0c6fd1703e
Adds a basic training script for a simple audio model to our examples. See third_party/docs_src/tutorials/audio_recognition.md for full documentation PiperOrigin-RevId: 165025732
60 lines
2.2 KiB
C++
60 lines
2.2 KiB
C++
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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==============================================================================*/
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#include "tensorflow/examples/speech_commands/accuracy_utils.h"
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#include "tensorflow/core/framework/tensor_testutil.h"
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#include "tensorflow/core/lib/core/status_test_util.h"
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#include "tensorflow/core/lib/io/path.h"
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#include "tensorflow/core/lib/strings/str_util.h"
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#include "tensorflow/core/platform/env.h"
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#include "tensorflow/core/platform/test.h"
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namespace tensorflow {
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TEST(AccuracyUtilsTest, ReadGroundTruthFile) {
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string file_name = tensorflow::io::JoinPath(tensorflow::testing::TmpDir(),
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"ground_truth.txt");
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string file_data = "a,10\nb,12\n";
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TF_ASSERT_OK(WriteStringToFile(Env::Default(), file_name, file_data));
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std::vector<std::pair<string, int64>> ground_truth;
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TF_ASSERT_OK(ReadGroundTruthFile(file_name, &ground_truth));
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ASSERT_EQ(2, ground_truth.size());
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EXPECT_EQ("a", ground_truth[0].first);
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EXPECT_EQ(10, ground_truth[0].second);
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EXPECT_EQ("b", ground_truth[1].first);
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EXPECT_EQ(12, ground_truth[1].second);
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}
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TEST(AccuracyUtilsTest, CalculateAccuracyStats) {
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StreamingAccuracyStats stats;
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CalculateAccuracyStats({{"a", 1000}, {"b", 9000}},
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{{"a", 1200}, {"b", 5000}, {"a", 8700}}, 10000, 500,
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&stats);
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EXPECT_EQ(2, stats.how_many_ground_truth_words);
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EXPECT_EQ(2, stats.how_many_ground_truth_matched);
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EXPECT_EQ(1, stats.how_many_false_positives);
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EXPECT_EQ(1, stats.how_many_correct_words);
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EXPECT_EQ(1, stats.how_many_wrong_words);
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}
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TEST(AccuracyUtilsTest, PrintAccuracyStats) {
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StreamingAccuracyStats stats;
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PrintAccuracyStats(stats);
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}
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} // namespace tensorflow
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