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https://github.com/ROCm/composable_kernel.git
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batched_gemm + multiple_d + gemm + multiple_d (#394)
* refactor
* start
* add device gemm file
* add BatchStrideD0
* add stridd0
* add gridwise file
* add d0 parameters to gridwise gemm
* add c layout transformer
* add d0 threadwise copy
* init kernel
* init kernel
* regular code
* nm desc put to out
* kernel parameter can not use reference
* host add bias+gelu
* run right for bias+gelu
* change AddFastGelu into another file
* interface add d1 bias parameters
* add d1 parameter to argument
* add d1 parameter to gridwise
* first all code,not verify
* gelu change to relu and GetElementSpaceSize bug
* add instance
* start add to ckprofiler
* ckprofiler finish code
* change input parameter for ckProfiler
* fix host bias+gelu bug
* show help for ckProfiler
* fix bug for lunch kernel ignore parametes
* add pad and fix about bug
* mutiple d0
* add dynamic d0_element_op
* change profiler and instance to mutiple d0
* example have 2 d0
* remove some comments not using
* change 2 d0 have self parameters
* change d element_op name
* change class name(multiple_d)
* fix bug
* fix bug that don't find file
* update profiler
* refactor
* update profiler
* clean
* revert example change
* add gon layout
* optimize parameter for gno
* add gon to gemm+gemm
* change helping input parameters
* change to GemmPadder_v2
* using ForEach
* fix gb_per_sec
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
Co-authored-by: ltqin <letaoqin@amd.com>
[ROCm/composable_kernel commit: 370efa6c08]
This commit is contained in:
ltqin
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// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include <cstdlib>
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#include "ck/ck.hpp"
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#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
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#include "ck/tensor_operation/gpu/device/device_batched_gemm_multiple_d_gemm_multiple_d.hpp"
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#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
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using CDE0ElementOp = ck::tensor_operation::element_wise::AddRelu;
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using CDE1ElementOp = ck::tensor_operation::element_wise::Add;
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namespace ck {
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namespace tensor_operation {
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namespace device {
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namespace instance {
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void add_device_batched_gemm_add_relu_gemm_add_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gno_gmo_instance(
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std::vector<std::unique_ptr<DeviceBatchedGemmMultipleDGemmMultipleD<Row,
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Col,
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ck::Tuple<Row>,
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Row,
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ck::Tuple<Row>,
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Row,
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F16,
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F16,
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ck::Tuple<F16>,
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F16,
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ck::Tuple<F16>,
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F16,
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PassThrough,
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PassThrough,
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CDE0ElementOp,
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PassThrough,
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CDE1ElementOp>>>&
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instances);
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void add_device_batched_gemm_add_relu_gemm_add_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gon_gmo_instance(
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std::vector<std::unique_ptr<DeviceBatchedGemmMultipleDGemmMultipleD<Row,
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Col,
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ck::Tuple<Row>,
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Col,
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ck::Tuple<Row>,
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Row,
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F16,
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F16,
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ck::Tuple<F16>,
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F16,
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ck::Tuple<F16>,
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F16,
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PassThrough,
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PassThrough,
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CDE0ElementOp,
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PassThrough,
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CDE1ElementOp>>>&
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instances);
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template <typename A0Layout,
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typename B0Layout,
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typename D0sLayout,
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typename B1Layout,
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typename D1sLayout,
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typename E1Layout,
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typename A0DataType,
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typename B0DataType,
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typename D0sDataType,
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typename B1DataType,
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typename D1sDataType,
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typename E1DataType>
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struct DeviceOperationInstanceFactory<
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ck::tensor_operation::device::DeviceBatchedGemmMultipleDGemmMultipleD<A0Layout,
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B0Layout,
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D0sLayout,
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B1Layout,
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D1sLayout,
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E1Layout,
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A0DataType,
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B0DataType,
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D0sDataType,
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B1DataType,
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D1sDataType,
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E1DataType,
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PassThrough,
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PassThrough,
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CDE0ElementOp,
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PassThrough,
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CDE1ElementOp>>
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{
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using DeviceOp = DeviceBatchedGemmMultipleDGemmMultipleD<A0Layout,
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B0Layout,
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D0sLayout,
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B1Layout,
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D1sLayout,
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E1Layout,
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A0DataType,
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B0DataType,
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D0sDataType,
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B1DataType,
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D1sDataType,
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E1DataType,
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PassThrough,
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PassThrough,
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CDE0ElementOp,
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PassThrough,
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CDE1ElementOp>;
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static auto GetInstances()
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{
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std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
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if constexpr(is_same_v<A0DataType, half_t> && is_same_v<B0DataType, half_t> &&
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is_same_v<B1DataType, half_t> && is_same_v<E1DataType, half_t>)
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{
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if constexpr(is_same_v<A0Layout, Row> && is_same_v<B0Layout, Col> &&
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is_same_v<B1Layout, Row> && is_same_v<E1Layout, Row>)
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{
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add_device_batched_gemm_add_relu_gemm_add_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gno_gmo_instance(
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op_ptrs);
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}
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else if constexpr(is_same_v<A0Layout, Row> && is_same_v<B0Layout, Col> &&
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is_same_v<B1Layout, Col> && is_same_v<E1Layout, Row>)
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{
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add_device_batched_gemm_add_relu_gemm_add_xdl_cshuffle_f16_f16_f16_f16_gmk_gnk_gon_gmo_instance(
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op_ptrs);
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}
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}
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return op_ptrs;
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}
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};
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} // namespace instance
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} // namespace device
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} // namespace tensor_operation
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} // namespace ck
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