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Unverified Commit ac9e01e2 authored by Illia Silin's avatar Illia Silin Committed by GitHub
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Clean-up the headers (#713) 



* fix headers for gpu instances

* remove unused headers

---------
Co-authored-by: default avatarzjing14 <zhangjing14@gmail.com>
parent 76ec0089
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Showing with 19 additions and 479 deletions
include/ck/utility/print.hpp deleted 100644 → 0
View file @ 76ec0089
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#ifndef CK_PRINT_HPP
#define CK_PRINT_HPP
#include "array.hpp"
#include "statically_indexed_array.hpp"
#include "container_helper.hpp"
#include "sequence.hpp"
namespace ck {
template <typename T>
__host__ __device__ void print_array(const char* s, T a)
{
constexpr index_t nsize = a.Size();
printf("%s size %d, {", s, nsize);
static_for<0, nsize, 1>{}([&a](auto i) constexpr { printf("%d, ", int32_t{a[i]}); });
printf("}\n");
}
} // namespace ck
#endif
library/include/ck/library/reference_tensor_operation/cpu/reference_gemm_bias_2d.hpp deleted 100644 → 0
View file @ 76ec0089
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <iostream>
#include <sstream>
#include "ck/tensor_operation/gpu/device/device_base.hpp"
#include "ck/library/utility/host_tensor.hpp"
namespace ck {
namespace tensor_operation {
namespace host {
template <typename ADataType,
typename BDataType,
typename C0DataType,
typename CDataType,
typename AccDataType,
typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation>
struct ReferenceGemmBias2D : public device::BaseOperator
{
// Argument
struct Argument : public device::BaseArgument
{
Argument(const Tensor<ADataType>& a_m_k,
const Tensor<BDataType>& b_k_n,
const Tensor<C0DataType>& c0_m_n,
Tensor<CDataType>& c_m_n,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op)
: a_m_k_{a_m_k},
b_k_n_{b_k_n},
c0_m_n_{c0_m_n},
c_m_n_{c_m_n},
a_element_op_{a_element_op},
b_element_op_{b_element_op},
c_element_op_{c_element_op}
{
}
const Tensor<ADataType>& a_m_k_;
const Tensor<BDataType>& b_k_n_;
const Tensor<CDataType>& c0_m_n_;
Tensor<CDataType>& c_m_n_;
AElementwiseOperation a_element_op_;
BElementwiseOperation b_element_op_;
CElementwiseOperation c_element_op_;
};
// Invoker
struct Invoker : public device::BaseInvoker
{
using Argument = ReferenceGemmBias2D::Argument;
float Run(const Argument& arg)
{
auto f_mk_kn_mn = [&](auto m, auto n) {
const int K = arg.a_m_k_.mDesc.GetLengths()[1];
AccDataType a = 0;
AccDataType b = 0;
AccDataType acc = 0;
for(int k = 0; k < K; ++k)
{
arg.a_element_op_(a, ck::type_convert<AccDataType>(arg.a_m_k_(m, k)));
arg.b_element_op_(b, ck::type_convert<AccDataType>(arg.b_k_n_(k, n)));
acc += a * b;
}
CDataType cast_acc = static_cast<CDataType>(acc);
arg.c_element_op_(arg.c_m_n_(m, n), cast_acc, arg.c0_m_n_(m, n));
};
make_ParallelTensorFunctor(
f_mk_kn_mn, arg.c_m_n_.mDesc.GetLengths()[0], arg.c_m_n_.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
return 0;
}
float Run(const device::BaseArgument* p_arg,
const StreamConfig& /* stream_config */ = StreamConfig{}) 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(const Tensor<ADataType>& a_m_k,
const Tensor<BDataType>& b_k_n,
const Tensor<C0DataType>& c0_m_n,
Tensor<CDataType>& c_m_n,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op)
{
return Argument{a_m_k, b_k_n, c0_m_n, c_m_n, a_element_op, b_element_op, c_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 << "ReferenceGemmBias2D"
<< std::endl;
// clang-format on
return str.str();
}
};
} // namespace host
} // namespace tensor_operation
} // namespace ck
library/include/ck/library/reference_tensor_operation/cpu/reference_gemm_bias_activation.hpp deleted 100644 → 0
View file @ 76ec0089
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <iostream>
#include <sstream>
#include "ck/tensor_operation/gpu/device/device_base.hpp"
#include "ck/library/utility/host_tensor.hpp"
namespace ck {
namespace tensor_operation {
namespace host {
template <typename ADataType,
typename BDataType,
typename CDataType,
typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation>
struct ReferenceGemmBiasActivation : public device::BaseOperator
{
// Argument
struct Argument : public device::BaseArgument
{
Argument(const Tensor<ADataType>& a_m_k,
const Tensor<BDataType>& b_k_n,
Tensor<CDataType>& c_m_n,
const Tensor<CDataType>& c0_n,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op)
: a_m_k_{a_m_k},
b_k_n_{b_k_n},
c_m_n_{c_m_n},
c0_n_{c0_n},
a_element_op_{a_element_op},
b_element_op_{b_element_op},
c_element_op_{c_element_op}
{
}
const Tensor<ADataType>& a_m_k_;
const Tensor<BDataType>& b_k_n_;
Tensor<CDataType>& c_m_n_;
const Tensor<CDataType>& c0_n_;
AElementwiseOperation a_element_op_;
BElementwiseOperation b_element_op_;
CElementwiseOperation c_element_op_;
};
// Invoker
struct Invoker : public device::BaseInvoker
{
using Argument = ReferenceGemmBiasActivation::Argument;
float Run(const Argument& arg)
{
auto f_mk_kn_mn = [&](auto m, auto n) {
const int K = arg.a_m_k_.mDesc.GetLengths()[1];
float v_acc = 0;
for(int k = 0; k < K; ++k)
{
float v_a;
float v_b;
arg.a_element_op_(v_a, static_cast<const float>(arg.a_m_k_(m, k)));
arg.b_element_op_(v_b, static_cast<const float>(arg.b_k_n_(k, n)));
v_acc += v_a * v_b;
}
float v_c;
arg.c_element_op_(v_c, v_acc, static_cast<float>(arg.c0_n_(n)));
arg.c_m_n_(m, n) = v_c;
};
make_ParallelTensorFunctor(
f_mk_kn_mn, arg.c_m_n_.mDesc.GetLengths()[0], arg.c_m_n_.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
return 0;
}
float Run(const device::BaseArgument* p_arg,
const StreamConfig& /* stream_config */ = StreamConfig{}) 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(const Tensor<ADataType>& a_m_k,
const Tensor<BDataType>& b_k_n,
Tensor<CDataType>& c_m_n,
const Tensor<CDataType>& c0_n,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op)
{
return Argument{a_m_k, b_k_n, c_m_n, c0_n, a_element_op, b_element_op, c_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 << "ReferenceGemmBiasActivation"
<< std::endl;
// clang-format on
return str.str();
}
};
} // namespace host
} // namespace tensor_operation
} // namespace ck
library/include/ck/library/tensor_operation_instance/gpu/batched_gemm.hpp
View file @ ac9e01e2
......@@ -3,8 +3,8 @@
#pragma once
#include <cstdlib>
#include <vector>
#include <memory>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm.hpp"
......
library/include/ck/library/tensor_operation_instance/gpu/batched_gemm_add_relu_gemm_add.hpp
View file @ ac9e01e2
......@@ -3,8 +3,8 @@
#pragma once
#include <cstdlib>
#include <vector>
#include <memory>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_multiple_d_gemm_multiple_d.hpp"
......
library/include/ck/library/tensor_operation_instance/gpu/batched_gemm_bias_softmax_gemm_permute.hpp
View file @ ac9e01e2
......@@ -3,8 +3,8 @@
#pragma once
#include <cstdlib>
#include <vector>
#include <memory>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_softmax_gemm_permute.hpp"
......
library/include/ck/library/tensor_operation_instance/gpu/batched_gemm_gemm.hpp
View file @ ac9e01e2
......@@ -3,8 +3,8 @@
#pragma once
#include <cstdlib>
#include <vector>
#include <memory>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_gemm.hpp"
......
library/include/ck/library/tensor_operation_instance/gpu/batched_gemm_softmax_gemm_permute.hpp
View file @ ac9e01e2
......@@ -3,8 +3,8 @@
#pragma once
#include <cstdlib>
#include <vector>
#include <memory>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_softmax_gemm_permute.hpp"
......
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