feat: add sequence enumerate op

paddle/fluid/operators/sequence_enumerate_op.cc

+//   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/operators/sequence_enumerate_op.h"
+
+namespace paddle {
+namespace operators {
+
+class SequenceEnumerateOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    PADDLE_ENFORCE(
+        ctx->HasInput("X"),
+        "Input(X) of SequecceEnumerate operator should not be null.");
+    PADDLE_ENFORCE(
+        ctx->HasOutput("Out"),
+        "Output(X) of SequenceEnumerate operator should not be null.");
+
+    const auto x_dims = ctx->GetInputDim("X");
+    PADDLE_ENFORCE(
+        x_dims.size() == 2 && x_dims[1] == 1,
+        "Input(X) of SequenceEnumerate operator should be a 2-D LoDTensor "
+        "with the 2nd dimension equal to 1.");
+
+    const auto win_size = ctx->Attrs().Get<int>("win_size");
+    PADDLE_ENFORCE(win_size <= x_dims[0],
+                   "The enumerate window size should be less than or equal to "
+                   "input sequence length.");
+    ctx->SetOutputDim("Out", {x_dims[0], win_size});
+    ctx->ShareLoD("X", "Out");
+  }
+};
+
+class SequenceEnumerateOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override {
+    AddInput("X",
+             "(2-D LoDTensor with the 2nd dimension equal to 1) "
+             "Input LoDTensor of SequenceEnumerate operator.");
+    AddOutput("Out",
+              "(2-D LoDTensor with the 2nd dimension equal to 1) "
+              "Output LoDTensor of SequenceEnumerate operator.");
+    AddAttr<int>("win_size", "(int) The enumerate sequence window size.")
+        .AddCustomChecker([](const int& win_size) {
+          PADDLE_ENFORCE(win_size >= 2,
+                         "The window size should be greater than 2.");
+        });
+    AddAttr<int>("pad_value", "(int) The enumerate sequence padding value.")
+        .SetDefault(0);
+    AddComment(R"DOC(
+Sequence Enumerate Operator.
+
+Sequence enumerate operator generate a new LoDTensor 
+with the same 1st dimension length as the original LoDTensor, 
+and with the 2nd dimension equal to the input window length, 
+the new sub-sequence on 2nd dimension is enumerated one by one on the original sequence.
+The values of the last insufficient part areall filled with the input pad_value.
+
+Examples:
+Case 1:
+  Input:
+    X.lod = [[0, 3, 5]]
+    X.data = [1, 2, 3, 4, 5]
+    X.dims = [5, 1]
+  Attrs:
+    win_size = 2
+    pad_value = 0
+  Output:
+    Out.lod = [[0, 3, 5]]
+    Out.data = [[1, 2], [2, 3], [3, 4], [4, 5], [0, 0]]
+    Out.dims = [5, 2]
+
+  Currently, only 1-level LoDTensor is supported.
+
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_WITHOUT_GRADIENT(sequence_enumerate, ops::SequenceEnumerateOp,
+                             ops::SequenceEnumerateOpMaker);
+REGISTER_OP_CPU_KERNEL(
+    sequence_enumerate,
+    ops::SequenceEnumerateKernel<paddle::platform::CPUDeviceContext, int32_t>,
+    ops::SequenceEnumerateKernel<paddle::platform::CPUDeviceContext, int64_t>);

paddle/fluid/operators/sequence_enumerate_op.cu

+//   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <thrust/device_vector.h>
+#include <thrust/host_vector.h>
+#include "paddle/fluid/operators/sequence_enumerate_op.h"
+#include "paddle/fluid/platform/cuda_primitives.h"
+
+namespace paddle {
+namespace operators {
+using platform::PADDLE_CUDA_NUM_THREADS;
+using LoDTensor = framework::LoDTensor;
+
+template <typename T>
+__global__ void CalcOutPut(const T* in_data, const int64_t in_len,
+                           const int64_t win_size, const int64_t pad_value,
+                           T* out_data) {
+  int index = blockIdx.x * blockDim.x + threadIdx.x;
+  if (index < in_len) {
+    for (size_t i = 0; i < win_size; ++i) {
+      int word_pos = index + i;
+      out_data[index * win_size + i] =
+          word_pos < in_len ? in_data[word_pos] : pad_value;
+    }
+  }
+}
+
+template <typename T>
+class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* in = context.Input<LoDTensor>("X");
+    auto* out = context.Output<LoDTensor>("Out");
+    int win_size = context.Attr<int>("win_size");
+    int pad_value = context.Attr<int>("pad_value");
+
+    auto in_dims = in->dims();
+    auto in_lod = in->lod();
+
+    PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
+                      "Only support one level sequence now.");
+    PADDLE_ENFORCE_EQ(
+        static_cast<uint64_t>(in_dims[0]), in_lod[0].back(),
+        "The actual input data's size mismatched with LoD information.");
+
+    /* Generate enumerate sequence set */
+    auto stream = context.cuda_device_context().stream();
+    auto in_len = in->numel();
+    auto in_data = in->data<T>();
+    auto out_data = out->mutable_data<T>(context.GetPlace());
+    // Calc output tensor
+    CalcOutPut<<<(in_len - 1) / PADDLE_CUDA_NUM_THREADS + 1,
+                 PADDLE_CUDA_NUM_THREADS, 0, stream>>>(
+        in_data, in_len, win_size, pad_value, out_data);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+REGISTER_OP_CUDA_KERNEL(
+    sequence_enumerate,
+    paddle::operators::SequenceEnumerateOpCUDAKernel<int32_t>,
+    paddle::operators::SequenceEnumerateOpCUDAKernel<int64_t>);

paddle/fluid/operators/sequence_enumerate_op.h

+//   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include "paddle/fluid/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+using LoDTensor = framework::LoDTensor;
+
+template <typename DeviceContext, typename T>
+class SequenceEnumerateKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* in = context.Input<LoDTensor>("X");
+    auto* out = context.Output<LoDTensor>("Out");
+    int win_size = context.Attr<int>("win_size");
+    int pad_value = context.Attr<int>("pad_value");
+
+    auto in_dims = in->dims();
+    auto in_lod = in->lod();
+
+    PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
+                      "Only support one level sequence now.");
+    PADDLE_ENFORCE_EQ(
+        static_cast<uint64_t>(in_dims[0]), in_lod[0].back(),
+        "The actual input data's size mismatched with LoD information.");
+
+    // Generate enumerate sequence set
+    auto seq_length = in_dims[0];
+    auto in_data = in->data<T>();
+    auto out_data = out->mutable_data<T>(context.GetPlace());
+    for (int idx = 0; idx < seq_length; ++idx) {
+      for (int word_idx = 0; word_idx < win_size; ++word_idx) {
+        int word_pos = idx + word_idx;
+        out_data[win_size * idx + word_idx] =
+            word_pos < seq_length ? in_data[word_pos] : pad_value;
+      }
+    }
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/fluid/tests/unittests/test_sequence_enumerate_op.py

+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+def sequence_enumerate(input_seq, lod0, win_size, pad_value):
+    out_seq = []
+    for idx in range(0, len(input_seq)):
+        single_seq = []
+        for word_idx in range(win_size):
+            word_pos = idx + word_idx
+            dat = input_seq[word_pos] if word_pos < len(input_seq) \
+                    else pad_value
+            single_seq.append(dat)
+        out_seq.append(single_seq)
+    return out_seq
+
+
+class TestSequenceEnumerateOp(OpTest):
+    def setUp(self):
+        self.op_type = "sequence_enumerate"
+        self.init_test_case()
+        self.inputs = {'X': (self.in_seq, self.lod)}
+        self.attrs = {'win_size': self.win_size, 'pad_value': self.pad_value}
+        self.outputs = {'Out': (self.out_seq, self.lod)}
+
+    def test_check_output(self):
+        self.check_output()
+
+    def init_test_case(self):
+        self.in_seq = np.random.randint(0, 10, (30, 1)).astype("int32")
+        self.lod = [[9, 4, 11, 6]]
+        self.win_size = 2
+        self.pad_value = 0
+        out_seq = sequence_enumerate(self.in_seq, self.lod[0], self.win_size,
+                                     self.pad_value)
+        self.out_seq = np.array(out_seq).astype("int32")
+
+
+class TesSequenceEnumerateOpInt64(TestSequenceEnumerateOp):
+    def init_test_case(self):
+        self.in_seq = np.random.randint(0, 10, (30, 1)).astype("int64")
+        self.lod = [[9, 4, 11, 6]]
+        self.win_size = 2
+        self.pad_value = 0
+        out_seq = sequence_enumerate(self.in_seq, self.lod[0], self.win_size,
+                                     self.pad_value)
+        self.out_seq = np.array(out_seq).astype("int64")
+
+
+class TestSequenceEnumerateOpMaxWinSize(TestSequenceEnumerateOp):
+    def init_test_case(self):
+        self.in_seq = np.random.randint(0, 10, (30, 1)).astype("int32")
+        self.lod = [[9, 4, 11, 6]]
+        self.win_size = 30
+        self.pad_value = 0
+        out_seq = sequence_enumerate(self.in_seq, self.lod[0], self.win_size,
+                                     self.pad_value)
+        self.out_seq = np.array(out_seq).astype("int32")
+
+
+if __name__ == "__main__":
+    unittest.main()