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Add instances of grouped convolution 3d forward with a ConvScale element-wise op for bf8@bf8->fp8 (#1326)

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We are adding more instances of grouped convolution 3d forward with a ConvScale element-wise operation.
This commit handles bf8@bf8->fp8 data types combination.

* Included an example.
* Added instances.
* Added a client example.

---------

Co-authored-by: Rostyslav Geyyer <rosty.geyyer@amd.com>
Co-authored-by: Bartłomiej Kocot <barkocot@amd.com>
This commit is contained in:
Andriy Roshchenko
2024-06-21 19:02:57 -06:00
committed by GitHub
parent fa129c1a5d
commit 05b10e0e5a
9 changed files with 295 additions and 32 deletions
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7
client_example/24_grouped_conv_activation/CMakeLists.txt
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@@ -40,9 +40,14 @@ add_executable(client_conv3d_fwd_convinvscale_fp8
grouped_convnd_fwd_convinvscale/conv3d_fwd_convinvscale_fp8.cpp)
target_link_libraries(client_conv3d_fwd_convinvscale_fp8 PRIVATE composable_kernel::device_conv_operations)
# Fwd convscale
add_executable(client_conv3d_fwd_convscale_fp8
add_executable(client_conv3d_fwd_convscale_fp8
grouped_convnd_fwd_convscale/conv3d_fwd_convscale_fp8.cpp)
target_link_libraries(client_conv3d_fwd_convscale_fp8 PRIVATE composable_kernel::device_conv_operations)
add_executable(client_conv3d_fwd_convscale_bf8
grouped_convnd_fwd_convscale/conv3d_fwd_convscale_bf8.cpp)
target_link_libraries(client_conv3d_fwd_convscale_bf8 PRIVATE composable_kernel::device_conv_operations)
add_executable(client_conv3d_fwd_convscale_fp8_bf8
grouped_convnd_fwd_convscale/conv3d_fwd_convscale_fp8_bf8.cpp)
target_link_libraries(client_conv3d_fwd_convscale_fp8_bf8 PRIVATE composable_kernel::device_conv_operations)

50
client_example/24_grouped_conv_activation/grouped_convnd_fwd_convscale/conv3d_fwd_convscale_bf8.cpp Normal file
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@@ -0,0 +1,50 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#include "common.hpp"
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
using InDataType = ck::bf8_t;
using WeiDataType = ck::bf8_t;
using CShuffleDataType = float;
using OutDataType = ck::f8_t;
using AComputeDataType = InDataType;
using BComputeDataType = AComputeDataType;
using InLayout = ck::tensor_layout::convolution::NDHWGC;
using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
using OutLayout = ck::tensor_layout::convolution::NDHWGK;
static constexpr ck::index_t NumDimSpatial = 3;
static constexpr ck::index_t G = 1;
static constexpr ck::index_t N = 64;
static constexpr ck::index_t K = 128;
static constexpr ck::index_t C = 64;
static constexpr ck::index_t Z = 3;
static constexpr ck::index_t Y = 3;
static constexpr ck::index_t X = 3;
static constexpr ck::index_t Di = 28;
static constexpr ck::index_t Hi = 28;
static constexpr ck::index_t Wi = 3;
static constexpr ck::index_t Do = 28;
static constexpr ck::index_t Ho = 28;
static constexpr ck::index_t Wo = 3;
int main()
{
return run_grouped_conv_fwd_convscale<NumDimSpatial,
InDataType,
WeiDataType,
OutDataType,
InLayout,
WeiLayout,
OutLayout,
3,
AComputeDataType,
BComputeDataType>(
{N, Di, Hi, Wi, G, C}, {G, K, Z, Y, X, C}, {N, Do, Ho, Wo, G, K})
? EXIT_SUCCESS
: EXIT_FAILURE;
}