wehub-resource-sync
128 lines
4.3 KiB
C++
128 lines
4.3 KiB
C++
// Copyright (c) 2024 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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#pragma once
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#include <algorithm>
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#include <vector>
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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/utils/optional.h"
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namespace phi {
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template <typename T, typename Context>
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void LodResetKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const optional<DenseTensor>& y,
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const std::vector<int>& target_lod,
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bool append,
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DenseTensor* out) {
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auto* in = &x;
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auto* lod_t = y.get_ptr();
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Copy(dev_ctx, *in, in->place(), false, out);
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std::vector<int> level0;
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if (lod_t) {
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if (lod_t->lod().size() > 0) {
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auto y_lod = lod_t->lod();
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auto last_level = y_lod[y_lod.size() - 1];
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PADDLE_ENFORCE_EQ(
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static_cast<int64_t>(last_level.back()),
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in->dims()[0],
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common::errors::InvalidArgument(
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"The last value of Input(Y)'s last level LoD should be equal "
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"to the first dimension of Input(X). But received the last "
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"value of Input(Y)'s last level LoD is %d, the first dimension "
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"of Input(X) is %d.",
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static_cast<int64_t>(last_level.back()),
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in->dims()[0]));
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out->set_lod(y_lod);
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return; // early return, since lod already set
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} else {
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auto* lod = lod_t->data<int>();
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DenseTensor lod_cpu;
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if (lod_t->place().GetType() == AllocationType::GPU) {
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Copy(dev_ctx, *lod_t, CPUPlace(), true, &lod_cpu);
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lod = lod_cpu.data<int>();
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}
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level0 = std::vector<int>(lod, lod + lod_t->numel());
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}
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} else {
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level0 = target_lod;
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}
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PADDLE_ENFORCE_GT(
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level0.size(),
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1UL,
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common::errors::InvalidArgument(
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"The size of target LoD should be greater than 1. But received the "
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"size of target LoD is %d.",
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level0.size()));
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PADDLE_ENFORCE_EQ(static_cast<int64_t>(level0[0]),
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0,
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common::errors::InvalidArgument(
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"Target LoD should be a vector starting from 0. But "
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"target LoD starts from %d.",
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static_cast<int64_t>(level0[0])));
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PADDLE_ENFORCE_EQ(
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static_cast<int64_t>(level0.back()),
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in->dims()[0],
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common::errors::InvalidArgument(
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"The last value of 'Target LoD''s last level LoD should be equal "
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"to the first dimension of Input(X). But received the 'Target LoD' "
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"is %s, Input(X)'s shape is %s.",
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make_ddim(level0),
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in->dims()));
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for (size_t i = 0; i < level0.size() - 1; ++i) {
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PADDLE_ENFORCE_GE(level0[i + 1],
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level0[i],
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common::errors::InvalidArgument(
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"'Target LoD' should be an ascending "
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"vector. But received the Target LoD is %s.",
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make_ddim(level0)));
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}
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// cast level0 to size_t
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std::vector<size_t> ulevel0(level0.size(), 0);
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std::transform(level0.begin(), level0.end(), ulevel0.begin(), [](int a) {
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return static_cast<size_t>(a);
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});
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if (append) {
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auto* out_lod = out->mutable_lod();
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out_lod->push_back(ulevel0);
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} else {
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LegacyLoD target_lod;
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target_lod.push_back(ulevel0);
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out->set_lod(target_lod);
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}
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}
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template <typename T, typename Context>
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void LodResetGradKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& out_grad,
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const std::vector<int>& target_lod,
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bool append,
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DenseTensor* x_grad) {
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auto* d_out = &out_grad;
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auto* d_x = x_grad;
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Copy(dev_ctx, *d_out, d_out->place(), false, d_x);
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}
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} // namespace phi
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