chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/phi/kernels/funcs/math_function.h"
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#include "paddle/phi/core/utils/visit_place.h"
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#ifdef PADDLE_WITH_MKLML
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#include "paddle/phi/backends/dynload/mklml.h"
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#endif
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#ifdef PADDLE_USE_OPENBLAS
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#include <cblas.h>
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#elif PADDLE_USE_ACCELERATE
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#include <Accelerate/Accelerate.h>
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#endif
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#include <memory>
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#include <utility>
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#include <vector>
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#include "paddle/phi/backends/context_pool.h"
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#ifdef PADDLE_WITH_XPU
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#include "paddle/phi/backends/xpu/xpu_context.h"
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#endif
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/math_function_impl.h"
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#ifdef PADDLE_WITH_CUSTOM_DEVICE
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#include "paddle/phi/api/lib/kernel_dispatch.h"
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#include "paddle/phi/core/kernel_factory.h"
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#endif
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namespace phi::funcs {
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template struct SetConstant<CPUContext, phi::float8_e4m3fn>;
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template struct SetConstant<CPUContext, phi::float8_e5m2>;
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template struct SetConstant<CPUContext, phi::float16>;
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template struct SetConstant<CPUContext, phi::bfloat16>;
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template struct SetConstant<CPUContext, float>;
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template struct SetConstant<CPUContext, double>;
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template struct SetConstant<CPUContext, int16_t>;
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template struct SetConstant<CPUContext, int>;
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template struct SetConstant<CPUContext, int64_t>;
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template struct SetConstant<CPUContext, bool>;
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template struct SetConstant<CPUContext, uint8_t>;
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template struct SetConstant<CPUContext, uint16_t>;
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template struct SetConstant<CPUContext, uint32_t>;
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template struct SetConstant<CPUContext, uint64_t>;
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template struct SetConstant<CPUContext, int8_t>;
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template struct SetConstant<CPUContext, phi::complex64>;
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template struct SetConstant<CPUContext, phi::complex128>;
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#ifdef PADDLE_WITH_XPU
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template struct SetConstant<XPUContext, phi::float16>;
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template struct SetConstant<XPUContext, phi::bfloat16>;
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template struct SetConstant<XPUContext, float>;
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template struct SetConstant<XPUContext, double>;
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template struct SetConstant<XPUContext, uint8_t>;
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template struct SetConstant<XPUContext, int8_t>;
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template struct SetConstant<XPUContext, int16_t>;
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template struct SetConstant<XPUContext, int>;
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template struct SetConstant<XPUContext, int64_t>;
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template struct SetConstant<XPUContext, bool>;
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template struct SetConstant<XPUContext, phi::complex64>;
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template struct SetConstant<XPUContext, phi::complex128>;
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#endif // PADDLE_WITH_XPU
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#define DEFINE_CPU_TRANS(RANK) \
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template struct PADDLE_API Transpose<CPUContext, phi::float16, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, phi::bfloat16, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, phi::float8_e4m3fn, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, phi::float8_e5m2, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, float, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, double, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, int, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, int64_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, bool, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, int16_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, uint8_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, uint16_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, uint32_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, uint64_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, int8_t, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, phi::complex64, RANK>; \
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template struct PADDLE_API Transpose<CPUContext, phi::complex128, RANK>;
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DEFINE_CPU_TRANS(1);
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DEFINE_CPU_TRANS(2);
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DEFINE_CPU_TRANS(3);
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DEFINE_CPU_TRANS(4);
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DEFINE_CPU_TRANS(5);
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DEFINE_CPU_TRANS(6);
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#ifdef PADDLE_WITH_XPU
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#define DEFINE_XPU_TRANS(RANK) \
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template struct PADDLE_API Transpose<XPUContext, bool, RANK>; \
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template struct PADDLE_API Transpose<XPUContext, float, RANK>; \
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template struct PADDLE_API Transpose<XPUContext, int, RANK>; \
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template struct PADDLE_API Transpose<XPUContext, int64_t, RANK>; \
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template struct PADDLE_API Transpose<XPUContext, phi::complex64, RANK>;
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DEFINE_XPU_TRANS(1);
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DEFINE_XPU_TRANS(2);
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DEFINE_XPU_TRANS(3);
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DEFINE_XPU_TRANS(4);
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DEFINE_XPU_TRANS(5);
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DEFINE_XPU_TRANS(6);
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#endif // PADDLE_WITH_XPU
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template <typename DeviceContext, typename T>
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void TransposeNormal<DeviceContext, T>::operator()(
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const DeviceContext& dev_ctx UNUSED,
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const DenseTensor& in,
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DenseTensor* out,
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const std::vector<int>& axis) {
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const int rank = static_cast<const int>(axis.size());
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auto in_stride = common::stride(in.dims());
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auto out_stride = common::stride(out->dims());
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const T* in_ptr = in.data<T>();
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T* out_ptr = out->data<T>();
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auto transpose_helper = [&](int64_t beg, int64_t end) {
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for (int64_t out_idx = beg; out_idx < end; ++out_idx) {
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int64_t in_idx = 0;
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int64_t tmp_idx = out_idx;
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// calculate the input index
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for (int i = 0; i < rank; ++i) {
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const int64_t coordinate = tmp_idx / out_stride[i];
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tmp_idx -= coordinate * out_stride[i];
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in_idx += coordinate * in_stride[axis[i]];
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}
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out_ptr[out_idx] = in_ptr[in_idx];
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}
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};
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transpose_helper(0, out->numel());
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}
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// define transpose normal
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#define DEFINE_CPU_TRANS_NORMAL(TYPE) \
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template struct TransposeNormal<CPUContext, TYPE>
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DEFINE_CPU_TRANS_NORMAL(phi::float8_e4m3fn);
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DEFINE_CPU_TRANS_NORMAL(phi::float8_e5m2);
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DEFINE_CPU_TRANS_NORMAL(phi::float16);
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DEFINE_CPU_TRANS_NORMAL(phi::bfloat16);
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DEFINE_CPU_TRANS_NORMAL(float);
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DEFINE_CPU_TRANS_NORMAL(double);
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DEFINE_CPU_TRANS_NORMAL(int);
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DEFINE_CPU_TRANS_NORMAL(int64_t);
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DEFINE_CPU_TRANS_NORMAL(bool);
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DEFINE_CPU_TRANS_NORMAL(int16_t);
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DEFINE_CPU_TRANS_NORMAL(uint8_t);
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DEFINE_CPU_TRANS_NORMAL(uint16_t);
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DEFINE_CPU_TRANS_NORMAL(uint32_t);
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DEFINE_CPU_TRANS_NORMAL(uint64_t);
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DEFINE_CPU_TRANS_NORMAL(int8_t);
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DEFINE_CPU_TRANS_NORMAL(phi::complex64);
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DEFINE_CPU_TRANS_NORMAL(phi::complex128);
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#ifdef PADDLE_WITH_XPU
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#define DEFINE_XPU_TRANS_NORMAL(TYPE) \
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template struct TransposeNormal<XPUContext, TYPE>
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DEFINE_XPU_TRANS_NORMAL(bool);
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DEFINE_XPU_TRANS_NORMAL(float);
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DEFINE_XPU_TRANS_NORMAL(int);
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DEFINE_XPU_TRANS_NORMAL(int64_t);
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DEFINE_XPU_TRANS_NORMAL(phi::complex64);
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#endif // PADDLE_WITH_XPU
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struct TensorSetConstantCPU {
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TensorSetConstantCPU(DenseTensor* tensor, float value)
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: tensor_(tensor), value_(value) {}
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template <typename T>
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void apply() const {
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auto cpu = CPUPlace();
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auto* begin = tensor_->mutable_data<T>(cpu);
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std::fill(begin, begin + tensor_->numel(), static_cast<T>(value_));
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}
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DenseTensor* tensor_;
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float value_;
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};
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template <>
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void set_constant_with_place<XPUPlace>(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value) {
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#ifdef PADDLE_WITH_XPU
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phi::VisitDataType(
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tensor->dtype(),
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TensorSetConstantXPU<float>(tensor, value, tensor->place()));
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#else
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PADDLE_THROW(common::errors::PreconditionNotMet("Not compiled with XPU!"));
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#endif
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}
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template <>
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void set_constant_with_place<phi::IPUPlace>(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value) {
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PADDLE_THROW(common::errors::Unimplemented("IPUPlace is not supported"));
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}
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template <>
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void set_constant_with_place<CustomPlace>(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value) {
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#ifdef PADDLE_WITH_CUSTOM_DEVICE
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auto kernel_result = phi::KernelFactory::Instance().SelectKernelOrThrowError(
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"full",
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{paddle::experimental::ParseBackend(tensor->place()),
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DataLayout::ALL_LAYOUT,
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paddle::experimental::ParseDataType(tensor->dtype())});
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const auto& kernel = kernel_result.kernel;
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using kernel_signature = void (*)(const DeviceContext&,
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const phi::IntArray&,
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const phi::Scalar&,
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DataType,
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DenseTensor*);
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auto* kernel_fn = kernel.GetVariadicKernelFn<kernel_signature>();
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(*kernel_fn)(dev_ctx,
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phi::IntArray(vectorize(tensor->dims())),
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phi::Scalar(value),
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tensor->dtype(),
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tensor);
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#else
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PADDLE_THROW(common::errors::Unimplemented("CustomPlace is not supported"));
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#endif
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}
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template <>
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void set_constant_with_place<CPUPlace>(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value) {
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phi::VisitDataType(tensor->dtype(), TensorSetConstantCPU(tensor, value));
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}
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template <>
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void set_constant_with_place<phi::GPUPinnedPlace>(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value) {
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phi::VisitDataType(tensor->dtype(), TensorSetConstantCPU(tensor, value));
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}
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struct TensorSetConstantWithPlace {
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using argument_type = phi::Place;
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using result_type = void;
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TensorSetConstantWithPlace(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value)
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: dev_ctx_(dev_ctx), tensor_(tensor), value_(value) {}
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template <typename Place>
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void operator()(Place place UNUSED) const {
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set_constant_with_place<Place>(dev_ctx_, tensor_, value_);
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}
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const DeviceContext& dev_ctx_;
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DenseTensor* tensor_;
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float value_;
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};
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void set_constant(const DeviceContext& dev_ctx,
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DenseTensor* tensor,
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float value) {
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TensorSetConstantWithPlace func(dev_ctx, tensor, value);
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#ifdef PADDLE_WITH_CUSTOM_DEVICE
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if (dev_ctx.GetPlace().GetType() == AllocationType::CUSTOM) {
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func(CustomPlace());
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return;
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}
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#endif
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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// tensor->place().apply_visitor(func);
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phi::VisitPlace(tensor->place(), func);
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#elif defined(PADDLE_WITH_XPU)
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if (dev_ctx.GetPlace().GetType() == AllocationType::XPU) {
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func(XPUPlace());
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return;
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} else {
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func(CPUPlace());
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}
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#else
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func(CPUPlace());
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#endif
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}
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template struct ColwiseSum<CPUContext, float>;
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template struct ColwiseSum<CPUContext, double>;
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template struct ColwiseSum<CPUContext, int>;
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template struct ColwiseSum<CPUContext, int64_t>;
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template struct RowwiseMean<CPUContext, float>;
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template struct RowwiseMean<CPUContext, double>;
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template <typename T>
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struct RowwiseAdd<CPUContext, T> {
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void operator()(const CPUContext& dev_ctx UNUSED,
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const DenseTensor& input,
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const DenseTensor& vector,
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DenseTensor* output) {
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auto in_dims = input.dims();
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const auto& out_dims = output->dims();
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auto size = input.numel() / in_dims[0];
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PADDLE_ENFORCE_EQ(
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vector.numel(),
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size,
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common::errors::InvalidArgument(
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"The input vector size"
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" should be equal to the size of each row of input tensor."
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" Expected vector size=%d, but received %d",
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size,
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vector.numel()));
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PADDLE_ENFORCE_EQ(out_dims,
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in_dims,
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common::errors::InvalidArgument(
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"The output tensor shape should be same as the input"
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" tensor shape. Expected output tensor shape: %s,"
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" but received %s",
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in_dims.to_str().c_str(),
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out_dims.to_str().c_str()));
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auto in = EigenMatrix<T>::From(input);
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auto vec = EigenVector<T>::Flatten(vector);
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auto out = EigenMatrix<T>::From(*output);
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for (int64_t i = 0; i < in_dims[0]; ++i) {
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out.chip(i, 0) = in.chip(i, 0) + vec;
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}
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}
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};
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template struct RowwiseAdd<CPUContext, float>;
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template struct RowwiseAdd<CPUContext, double>;
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} // namespace phi::funcs
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