wehub-resource-sync
61 lines
2.0 KiB
C++
61 lines
2.0 KiB
C++
/* Copyright (c) 2022 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/unstack_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 UnStackKernel(const Context &dev_ctx,
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const DenseTensor &x,
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int axis,
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int num,
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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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if (axis < 0) axis += x_dims.size();
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auto x_shape = vectorize<int64_t>(x_dims);
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std::vector<int64_t> dx_dims_list(outs.size(), 1);
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std::vector<XPUType *> dx_lists;
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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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dx_lists.push_back(reinterpret_cast<XPUType *>(outs[j]->data<T>()));
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}
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int r = xpu::split<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<const XPUType *>(x.data<T>()),
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dx_lists,
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x_shape,
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dx_dims_list,
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axis);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "split in unstack op");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(unstack,
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XPU,
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ALL_LAYOUT,
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phi::UnStackKernel,
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phi::float16,
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float,
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int,
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int64_t) {}
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