wehub-resource-sync
148 lines
4.5 KiB
C++
148 lines
4.5 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/unsqueeze_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/core/tensor_utils.h"
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#include "paddle/phi/kernels/funcs/unsqueeze.h"
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namespace phi {
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template <typename T, typename Context>
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void UnsqueezeKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const IntArray& axes,
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DenseTensor* out) {
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auto x_dims = x.dims();
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auto out_dims = out->dims();
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if (axes.FromTensor() && out->dims()[0] == -1) {
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out_dims = funcs::GetUnsqueezeShape(axes.GetData(), x_dims);
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}
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out->Resize(out_dims);
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dev_ctx.template Alloc<T>(out);
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if (x.Holder() == out->Holder()) {
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return;
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}
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phi::Copy(dev_ctx, x, dev_ctx.GetPlace(), false, out);
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out->Resize(out_dims); // copy will reset the dims.
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}
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template <typename T, typename Context>
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void UnsqueezeWithXShapeKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const IntArray& axes,
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DenseTensor* out,
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DenseTensor* xshape UNUSED) {
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UnsqueezeKernel<T, Context>(dev_ctx, x, axes, out);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(unsqueeze,
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CPU,
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ALL_LAYOUT,
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phi::UnsqueezeKernel,
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float,
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double,
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phi::bfloat16,
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bool,
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int,
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int16_t,
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uint8_t,
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int8_t,
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int64_t,
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phi::complex64,
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phi::complex128) {}
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PD_REGISTER_KERNEL(unsqueeze_with_xshape,
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CPU,
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ALL_LAYOUT,
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phi::UnsqueezeWithXShapeKernel,
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float,
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double,
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phi::bfloat16,
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bool,
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int,
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int16_t,
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uint8_t,
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int8_t,
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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(unsqueeze,
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GPU,
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ALL_LAYOUT,
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phi::UnsqueezeKernel,
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float,
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double,
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phi::float16,
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phi::bfloat16,
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bool,
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int,
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int16_t,
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uint8_t,
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int8_t,
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int64_t,
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phi::complex64,
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phi::complex128) {}
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PD_REGISTER_KERNEL(unsqueeze_with_xshape,
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GPU,
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ALL_LAYOUT,
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phi::UnsqueezeWithXShapeKernel,
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bool,
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float,
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double,
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int,
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int8_t,
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int64_t,
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int16_t,
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uint8_t,
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phi::float16,
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phi::bfloat16,
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phi::complex64,
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phi::complex128) {}
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#endif
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#ifdef PADDLE_WITH_XPU
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PD_REGISTER_KERNEL(unsqueeze,
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XPU,
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ALL_LAYOUT,
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phi::UnsqueezeKernel,
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float,
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double,
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phi::float16,
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phi::bfloat16,
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bool,
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int,
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uint8_t,
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int8_t,
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int64_t) {}
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PD_REGISTER_KERNEL(unsqueeze_with_xshape,
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XPU,
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ALL_LAYOUT,
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phi::UnsqueezeWithXShapeKernel,
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float,
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double,
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phi::float16,
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phi::bfloat16,
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bool,
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int,
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uint8_t,
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int8_t,
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int64_t) {}
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#endif
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