49 lines
1.7 KiB
C++
49 lines
1.7 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/unbind_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void UnbindKernel(const Context& dev_ctx,
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const DenseTensor& x,
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int axis,
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std::vector<DenseTensor*> outs) {
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using XPUType = typename XPUTypeTrait<T>::Type;
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auto x_dims = x.dims();
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axis = axis < 0 ? x_dims.size() + axis : axis;
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std::vector<XPUType*> y_ptrs;
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for (size_t j = 0; j < outs.size(); ++j) {
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dev_ctx.template Alloc<T>(outs[j]);
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y_ptrs.emplace_back(reinterpret_cast<XPUType*>(outs[j]->data<T>()));
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}
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auto x_shape = vectorize<int64_t>(x.dims());
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int r = xpu::unbind(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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y_ptrs,
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x_shape,
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static_cast<int64_t>(axis));
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "unbind");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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unbind, XPU, ALL_LAYOUT, phi::UnbindKernel, float, phi::bfloat16) {}
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