WeiPtr, typename OutPtr>
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struct GroupedConvHostArgs : public conv::ConvParam
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{
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CK_TILE_HOST GroupedConvHostArgs() = delete;
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CK_TILE_HOST GroupedConvHostArgs(ConvParam conv_param,
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const void* in_ptr_,
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const void* wei_ptr_,
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InPtr in_ptr_,
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WeiPtr wei_ptr_,
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const std::vector<const void*> ds_ptr_,
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void* out_ptr_,
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OutPtr out_ptr_,
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index_t k_batch_)
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: conv::ConvParam(conv_param),
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in_ptr(in_ptr_),
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@@ -32,13 +33,16 @@ struct GroupedConvHostArgs : public conv::ConvParam
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{
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}
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const void* in_ptr;
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const void* wei_ptr;
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InPtr in_ptr;
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WeiPtr wei_ptr;
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const std::vector<const void*> ds_ptr;
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void* out_ptr;
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OutPtr out_ptr;
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index_t k_batch;
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};
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using GroupedConvFwdHostArgs = GroupedConvHostArgs<const void*, const void*, void*>;
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using GroupedConvBwdWeightHostArgs = GroupedConvHostArgs<const void*, void*, const void*>;
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template <index_t NDimSpatial_,
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ConvolutionSpecialization ConvSpecialization_,
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typename InLayout_,
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@@ -55,6 +59,7 @@ struct GroupedConvTraits
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}
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public:
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static constexpr index_t NumGroupsToMerge = 1;
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static constexpr index_t NDimSpatial = NDimSpatial_;
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static constexpr ConvolutionSpecialization ConvSpecialization = ConvSpecialization_;
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using InLayout = InLayout_;
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@@ -0,0 +1,659 @@
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/ops/grouped_convolution/utils/convolution_specialization.hpp"
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namespace ck_tile {
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template <index_t NDimSpatial,
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ConvolutionSpecialization ConvolutionSpecialization,
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bool SplitN = false,
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typename ADataType = float,
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typename CDataType = float,
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index_t NumGroupsToMerge = 1,
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typename IndexType = index_t>
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struct TransformConvBwdWeightToGemm
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{
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private:
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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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#if 0 // TODO: Enable these functionalities
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template <typename ConvDimsType>
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static long_index_t calculate_element_space_size_impl(const ConvDimsType& lengths,
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const ConvDimsType& strides,
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index_t i)
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{
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long_index_t acc = 1;
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for(; i < (NDimSpatial + 3); i++)
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{
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acc +=
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static_cast<long_index_t>(lengths[i] - I1) * static_cast<long_index_t>(strides[i]);
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}
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return acc;
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}
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template <typename ConvDimsType>
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static IndexType GetSplitedNSize(const ConvDimsType& a_g_n_c_wis_lengths,
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const ConvDimsType& a_g_n_c_wis_strides,
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const ConvDimsType& c_g_n_k_wos_lengths,
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const ConvDimsType& c_g_n_k_wos_strides)
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{
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const long_index_t a_element_space_size =
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calculate_element_space_size_impl(a_g_n_c_wis_lengths, a_g_n_c_wis_strides, I1);
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const long_index_t c_element_space_size =
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calculate_element_space_size_impl(c_g_n_k_wos_lengths, c_g_n_k_wos_strides, I1);
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const long_index_t element_space_size = math::max(a_element_space_size * sizeof(ADataType),
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c_element_space_size * sizeof(CDataType));
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constexpr long_index_t TwoGB = (long_index_t{1} << 31);
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const IndexType N = a_g_n_c_wis_lengths[I1];
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if(element_space_size > TwoGB)
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{
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// Minimum divisor of N to not exceed 2GB
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const auto divisor = math::integer_divide_ceil(element_space_size, TwoGB);
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if(divisor <= static_cast<double>(N))
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{
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// Find least divisor of N larger than element_space_size / TwoGB
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// Iterate up to sqrt(N). There are no divisors above this value.
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for(IndexType least_divisor = divisor; least_divisor * least_divisor <= N;
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least_divisor++)
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{
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if(N % least_divisor == 0)
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{
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return N / least_divisor;
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}
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}
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// Not found, process one Convolution N per block
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return 1;
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}
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else
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{
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// Split Convolution's N dimension into N workgroups. However
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// this still might not result in sufficiently small tensor,
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// but at least later on we could divide the image as well.
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return 1;
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}
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}
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else
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{
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// Split N is not needed.
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return N;
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}
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}
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#endif
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public:
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CK_TILE_HOST constexpr TransformConvBwdWeightToGemm() {}
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template <typename TransformConvBwdWeightToGemmBase>
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CK_TILE_HOST TransformConvBwdWeightToGemm(
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const TransformConvBwdWeightToGemmBase& transform_conv_fwd_to_gemm_base)
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: G_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.G_)},
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N_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.N_)},
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Di_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Di_)},
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Hi_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Hi_)},
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Wi_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Wi_)},
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Do_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Do_)},
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Ho_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Ho_)},
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Wo_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Wo_)},
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Z_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Z_)},
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Y_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.Y_)},
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X_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.X_)},
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K_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.K_)},
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C_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.C_)},
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ConvStrideD_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ConvStrideD_)},
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ConvStrideH_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ConvStrideH_)},
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ConvStrideW_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ConvStrideW_)},
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ConvDilationD_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ConvDilationD_)},
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ConvDilationH_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ConvDilationH_)},
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ConvDilationW_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ConvDilationW_)},
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InLeftPadD_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.InLeftPadD_)},
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InLeftPadH_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.InLeftPadH_)},
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InLeftPadW_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.InLeftPadW_)},
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InRightPadD_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.InRightPadD_)},
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InRightPadH_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.InRightPadH_)},
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InRightPadW_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.InRightPadW_)},
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ZYX_{static_cast<IndexType>(transform_conv_fwd_to_gemm_base.ZYX_)}
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{
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}
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template <typename ConvDimsType,
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typename ConvSpatialDimsType,
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index_t NDim = NDimSpatial,
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typename std::enable_if<NDim == 1, bool>::type = false>
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CK_TILE_HOST TransformConvBwdWeightToGemm(const ConvDimsType& a_g_n_c_wis_lengths,
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const ConvDimsType& b_g_k_c_xs_lengths,
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const ConvDimsType& c_g_n_k_wos_lengths,
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const ConvSpatialDimsType& conv_filter_strides,
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const ConvSpatialDimsType& conv_filter_dilations,
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const ConvSpatialDimsType& input_left_pads,
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const ConvSpatialDimsType& input_right_pads)
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: G_{a_g_n_c_wis_lengths[I0]},
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Di_{I1},
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Hi_{I1},
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Wi_{a_g_n_c_wis_lengths[I3]},
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Do_{I1},
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Ho_{I1},
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Wo_{c_g_n_k_wos_lengths[I3]},
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Z_{I1},
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Y_{I1},
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X_{b_g_k_c_xs_lengths[I3]},
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K_{c_g_n_k_wos_lengths[I2]},
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C_{b_g_k_c_xs_lengths[I2]},
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ConvStrideD_{I1},
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ConvStrideH_{I1},
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ConvStrideW_{conv_filter_strides[I0]},
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ConvDilationD_{I1},
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ConvDilationH_{I1},
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ConvDilationW_{conv_filter_dilations[I0]},
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InLeftPadD_{I0},
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InLeftPadH_{I0},
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InLeftPadW_{input_left_pads[I0]},
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InRightPadD_{I0},
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InRightPadH_{I0},
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InRightPadW_{input_right_pads[I0]},
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ZYX_{X_}
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{
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static_assert(std::is_same_v<ConvSpatialDimsType, std::array<IndexType, NDimSpatial>> ||
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std::is_same_v<ConvSpatialDimsType, ck_tile::array<IndexType, NDimSpatial>>);
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static_assert(std::is_same_v<ConvDimsType, std::array<IndexType, NDimSpatial + I3>> ||
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std::is_same_v<ConvDimsType, ck_tile::array<IndexType, NDimSpatial + I3>>);
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#if 0 // TODO: Enable these functionalities
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if constexpr(SplitN)
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{
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N_ = GetSplitedNSize(
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a_g_n_c_wis_lengths, a_g_n_c_wis_strides, c_g_n_k_wos_lengths, c_g_n_k_wos_strides);
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}
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else
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{
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N_ = c_g_n_k_wos_lengths[I1];
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}
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#endif
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N_ = c_g_n_k_wos_lengths[I1];
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}
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template <typename ConvDimsType,
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typename ConvSpatialDimsType,
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index_t NDim = NDimSpatial,
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typename std::enable_if<NDim == 2, bool>::type = false>
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CK_TILE_HOST TransformConvBwdWeightToGemm(const ConvDimsType& a_g_n_c_wis_lengths,
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const ConvDimsType& b_g_k_c_xs_lengths,
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const ConvDimsType& c_g_n_k_wos_lengths,
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const ConvSpatialDimsType& conv_filter_strides,
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const ConvSpatialDimsType& conv_filter_dilations,
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const ConvSpatialDimsType& input_left_pads,
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const ConvSpatialDimsType& input_right_pads)
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: G_{a_g_n_c_wis_lengths[I0]},
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Di_{I1},
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Hi_{a_g_n_c_wis_lengths[I3]},
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Wi_{a_g_n_c_wis_lengths[I4]},
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Do_{I1},
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Ho_{c_g_n_k_wos_lengths[I3]},
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Wo_{c_g_n_k_wos_lengths[I4]},
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Z_{I1},
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Y_{b_g_k_c_xs_lengths[I3]},
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X_{b_g_k_c_xs_lengths[I4]},
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K_{c_g_n_k_wos_lengths[I2]},
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C_{b_g_k_c_xs_lengths[I2]},
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ConvStrideD_{I1},
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ConvStrideH_{conv_filter_strides[I0]},
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ConvStrideW_{conv_filter_strides[I1]},
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ConvDilationD_{I1},
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ConvDilationH_{conv_filter_dilations[I0]},
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ConvDilationW_{conv_filter_dilations[I1]},
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InLeftPadD_{I0},
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InLeftPadH_{input_left_pads[I0]},
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InLeftPadW_{input_left_pads[I1]},
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InRightPadD_{I0},
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InRightPadH_{input_right_pads[I0]},
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InRightPadW_{input_right_pads[I1]},
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ZYX_{Y_ * X_}
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{
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static_assert(std::is_same_v<ConvSpatialDimsType, std::array<IndexType, NDimSpatial>> ||
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std::is_same_v<ConvSpatialDimsType, ck_tile::array<IndexType, NDimSpatial>>);
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static_assert(std::is_same_v<ConvDimsType, std::array<IndexType, NDimSpatial + I3>> ||
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std::is_same_v<ConvDimsType, ck_tile::array<IndexType, NDimSpatial + I3>>);
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#if 0 // TODO: Enable these functionalities
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if constexpr(SplitN)
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{
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N_ = GetSplitedNSize(
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a_g_n_c_wis_lengths, a_g_n_c_wis_strides, c_g_n_k_wos_lengths, c_g_n_k_wos_strides);
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}
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else
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{
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N_ = c_g_n_k_wos_lengths[I1];
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}
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#endif
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N_ = c_g_n_k_wos_lengths[I1];
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}
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template <typename ConvDimsType,
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typename ConvSpatialDimsType,
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index_t NDim = NDimSpatial,
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typename std::enable_if<NDim == 3, bool>::type = false>
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CK_TILE_HOST TransformConvBwdWeightToGemm(const ConvDimsType& a_g_n_c_wis_lengths,
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const ConvDimsType& b_g_k_c_xs_lengths,
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const ConvDimsType& c_g_n_k_wos_lengths,
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const ConvSpatialDimsType& conv_filter_strides,
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const ConvSpatialDimsType& conv_filter_dilations,
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const ConvSpatialDimsType& input_left_pads,
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const ConvSpatialDimsType& input_right_pads)
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: G_{a_g_n_c_wis_lengths[I0]},
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Di_{a_g_n_c_wis_lengths[I3]},
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Hi_{a_g_n_c_wis_lengths[I4]},
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Wi_{a_g_n_c_wis_lengths[I5]},
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Do_{c_g_n_k_wos_lengths[I3]},
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Ho_{c_g_n_k_wos_lengths[I4]},
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Wo_{c_g_n_k_wos_lengths[I5]},
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Z_{b_g_k_c_xs_lengths[I3]},
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Y_{b_g_k_c_xs_lengths[I4]},
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X_{b_g_k_c_xs_lengths[I5]},
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K_{c_g_n_k_wos_lengths[I2]},
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C_{b_g_k_c_xs_lengths[I2]},
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ConvStrideD_{conv_filter_strides[I0]},
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ConvStrideH_{conv_filter_strides[I1]},
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ConvStrideW_{conv_filter_strides[I2]},
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ConvDilationD_{conv_filter_dilations[I0]},
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ConvDilationH_{conv_filter_dilations[I1]},
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ConvDilationW_{conv_filter_dilations[I2]},
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InLeftPadD_{input_left_pads[I0]},
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InLeftPadH_{input_left_pads[I1]},
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InLeftPadW_{input_left_pads[I2]},
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InRightPadD_{input_right_pads[I0]},
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InRightPadH_{input_right_pads[I1]},
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InRightPadW_{input_right_pads[I2]},
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ZYX_{Z_ * Y_ * X_}
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{
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static_assert(std::is_same_v<ConvSpatialDimsType, std::array<IndexType, NDimSpatial>> ||
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std::is_same_v<ConvSpatialDimsType, ck_tile::array<IndexType, NDimSpatial>>);
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static_assert(std::is_same_v<ConvDimsType, std::array<IndexType, NDimSpatial + I3>> ||
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std::is_same_v<ConvDimsType, ck_tile::array<IndexType, NDimSpatial + I3>>);
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#if 0 // TODO: Enable these functionalities
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if constexpr(SplitN)
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{
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N_ = GetSplitedNSize(
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a_g_n_c_wis_lengths, a_g_n_c_wis_strides, c_g_n_k_wos_lengths, c_g_n_k_wos_strides);
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}
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else
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{
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N_ = c_g_n_k_wos_lengths[I1];
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}
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#endif
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N_ = c_g_n_k_wos_lengths[I1];
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}
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#if 0 // TODO: Enable these functionalities
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__host__ bool AreDescriptorsSmallerThan2GB() const
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{
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constexpr long_index_t TwoGB = (long_index_t{1} << 31);
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const long_index_t in_desc_space_size =
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I1 + (N_ - I1) * NStrideTensorA_ + (Di_ - I1) * DiStride_ + (Hi_ - I1) * HiStride_ +
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(Wi_ - I1) * WiStride_ + (C_ - I1) * CStrideTensorA_;
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const long_index_t out_desc_space_size =
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I1 + (N_ - I1) * NStrideTensorC_ + (Do_ - I1) * DoStride_ + (Ho_ - I1) * HoStride_ +
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(Wo_ - I1) * WoStride_ + (K_ - I1) * KStrideTensorC_;
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bool is_a_descriptor_smaller_than_2GB = (in_desc_space_size * sizeof(ADataType)) <= TwoGB;
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bool is_c_descriptor_smaller_than_2GB = (out_desc_space_size * sizeof(CDataType)) <= TwoGB;
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|
||||
return is_a_descriptor_smaller_than_2GB && is_c_descriptor_smaller_than_2GB;
|
||||
}
|
||||
|
||||
__host__ auto SplitConvProblem(const ADataType* a_grid_ptr_base,
|
||||
CDataType* c_grid_ptr_base) const
|
||||
{
|
||||
// Create copies
|
||||
auto conv_to_gemm_transformer_left = *this;
|
||||
auto conv_to_gemm_transformer_right = *this;
|
||||
IndexType a_right_offset = 0;
|
||||
IndexType c_right_offset = 0;
|
||||
// Calculate real filter size
|
||||
const IndexType z_eff = (Z_ - 1) * ConvDilationD_ + 1;
|
||||
const IndexType y_eff = (Y_ - 1) * ConvDilationH_ + 1;
|
||||
const IndexType x_eff = (X_ - 1) * ConvDilationW_ + 1;
|
||||
// Calculate start position in input for right tensor
|
||||
const IndexType di_right_transformer_start_idx = (Do_ / 2) * ConvStrideD_;
|
||||
const IndexType hi_right_transformer_start_idx = (Ho_ / 2) * ConvStrideH_;
|
||||
const IndexType wi_right_transformer_start_idx = (Wo_ / 2) * ConvStrideW_;
|
||||
// Calculate last position in input for left tensor
|
||||
const IndexType di_left_transformer_end_idx = (Do_ / 2 - 1) * ConvStrideD_ + z_eff;
|
||||
const IndexType hi_left_transformer_end_idx = (Ho_ / 2 - 1) * ConvStrideH_ + y_eff;
|
||||
const IndexType wi_left_transformer_end_idx = (Wo_ / 2 - 1) * ConvStrideW_ + x_eff;
|
||||
// Allow to split if whole left padding will be in left tensor and right padding in right
|
||||
// tensor
|
||||
const bool is_possible_to_split_d = Do_ != 1 &&
|
||||
di_right_transformer_start_idx > InLeftPadD_ &&
|
||||
di_left_transformer_end_idx <= (InLeftPadD_ + Di_);
|
||||
const bool is_possible_to_split_h = Ho_ != 1 &&
|
||||
hi_right_transformer_start_idx > InLeftPadH_ &&
|
||||
hi_left_transformer_end_idx <= (InLeftPadH_ + Hi_);
|
||||
const bool is_possible_to_split_w = Wo_ != 1 &&
|
||||
wi_right_transformer_start_idx > InLeftPadW_ &&
|
||||
wi_left_transformer_end_idx <= (InLeftPadW_ + Wi_);
|
||||
|
||||
if(is_possible_to_split_d)
|
||||
{
|
||||
// Apply new sizes
|
||||
// Split output on half
|
||||
conv_to_gemm_transformer_left.Do_ = Do_ / 2;
|
||||
conv_to_gemm_transformer_right.Do_ = Do_ - Do_ / 2;
|
||||
// Assign left padding to left convolution
|
||||
conv_to_gemm_transformer_left.InLeftPadD_ = InLeftPadD_;
|
||||
conv_to_gemm_transformer_right.InLeftPadD_ = 0;
|
||||
// Assign right padding to right convolution
|
||||
conv_to_gemm_transformer_left.InRightPadD_ = 0;
|
||||
conv_to_gemm_transformer_right.InRightPadD_ = InRightPadD_;
|
||||
// Calculate new input size
|
||||
conv_to_gemm_transformer_left.Di_ = di_left_transformer_end_idx - InLeftPadD_;
|
||||
conv_to_gemm_transformer_right.Di_ =
|
||||
math::min(Di_ - (di_right_transformer_start_idx - InLeftPadD_),
|
||||
(conv_to_gemm_transformer_right.Do_ - 1) * ConvStrideD_ + z_eff);
|
||||
;
|
||||
// Calcualte offsets
|
||||
a_right_offset = ((Do_ / 2) * ConvStrideD_ - InLeftPadD_) * DiStride_;
|
||||
c_right_offset = (Do_ / 2) * DoStride_;
|
||||
}
|
||||
else if(is_possible_to_split_h)
|
||||
{
|
||||
conv_to_gemm_transformer_left.Ho_ = Ho_ / 2;
|
||||
conv_to_gemm_transformer_right.Ho_ = Ho_ - Ho_ / 2;
|
||||
|
||||
conv_to_gemm_transformer_left.InLeftPadH_ = InLeftPadH_;
|
||||
conv_to_gemm_transformer_right.InLeftPadH_ = 0;
|
||||
|
||||
conv_to_gemm_transformer_left.InRightPadH_ = 0;
|
||||
conv_to_gemm_transformer_right.InRightPadH_ = InRightPadH_;
|
||||
|
||||
conv_to_gemm_transformer_left.Hi_ = hi_left_transformer_end_idx - InLeftPadH_;
|
||||
conv_to_gemm_transformer_right.Hi_ =
|
||||
math::min(Hi_ - (hi_right_transformer_start_idx - InLeftPadH_),
|
||||
(conv_to_gemm_transformer_right.Ho_ - 1) * ConvStrideH_ + y_eff);
|
||||
a_right_offset = ((Ho_ / 2) * ConvStrideH_ - InLeftPadH_) * HiStride_;
|
||||
c_right_offset = (Ho_ / 2) * HoStride_;
|
||||
}
|
||||
else if(is_possible_to_split_w)
|
||||
{
|
||||
conv_to_gemm_transformer_left.Wo_ = Wo_ / 2;
|
||||
conv_to_gemm_transformer_right.Wo_ = Wo_ - Wo_ / 2;
|
||||
|
||||
conv_to_gemm_transformer_left.InLeftPadW_ = InLeftPadW_;
|
||||
conv_to_gemm_transformer_right.InLeftPadW_ = 0;
|
||||
|
||||
conv_to_gemm_transformer_left.InRightPadW_ = 0;
|
||||
conv_to_gemm_transformer_right.InRightPadW_ = InRightPadW_;
|
||||
|
||||
conv_to_gemm_transformer_left.Wi_ = wi_left_transformer_end_idx - InLeftPadW_;
|
||||
conv_to_gemm_transformer_right.Wi_ =
|
||||
math::min(Wi_ - (wi_right_transformer_start_idx - InLeftPadW_),
|
||||
(conv_to_gemm_transformer_right.Wo_ - 1) * ConvStrideW_ + x_eff);
|
||||
|
||||
a_right_offset = ((Wo_ / 2) * ConvStrideW_ - InLeftPadW_) * WiStride_;
|
||||
c_right_offset = (Wo_ / 2) * WoStride_;
|
||||
}
|
||||
// Return left transform, right transformer, right offset to Input and right offset to
|
||||
// Output
|
||||
return ck_tile::make_tuple(conv_to_gemm_transformer_left,
|
||||
conv_to_gemm_transformer_right,
|
||||
a_grid_ptr_base + a_right_offset,
|
||||
c_grid_ptr_base + c_right_offset);
|
||||
}
|
||||
#endif
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 1, bool>::type = false>
|
||||
CK_TILE_HOST auto make_out_grid_desc() const
|
||||
{
|
||||
// NWGK
|
||||
const index_t NDoHoWoStride = G_ * K_;
|
||||
constexpr auto KStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
|
||||
return make_naive_tensor_descriptor(make_tuple(K_, N_ * Wo_),
|
||||
make_tuple(KStride, NDoHoWoStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 1, bool>::type = false>
|
||||
CK_TILE_HOST auto make_in_grid_desc() const
|
||||
{
|
||||
// NWGC
|
||||
const index_t NStride = Wi_ * G_ * C_;
|
||||
const index_t WiStride = G_ * C_;
|
||||
constexpr auto CStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
return make_naive_tensor_descriptor(make_tuple(N_, Wi_, C_),
|
||||
make_tuple(NStride, WiStride, CStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 1, bool>::type = false>
|
||||
CK_TILE_HOST auto make_wei_grid_desc() const
|
||||
{
|
||||
// GKXC
|
||||
const index_t KStride = X_ * C_;
|
||||
constexpr auto CXStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
return make_naive_tensor_descriptor(make_tuple(K_, X_ * C_), make_tuple(KStride, CXStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 2, bool>::type = false>
|
||||
CK_TILE_HOST auto make_out_grid_desc() const
|
||||
{
|
||||
// NHWGK
|
||||
const index_t NDoHoWoStride = G_ * K_;
|
||||
constexpr auto KStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
|
||||
return make_naive_tensor_descriptor(make_tuple(K_, N_ * Ho_ * Wo_),
|
||||
make_tuple(KStride, NDoHoWoStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 2, bool>::type = false>
|
||||
CK_TILE_HOST auto make_in_grid_desc() const
|
||||
{
|
||||
// NHWGC
|
||||
const index_t NStride = Hi_ * Wi_ * G_ * C_;
|
||||
const index_t HiStride = Wi_ * G_ * C_;
|
||||
const index_t WiStride = G_ * C_;
|
||||
constexpr auto CStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
return make_naive_tensor_descriptor(make_tuple(N_, Hi_, Wi_, C_),
|
||||
make_tuple(NStride, HiStride, WiStride, CStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 2, bool>::type = false>
|
||||
CK_TILE_HOST auto make_wei_grid_desc() const
|
||||
{
|
||||
// GKYXC
|
||||
const index_t KStride = Y_ * X_ * C_;
|
||||
constexpr auto CStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
return make_naive_tensor_descriptor(make_tuple(K_, Y_ * X_ * C_),
|
||||
make_tuple(KStride, CStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 3, bool>::type = false>
|
||||
CK_TILE_HOST auto make_out_grid_desc() const
|
||||
{
|
||||
// NDHWGK
|
||||
const index_t NDoHoWoStride = G_ * K_;
|
||||
constexpr auto KStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
|
||||
return make_naive_tensor_descriptor(make_tuple(K_, N_ * Do_ * Ho_ * Wo_),
|
||||
make_tuple(KStride, NDoHoWoStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 3, bool>::type = false>
|
||||
CK_TILE_HOST auto make_in_grid_desc() const
|
||||
{
|
||||
const index_t NStride = Di_ * Hi_ * Wi_ * G_ * C_;
|
||||
const index_t DiStride = Hi_ * Wi_ * G_ * C_;
|
||||
const index_t HiStride = Wi_ * G_ * C_;
|
||||
const index_t WiStride = G_ * C_;
|
||||
constexpr auto CStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
return make_naive_tensor_descriptor(
|
||||
make_tuple(N_, Di_, Hi_, Wi_, C_),
|
||||
make_tuple(NStride, DiStride, HiStride, WiStride, CStride));
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 3, bool>::type = false>
|
||||
CK_TILE_HOST auto make_wei_grid_desc() const
|
||||
{
|
||||
// KZYXC
|
||||
const index_t KStride = Z_ * Y_ * X_ * C_;
|
||||
constexpr auto CStride = I1;
|
||||
|
||||
// TODO Add support for NumGroupsToMerge > 1
|
||||
return make_naive_tensor_descriptor(make_tuple(K_, Z_ * Y_ * X_ * C_),
|
||||
make_tuple(KStride, CStride));
|
||||
}
|
||||
|
||||
// TODO: implement ck_tile::tensor_layout::convolution that describe packed/strided dimemsion as
|
||||
// properties
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 1, bool>::type = false>
|
||||
CK_TILE_HOST auto MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N() const
|
||||
{
|
||||
const auto out_grid_desc = make_out_grid_desc<NDimSpatial>();
|
||||
const auto in_grid_desc = make_in_grid_desc<NDimSpatial>();
|
||||
const auto wei_grid_desc = make_wei_grid_desc<NDimSpatial>();
|
||||
|
||||
// B: input tensor comes in K_N
|
||||
const auto in_n_hip_wip_c_grid_desc = transform_tensor_descriptor(
|
||||
in_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N_),
|
||||
make_pad_transform(Wi_, InLeftPadW_, InRightPadW_),
|
||||
make_pass_through_transform(C_)),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}));
|
||||
|
||||
const auto in_n_y_ho_x_wo_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(X_, Wo_), make_tuple(ConvDilationW_, ConvStrideW_)),
|
||||
make_pass_through_transform(C_)),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1, 2>{}, sequence<3>{}));
|
||||
|
||||
const auto in_gemmn_gemmktotal_grid_desc =
|
||||
transform_tensor_descriptor(in_n_y_ho_x_wo_c_grid_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(X_, C_)),
|
||||
make_merge_transform(make_tuple(N_, Wo_))),
|
||||
make_tuple(sequence<1, 3>{}, sequence<0, 2>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
return make_tuple(out_grid_desc, in_gemmn_gemmktotal_grid_desc, wei_grid_desc);
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 2, bool>::type = false>
|
||||
CK_TILE_HOST auto MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N() const
|
||||
{
|
||||
const auto out_grid_desc = make_out_grid_desc<NDimSpatial>();
|
||||
const auto in_grid_desc = make_in_grid_desc<NDimSpatial>();
|
||||
const auto wei_grid_desc = make_wei_grid_desc<NDimSpatial>();
|
||||
|
||||
// B: input tensor comes in K_N
|
||||
const auto in_n_hip_wip_c_grid_desc = transform_tensor_descriptor(
|
||||
in_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_y_ho_x_wo_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(Y_, Ho_), make_tuple(ConvDilationH_, ConvStrideH_)),
|
||||
make_embed_transform(make_tuple(X_, Wo_), 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_gemmn_gemmktotal_grid_desc =
|
||||
transform_tensor_descriptor(in_n_y_ho_x_wo_c_grid_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(Y_, X_, C_)),
|
||||
make_merge_transform(make_tuple(N_, Ho_, Wo_))),
|
||||
make_tuple(sequence<1, 3, 5>{}, sequence<0, 2, 4>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
return make_tuple(out_grid_desc, in_gemmn_gemmktotal_grid_desc, wei_grid_desc);
|
||||
}
|
||||
|
||||
template <index_t NDim = NDimSpatial, typename std::enable_if<NDim == 3, bool>::type = false>
|
||||
CK_TILE_HOST auto MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N() const
|
||||
{
|
||||
const auto out_grid_desc = make_out_grid_desc<NDimSpatial>();
|
||||
const auto in_grid_desc = make_in_grid_desc<NDimSpatial>();
|
||||
const auto wei_grid_desc = make_wei_grid_desc<NDimSpatial>();
|
||||
|
||||
// B: input tensor comes in K_N
|
||||
const auto in_n_hip_wip_c_grid_desc = transform_tensor_descriptor(
|
||||
in_grid_desc,
|
||||
make_tuple(make_pass_through_transform(N_),
|
||||
make_pad_transform(Di_, InLeftPadD_, InRightPadD_),
|
||||
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>{}, sequence<4>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}, sequence<3>{}, sequence<4>{}));
|
||||
|
||||
const auto in_n_y_ho_x_wo_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(Z_, Do_), make_tuple(ConvDilationD_, ConvStrideD_)),
|
||||
make_embed_transform(make_tuple(Y_, Ho_), make_tuple(ConvDilationH_, ConvStrideH_)),
|
||||
make_embed_transform(make_tuple(X_, Wo_), make_tuple(ConvDilationW_, ConvStrideW_)),
|
||||
make_pass_through_transform(C_)),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}, sequence<3>{}, sequence<4>{}),
|
||||
make_tuple(sequence<0>{},
|
||||
sequence<1, 2>{},
|
||||
sequence<3, 4>{},
|
||||
sequence<5, 6>{},
|
||||
sequence<7>{}));
|
||||
|
||||
const auto in_gemmn_gemmktotal_grid_desc = transform_tensor_descriptor(
|
||||
in_n_y_ho_x_wo_c_grid_desc,
|
||||
make_tuple(make_merge_transform(make_tuple(Z_, Y_, X_, C_)),
|
||||
make_merge_transform(make_tuple(N_, Do_, Ho_, Wo_))),
|
||||
make_tuple(sequence<1, 3, 5, 7>{}, sequence<0, 2, 4, 6>{}),
|
||||
make_tuple(sequence<0>{}, sequence<1>{}));
|
||||
|
||||
return make_tuple(out_grid_desc, in_gemmn_gemmktotal_grid_desc, wei_grid_desc);
|
||||
}
|
||||
|
||||
IndexType G_, N_;
|
||||
IndexType Di_, Hi_, Wi_;
|
||||
IndexType Do_, Ho_, Wo_;
|
||||
IndexType Z_, Y_, X_;
|
||||
IndexType K_, C_;
|
||||
IndexType ConvStrideD_, ConvStrideH_, ConvStrideW_;
|
||||
IndexType ConvDilationD_, ConvDilationH_, ConvDilationW_;
|
||||
IndexType InLeftPadD_, InLeftPadH_, InLeftPadW_;
|
||||
IndexType InRightPadD_, InRightPadH_, InRightPadW_;
|
||||
IndexType ZYX_;
|
||||
};
|
||||
|
||||
} // namespace ck_tile
|
||||
Reference in New Issue
Block a user