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// Copyright (c) 2018 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/fluid/operators/sequence_enumerate_op.h"
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namespace paddle {
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namespace operators {
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class SequenceEnumerateOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(
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ctx->HasInput("X"),
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"Input(X) of SequecceEnumerate operator should not be null.");
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PADDLE_ENFORCE(
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ctx->HasOutput("Out"),
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"Output(X) of SequenceEnumerate operator should not be null.");
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const auto x_dims = ctx->GetInputDim("X");
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PADDLE_ENFORCE(
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x_dims.size() == 2 && x_dims[1] == 1,
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"Input(X) of SequenceEnumerate operator should be a 2-D LoDTensor "
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"with the 2nd dimension equal to 1.");
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const auto win_size = ctx->Attrs().Get<int>("win_size");
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PADDLE_ENFORCE(win_size <= x_dims[0],
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"The enumerate window size should be less than or equal to "
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"input sequence length.");
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ctx->SetOutputDim("Out", {x_dims[0], win_size});
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ctx->ShareLoD("X", "Out");
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}
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};
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class SequenceEnumerateOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X",
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"(2-D LoDTensor with the 2nd dimension equal to 1) "
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"Input LoDTensor of SequenceEnumerate operator.");
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AddOutput("Out",
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"(2-D LoDTensor with the 2nd dimension equal to 1) "
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"Output LoDTensor of SequenceEnumerate operator.");
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AddAttr<int>("win_size", "(int) The enumerate sequence window size.")
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.AddCustomChecker([](const int& win_size) {
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PADDLE_ENFORCE(win_size >= 2,
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"The window size should be greater than 2.");
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});
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AddAttr<int>("pad_value", "(int) The enumerate sequence padding value.")
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.SetDefault(0);
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AddComment(R"DOC(
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Sequence Enumerate Operator.
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Sequence enumerate operator generate a new LoDTensor
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with the same 1st dimension length as the original LoDTensor,
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and with the 2nd dimension equal to the input window length,
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the new sub-sequence on 2nd dimension is enumerated one by one on the original sequence.
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The values of the last insufficient part areall filled with the input pad_value.
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Examples:
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Case 1:
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Input:
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X.lod = [[0, 3, 5]]
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X.data = [1, 2, 3, 4, 5]
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X.dims = [5, 1]
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Attrs:
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win_size = 2
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pad_value = 0
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Output:
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Out.lod = [[0, 3, 5]]
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Out.data = [[1, 2], [2, 3], [3, 4], [4, 5], [0, 0]]
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Out.dims = [5, 2]
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Currently, only 1-level LoDTensor is supported.
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_WITHOUT_GRADIENT(sequence_enumerate, ops::SequenceEnumerateOp,
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ops::SequenceEnumerateOpMaker);
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REGISTER_OP_CPU_KERNEL(
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sequence_enumerate,
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ops::SequenceEnumerateKernel<paddle::platform::CPUDeviceContext, int32_t>,
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ops::SequenceEnumerateKernel<paddle::platform::CPUDeviceContext, int64_t>);
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@ -0,0 +1,75 @@
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// Copyright (c) 2018 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 <thrust/device_vector.h>
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#include <thrust/host_vector.h>
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#include "paddle/fluid/operators/sequence_enumerate_op.h"
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#include "paddle/fluid/platform/cuda_primitives.h"
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namespace paddle {
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namespace operators {
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using platform::PADDLE_CUDA_NUM_THREADS;
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using LoDTensor = framework::LoDTensor;
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template <typename T>
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__global__ void CalcOutPut(const T* in_data, const int64_t in_len,
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const int64_t win_size, const int64_t pad_value,
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T* out_data) {
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int index = blockIdx.x * blockDim.x + threadIdx.x;
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if (index < in_len) {
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for (size_t i = 0; i < win_size; ++i) {
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int word_pos = index + i;
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out_data[index * win_size + i] =
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word_pos < in_len ? in_data[word_pos] : pad_value;
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}
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}
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}
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template <typename T>
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class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* in = context.Input<LoDTensor>("X");
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auto* out = context.Output<LoDTensor>("Out");
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int win_size = context.Attr<int>("win_size");
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int pad_value = context.Attr<int>("pad_value");
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auto in_dims = in->dims();
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auto in_lod = in->lod();
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PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
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"Only support one level sequence now.");
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PADDLE_ENFORCE_EQ(
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static_cast<uint64_t>(in_dims[0]), in_lod[0].back(),
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"The actual input data's size mismatched with LoD information.");
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/* Generate enumerate sequence set */
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auto stream = context.cuda_device_context().stream();
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auto in_len = in->numel();
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auto in_data = in->data<T>();
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auto out_data = out->mutable_data<T>(context.GetPlace());
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// Calc output tensor
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CalcOutPut<<<(in_len - 1) / PADDLE_CUDA_NUM_THREADS + 1,
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PADDLE_CUDA_NUM_THREADS, 0, stream>>>(
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in_data, in_len, win_size, pad_value, out_data);
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}
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};
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} // namespace operators
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} // namespace paddle
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REGISTER_OP_CUDA_KERNEL(
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sequence_enumerate,
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paddle::operators::SequenceEnumerateOpCUDAKernel<int32_t>,
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paddle::operators::SequenceEnumerateOpCUDAKernel<int64_t>);
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// Copyright (c) 2018 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 "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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using LoDTensor = framework::LoDTensor;
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template <typename DeviceContext, typename T>
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class SequenceEnumerateKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* in = context.Input<LoDTensor>("X");
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auto* out = context.Output<LoDTensor>("Out");
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int win_size = context.Attr<int>("win_size");
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int pad_value = context.Attr<int>("pad_value");
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auto in_dims = in->dims();
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auto in_lod = in->lod();
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PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
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"Only support one level sequence now.");
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PADDLE_ENFORCE_EQ(
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static_cast<uint64_t>(in_dims[0]), in_lod[0].back(),
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"The actual input data's size mismatched with LoD information.");
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// Generate enumerate sequence set
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auto seq_length = in_dims[0];
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auto in_data = in->data<T>();
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auto out_data = out->mutable_data<T>(context.GetPlace());
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for (int idx = 0; idx < seq_length; ++idx) {
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for (int word_idx = 0; word_idx < win_size; ++word_idx) {
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int word_pos = idx + word_idx;
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out_data[win_size * idx + word_idx] =
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word_pos < seq_length ? in_data[word_pos] : pad_value;
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}
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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# Copyright (c) 2018 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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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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def sequence_enumerate(input_seq, lod0, win_size, pad_value):
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out_seq = []
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for idx in range(0, len(input_seq)):
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single_seq = []
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for word_idx in range(win_size):
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word_pos = idx + word_idx
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dat = input_seq[word_pos] if word_pos < len(input_seq) \
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else pad_value
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single_seq.append(dat)
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out_seq.append(single_seq)
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return out_seq
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class TestSequenceEnumerateOp(OpTest):
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def setUp(self):
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self.op_type = "sequence_enumerate"
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self.init_test_case()
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self.inputs = {'X': (self.in_seq, self.lod)}
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self.attrs = {'win_size': self.win_size, 'pad_value': self.pad_value}
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self.outputs = {'Out': (self.out_seq, self.lod)}
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def test_check_output(self):
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self.check_output()
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def init_test_case(self):
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self.in_seq = np.random.randint(0, 10, (30, 1)).astype("int32")
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self.lod = [[9, 4, 11, 6]]
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self.win_size = 2
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self.pad_value = 0
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out_seq = sequence_enumerate(self.in_seq, self.lod[0], self.win_size,
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self.pad_value)
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self.out_seq = np.array(out_seq).astype("int32")
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class TesSequenceEnumerateOpInt64(TestSequenceEnumerateOp):
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def init_test_case(self):
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self.in_seq = np.random.randint(0, 10, (30, 1)).astype("int64")
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self.lod = [[9, 4, 11, 6]]
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self.win_size = 2
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self.pad_value = 0
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out_seq = sequence_enumerate(self.in_seq, self.lod[0], self.win_size,
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self.pad_value)
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self.out_seq = np.array(out_seq).astype("int64")
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class TestSequenceEnumerateOpMaxWinSize(TestSequenceEnumerateOp):
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def init_test_case(self):
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self.in_seq = np.random.randint(0, 10, (30, 1)).astype("int32")
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self.lod = [[9, 4, 11, 6]]
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self.win_size = 30
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self.pad_value = 0
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out_seq = sequence_enumerate(self.in_seq, self.lod[0], self.win_size,
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self.pad_value)
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self.out_seq = np.array(out_seq).astype("int32")
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if __name__ == "__main__":
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unittest.main()
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Loading…
Reference in new issue