Add speech endpointer model test for TF-lite.

PiperOrigin-RevId: 181644178
author: A. Unique TensorFlower <gardener@tensorflow.org> 2018-01-11 12:15:24 -0800
committer: TensorFlower Gardener <gardener@tensorflow.org> 2018-01-11 12:24:00 -0800
commit: 82b5d883774382f0e9cddc828f0d2f85af70f2ad (patch)
tree: 2000601905fd6ac2b8f03a37f2b6d7de247fc053 /tensorflow/contrib/lite/models
parent: 9698e9d86942e41915461f6649d209586b7e5b2d (diff)
3 files changed, 125 insertions, 0 deletions
diff --git a/tensorflow/contrib/lite/models/speech_endpointer_model_test.cc b/tensorflow/contrib/lite/models/speech_endpointer_model_test.cc
new file mode 100644
index 0000000000..f7e136113a
--- /dev/null
+++ b/tensorflow/contrib/lite/models/speech_endpointer_model_test.cc
@@ -0,0 +1,104 @@
+/* Copyright 2017 The TensorFlow 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.
+==============================================================================*/
+// Unit test for speech EndPointer model using TFLite Ops.
+
+#include <string.h>
+
+#include <memory>
+#include <string>
+
+#include "base/logging.h"
+#include "testing/base/public/googletest.h"
+#include <gtest/gtest.h>
+#include "absl/strings/str_cat.h"
+#include "tensorflow/contrib/lite/context.h"
+#include "tensorflow/contrib/lite/interpreter.h"
+#include "tensorflow/contrib/lite/kernels/register.h"
+#include "tensorflow/contrib/lite/model.h"
+#include "tensorflow/contrib/lite/models/test_utils.h"
+
+namespace tflite {
+namespace models {
+
+constexpr int kModelInputTensor = 0;
+constexpr int kLstmLayer1OutputStateTensor = 28;
+constexpr int kLstmLayer1CellStateTensor = 29;
+constexpr int kLstmLayer2OutputStateTensor = 49;
+constexpr int kLstmLayer2CellStateTensor = 50;
+constexpr int kModelOutputTensor = 58;
+
+TEST(SpeechEndpointer, EndpointerTest) {
+  // Read the model.
+  string tflite_file_path =
+      StrCat(TestDataPath(), "/", "speech_endpointer_model.tflite");
+  auto model = FlatBufferModel::BuildFromFile(tflite_file_path.c_str());
+  CHECK(model) << "Failed to read model from file " << tflite_file_path;
+
+  // Initialize the interpreter.
+  ops::builtin::BuiltinOpResolver builtins;
+  std::unique_ptr<Interpreter> interpreter;
+  InterpreterBuilder(*model, builtins)(&interpreter);
+  CHECK(interpreter != nullptr);
+  interpreter->AllocateTensors();
+
+  // Load the input frames.
+  Frames input_frames;
+  const string input_file_path =
+      StrCat(TestDataPath(), "/", "speech_endpointer_model_in.csv");
+  ReadFrames(input_file_path, &input_frames);
+
+  // Load the golden output results.
+  Frames output_frames;
+  const string output_file_path =
+      StrCat(TestDataPath(), "/", "speech_endpointer_model_out.csv");
+  ReadFrames(output_file_path, &output_frames);
+
+  const int speech_batch_size =
+      interpreter->tensor(kModelInputTensor)->dims->data[0];
+  const int speech_input_size =
+      interpreter->tensor(kModelInputTensor)->dims->data[1];
+  const int speech_output_size =
+      interpreter->tensor(kModelOutputTensor)->dims->data[1];
+
+  float* input_ptr = interpreter->tensor(kModelInputTensor)->data.f;
+  float* output_ptr = interpreter->tensor(kModelOutputTensor)->data.f;
+
+  // Clear the LSTM state for layers.
+  memset(interpreter->tensor(kLstmLayer1OutputStateTensor)->data.raw, 0,
+         interpreter->tensor(kLstmLayer1OutputStateTensor)->bytes);
+  memset(interpreter->tensor(kLstmLayer1CellStateTensor)->data.raw, 0,
+         interpreter->tensor(kLstmLayer1CellStateTensor)->bytes);
+  memset(interpreter->tensor(kLstmLayer2OutputStateTensor)->data.raw, 0,
+         interpreter->tensor(kLstmLayer2OutputStateTensor)->bytes);
+  memset(interpreter->tensor(kLstmLayer2CellStateTensor)->data.raw, 0,
+         interpreter->tensor(kLstmLayer2CellStateTensor)->bytes);
+
+  for (int i = 0; i < input_frames.size(); i++) {
+    // Feed the input to model.
+    int frame_ptr = 0;
+    for (int k = 0; k < speech_input_size * speech_batch_size; k++) {
+      input_ptr[k] = input_frames[i][frame_ptr++];
+    }
+    // Run the model.
+    interpreter->Invoke();
+    // Validate the output.
+    for (int k = 0; k < speech_output_size; k++) {
+      ASSERT_NEAR(output_ptr[k], output_frames[i][k], 1e-5);
+    }
+  }
+}
+
+}  // namespace models
+}  // namespace tflite
diff --git a/tensorflow/contrib/lite/models/testdata/g3doc/README.md b/tensorflow/contrib/lite/models/testdata/g3doc/README.md
index 46b24248f0..8a023ea869 100644
--- a/tensorflow/contrib/lite/models/testdata/g3doc/README.md
+++ b/tensorflow/contrib/lite/models/testdata/g3doc/README.md
@@ -75,6 +75,20 @@ The corresponding parameters as shown in the figure.
 
 ![asr_lm_model](asr_lm.svg "ASR LM model")
 
+### Endpointer Model
+
+The endpointer model is the neural network model for predicting end of speech
+in an utterance. More precisely, it generates posterior probabilities of various
+events that allow detection of speech start and end events.
+It has an input size of 40 (float) which are speech frontend features
+(log-mel filterbanks), and an output size of four corresponding to:
+speech, intermediate non-speech, initial non-speech, and final non-speech.
+The model consists of a convolutional layer, followed by a fully-connected
+layer, two LSTM layers, and two additional fully-connected layers.
+The corresponding parameters as shown in the figure.
+![endpointer_model](endpointer.svg "Endpointer model")
+
+
 ## Speech models test input/output generation
 
 As mentioned above the input to models are generated from a pre-processing
@@ -115,6 +129,9 @@ test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/li
 [ASR AM model
 test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_terse_am_model_test.cc)
 
+[Endpointer model
+test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_endpointer_model_test.cc)
+
 ## Android Support
 The models have been tested on Android phones, using the following tests:
 
diff --git a/tensorflow/contrib/lite/models/testdata/g3doc/endpointer.svg b/tensorflow/contrib/lite/models/testdata/g3doc/endpointer.svg
new file mode 100644
index 0000000000..6033bdc529
--- /dev/null
+++ b/tensorflow/contrib/lite/models/testdata/g3doc/endpointer.svg
@@ -0,0 +1,4 @@
+<?xml version="1.0" standalone="yes"?>
+
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author	A. Unique TensorFlower <gardener@tensorflow.org>	2018-01-11 12:15:24 -0800
committer	TensorFlower Gardener <gardener@tensorflow.org>	2018-01-11 12:24:00 -0800
commit	82b5d883774382f0e9cddc828f0d2f85af70f2ad (patch)
tree	2000601905fd6ac2b8f03a37f2b6d7de247fc053 /tensorflow/contrib/lite/models
parent	9698e9d86942e41915461f6649d209586b7e5b2d (diff)