wehub-resource-sync
71 lines
2.5 KiB
C++
71 lines
2.5 KiB
C++
/* 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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#pragma once
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#include <string>
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#include "paddle/fluid/framework/dense_tensor_array.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/phi/core/platform/device_context.h"
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namespace paddle {
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namespace operators {
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class ArrayOp : public framework::OperatorBase {
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public:
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ArrayOp(const std::string &type,
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const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorBase(type, inputs, outputs, attrs) {}
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protected:
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size_t GetOffset(const framework::Scope &scope,
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const phi::Place &place) const {
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auto *i = scope.FindVar(Input("I"));
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PADDLE_ENFORCE_NOT_NULL(i,
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common::errors::NotFound("Input(I) is not found."));
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auto &i_tensor = i->Get<DenseTensor>();
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PADDLE_ENFORCE_EQ(i_tensor.numel(),
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1,
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common::errors::InvalidArgument(
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"Input(I) must have numel 1. "
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"But received %d, and it's shape is [%s].",
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i_tensor.numel(),
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i_tensor.dims()));
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// get device context from pool
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phi::DeviceContextPool &pool = phi::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(place);
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size_t offset;
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if (i_tensor.place().GetType() == phi::AllocationType::GPU ||
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i_tensor.place().GetType() == phi::AllocationType::XPU ||
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i_tensor.place().GetType() == phi::AllocationType::CUSTOM) {
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// FIXME: Avoid copy from GPU to CPU
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DenseTensor t;
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phi::Copy(dev_ctx, i_tensor, phi::CPUPlace(), false, &t);
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dev_ctx.Wait();
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offset = static_cast<size_t>(*t.data<int64_t>());
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} else {
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offset = static_cast<size_t>(*i_tensor.data<int64_t>());
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}
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VLOG(10) << " Offset = " << offset;
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return offset;
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}
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};
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} // namespace operators
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} // namespace paddle
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