wehub-resource-sync
104 lines
3.4 KiB
C++
104 lines
3.4 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/reduce_mean_kernel.h"
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#include "paddle/phi/backends/all_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/cast_kernel.h"
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#include "paddle/phi/kernels/reduce_kernel_impl.h"
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namespace phi {
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template <typename T, typename Context>
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void MeanKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const IntArray& dims,
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bool keep_dim,
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DenseTensor* out) {
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bool reduce_all = recompute_reduce_all(x, dims);
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if (std::is_same<T, int>::value || std::is_same<T, int64_t>::value ||
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std::is_same<T, bool>::value) {
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using Type =
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typename std::conditional<std::is_same<T, int>::value ||
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std::is_same<T, int64_t>::value ||
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std::is_same<T, bool>::value,
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float,
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T>::type;
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DenseTensor x_float = Cast<T, Context>(dev_ctx, x, phi::DataType::FLOAT32);
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DenseTensor out_float;
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out_float.Resize(out->dims());
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MeanRawKernel<Type>(
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dev_ctx, x_float, dims, keep_dim, reduce_all, &out_float);
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CastKernel<Type, Context>(dev_ctx, out_float, x.dtype(), out);
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} else {
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MeanRawKernel<T>(dev_ctx, x, dims, keep_dim, reduce_all, out);
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(mean,
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CPU,
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ALL_LAYOUT,
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phi::MeanKernel,
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float,
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double,
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bool,
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int,
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int64_t,
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phi::complex64,
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phi::complex128) {}
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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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PD_REGISTER_KERNEL(mean,
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GPU,
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ALL_LAYOUT,
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phi::MeanKernel,
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float,
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double,
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bool,
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int,
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int64_t,
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phi::float16,
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phi::bfloat16,
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phi::float8_e4m3fn,
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phi::complex64,
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phi::complex128) {}
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#endif
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#if defined(PADDLE_WITH_XPU_KP) && !defined(PADDLE_WITH_XPU)
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PD_REGISTER_KERNEL(mean, KPS, ALL_LAYOUT, phi::MeanKernel, float) {}
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#endif
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#if defined(PADDLE_WITH_DNNL)
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PD_REGISTER_KERNEL(
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mean, OneDNN, ONEDNN, phi::MeanKernel, float, phi::bfloat16) {
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kernel->check_if_onednn_kernel_support_ = phi::ReduceMeanCheckIfOneDNNSupport;
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}
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#endif
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#if defined(PADDLE_WITH_XPU)
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PD_REGISTER_KERNEL(mean,
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XPU,
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ALL_LAYOUT,
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phi::MeanKernel,
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float,
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bool,
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int,
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int64_t,
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phi::float16,
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phi::bfloat16) {}
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#endif
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