Merge pull request #7527 from wanghaoshuang/ctc_greedy_decode

Add CTC align op

Author: wanghaoshuang

paddle/operators/ctc_align_op.cc

@@ -0,0 +1,93 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/operators/ctc_align_op.h"
+
+namespace paddle {
+namespace operators {
+
+class CTCAlignOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("Input"),
+                   "Input of CTCAlignOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("Output"),
+                   "Output of CTCAlignOp should not be null.");
+
+    auto input_dims = ctx->GetInputDim("Input");
+
+    // TODO(wanghaoshuang): it is tricky to set the wrong dimension here.
+    ctx->SetOutputDim("Output", input_dims);
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    return framework::OpKernelType(
+        framework::ToDataType(ctx.Input<Tensor>("Input")->type()),
+        ctx.device_context());
+  }
+};
+
+class CTCAlignOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  CTCAlignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("Input",
+             "(LodTensor, default: LoDTensor<int>), Its shape is "
+             "[Lp, 1], where Lp is the sum of all input sequences' length.");
+    AddOutput("Output", "(Tensor, default: Tensor<int>), The align result.");
+    AddAttr<int>("blank",
+                 "(int, default: 0), the blank label setted in Connectionist "
+                 "Temporal Classification (CTC) op.")
+        .SetDefault(0);
+    AddAttr<bool>("merge_repeated",
+                  "(bool, default: true), whether to "
+                  "merge repeated elements between two blanks. ")
+        .SetDefault(true);
+    AddComment(R"DOC(
+CTCAlign op is used to merge repeated elements between two blanks
+and then delete all blanks in sequence.
+
+Given:
+    Input.data = [0, 1, 2, 2, 0, 4, 0, 4, 5, 0, 6,
+                  6, 0, 0, 7, 7, 7, 0]
+    Input.dims = {18, 1}
+    Input.LoD = [[0, 11, 18]]
+
+And:
+    blank = 0
+    merge_repeated = True
+
+Then:
+    Output.data = [1, 2, 4, 4, 5, 6,
+                   6, 7]
+    Output.dims = {8, 1}
+    Output.LoD = [[0, 6, 8]]
+
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OPERATOR(ctc_align, ops::CTCAlignOp, ops::CTCAlignOpMaker,
+                  paddle::framework::EmptyGradOpMaker);
+REGISTER_OP_CPU_KERNEL(
+    ctc_align, ops::CTCAlignKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::CTCAlignKernel<paddle::platform::CPUDeviceContext, int64_t>);

paddle/operators/ctc_align_op.cu

@@ -0,0 +1,91 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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 <stdio.h>
+#include <thrust/device_vector.h>
+#include <thrust/host_vector.h>
+#include "paddle/operators/ctc_align_op.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+__global__ void MergeAndDelCudaKernel(const int64_t num_token, const T* tokens,
+                                      const size_t num_seq, size_t* lod0,
+                                      const int blank, const int merge_repeated,
+                                      size_t* out_lod0, T* output) {
+  int ouput_idx = 0;
+  out_lod0[0] = 0;
+
+  for (int i = 0; i < num_seq; ++i) {
+    T pre_token = -1;
+    for (int j = lod0[i]; j < lod0[i + 1]; ++j) {
+      if (tokens[j] != blank && !(merge_repeated && tokens[j] == pre_token)) {
+        output[ouput_idx] = tokens[j];
+        ++ouput_idx;
+      }
+      pre_token = tokens[j];
+    }
+    out_lod0[i + 1] = ouput_idx;
+  }
+}
+
+template <typename T>
+class CTCAlignOpCUDAKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
+                   "It must use CUDAPlace.");
+    const size_t level = 0;
+    auto* input = ctx.Input<LoDTensor>("Input");
+    auto* output = ctx.Output<LoDTensor>("Output");
+    auto input_lod = framework::ToAbsOffset(input->lod());
+
+    const T* tokens = input->data<T>();
+    const int64_t num_tokens = input->dims()[0];
+    const size_t num_seq = input_lod[level].size() - 1;
+
+    const int blank = ctx.Attr<int>("blank");
+    const int merge_repeated =
+        static_cast<int>(ctx.Attr<bool>("merge_repeated"));
+
+    // prepare a lod to record lod information while merging elements
+    thrust::device_vector<size_t> dev_out_lod0(input_lod[level].size());
+    size_t* dev_out_lod0_ptr = thrust::raw_pointer_cast(dev_out_lod0.data());
+
+    // merge elements and delete blank
+    T* output_data = output->mutable_data<T>({num_tokens, 1}, ctx.GetPlace());
+
+    auto stream = ctx.cuda_device_context().stream();
+    MergeAndDelCudaKernel<T><<<1, 1, 0, stream>>>(
+        num_tokens, tokens, num_seq, input_lod[level].data(), blank,
+        merge_repeated, dev_out_lod0_ptr, output_data);
+
+    // set output lod
+    thrust::host_vector<size_t> host_out_lod0(dev_out_lod0.begin(),
+                                              dev_out_lod0.end());
+    framework::LoD out_lod;
+    out_lod.push_back(host_out_lod0);
+    output->set_lod(out_lod);
+
+    // resize output dims
+    output->Resize({static_cast<int64_t>(host_out_lod0.back()), 1});
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+REGISTER_OP_CUDA_KERNEL(ctc_align, paddle::operators::CTCAlignOpCUDAKernel<int>,
+                        paddle::operators::CTCAlignOpCUDAKernel<int64_t>);

paddle/operators/ctc_align_op.h

@@ -0,0 +1,75 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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 <string.h>
+#include "paddle/framework/op_registry.h"
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+using LoDTensor = framework::LoDTensor;
+
+template <typename DeviceContext, typename T>
+class CTCAlignKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* input = ctx.Input<LoDTensor>("Input");
+    auto* output = ctx.Output<LoDTensor>("Output");
+    const size_t level = 0;
+    auto input_lod = framework::ToAbsOffset(input->lod());
+
+    // check input dims and lod
+    auto input_dims = input->dims();
+    PADDLE_ENFORCE_EQ(input_dims[0],
+                      static_cast<int64_t>(input_lod[level].back()),
+                      "The first dimension of Input(Input) should be equal to "
+                      "the sum of all sequences' lengths.");
+
+    const size_t num_sequences = input_lod[level].size() - 1;
+    size_t blank = static_cast<size_t>(ctx.Attr<int>("blank"));
+    bool merge_repeated = ctx.Attr<bool>("merge_repeated");
+
+    // merge repeated tokens and delete blank
+    T* output_data = output->mutable_data<T>(ctx.GetPlace());
+    size_t output_idx = 0;
+    std::vector<size_t> output_lod0(1, 0);
+    const T* input_data = input->data<T>();
+    for (size_t seq_idx = 0; seq_idx < num_sequences; ++seq_idx) {
+      T prev_token = -1;
+      for (size_t i = input_lod[level][seq_idx];
+           i < input_lod[level][seq_idx + 1]; ++i) {
+        if (input_data[i] != blank &&
+            !(merge_repeated && input_data[i] == prev_token)) {
+          output_data[output_idx] = input_data[i];
+          ++output_idx;
+        }
+        prev_token = input_data[i];
+      }
+      output_lod0.push_back(output_idx);
+    }
+
+    // set output lod
+    framework::LoD output_lod;
+    output_lod.push_back(output_lod0);
+    output->set_lod(output_lod);
+
+    // resize output dims
+    output->Resize({static_cast<int64_t>(output_lod0.back()), 1});
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/operators/sequence_expand_op.cc

@@ -58,7 +58,7 @@ This operator expands input(X) according to LOD of input(Y).
 Following are cases to better explain how this works:
 Case 1:
 
-Given 2-level a LoDTensor input(X)
+Given a 2-level LoDTensor input(X)
     X.lod = [[0,       2, 3],
              [0, 1,    3, 4]]
     X.data = [a, b, c, d]
@@ -75,9 +75,8 @@ then we get 2-level LoDTensor
 
 Case 2:
 
-Given a 0-level LoDTensor input(X)
+Given a common Tensor input(X)
     X.data = [a, b, c]
-    X.lod = NULL
     X.dims = [3, 1]
 and input(Y)
     Y.lod = [[0, 2, 3, 6]]
@@ -89,9 +88,8 @@ then we get 1-level LoDTensor
 
 Case 3:
 
-Given a 0-level LoDTensor input(X)
+Given a common Tensor input(X)
     X.data = [[a, b], [c, d], [e, f]]
-    X.lod = NULL
     X.dims = [3, 2]
 and input(Y)
     Y.lod = [[0, 2, 3, 6]]

python/paddle/v2/fluid/tests/test_ctc_align.py

@@ -0,0 +1,76 @@
+#  Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
+#
+#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.
+
+import sys
+import unittest
+import numpy as np
+from op_test import OpTest
+from test_softmax_op import stable_softmax
+
+
+def CTCAlign(input, lod, blank, merge_repeated):
+    lod0 = lod[0]
+    result = []
+    for i in range(len(lod0) - 1):
+        prev_token = -1
+        for j in range(lod0[i], lod0[i + 1]):
+            token = input[j][0]
+            if (token != blank) and not (merge_repeated and
+                                         token == prev_token):
+                result.append(token)
+            prev_token = token
+    result = np.array(result).reshape([len(result), 1]).astype("int32")
+    return result
+
+
+class TestCTCAlignOp(OpTest):
+    def config(self):
+        self.op_type = "ctc_align"
+        self.input_lod = [[0, 11, 18]]
+        self.blank = 0
+        self.merge_repeated = False
+        self.input = np.array(
+            [0, 1, 2, 2, 0, 4, 0, 4, 5, 0, 6, 6, 0, 0, 7, 7, 7, 0]).reshape(
+                [18, 1]).astype("int32")
+
+    def setUp(self):
+        self.config()
+        output = CTCAlign(self.input, self.input_lod, self.blank,
+                          self.merge_repeated)
+
+        self.inputs = {"Input": (self.input, self.input_lod), }
+        self.outputs = {"Output": output}
+        self.attrs = {
+            "blank": self.blank,
+            "merge_repeated": self.merge_repeated
+        }
+
+    def test_check_output(self):
+        self.check_output()
+        pass
+
+
+class TestCTCAlignOpCase1(TestCTCAlignOp):
+    def config(self):
+        self.op_type = "ctc_align"
+        self.input_lod = [[0, 11, 19]]
+        self.blank = 0
+        self.merge_repeated = True
+        self.input = np.array(
+            [0, 1, 2, 2, 0, 4, 0, 4, 5, 0, 6, 6, 0, 0, 7, 7, 7, 0, 0]).reshape(
+                [19, 1]).astype("int32")
+
+
+if __name__ == "__main__":
+    unittest.main()