| /external/webrtc/webrtc/modules/audio_coding/neteq/tools/ |
| audio_sink.h | 28 // Writes |num_samples| from |audio| to the AudioSink. Returns true if
30 virtual bool WriteArray(const int16_t* audio, size_t num_samples) = 0;
50 bool WriteArray(const int16_t* audio, size_t num_samples) override {
51 return left_sink_->WriteArray(audio, num_samples) &&
52 right_sink_->WriteArray(audio, num_samples);
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| output_wav_file.h | 30 bool WriteArray(const int16_t* audio, size_t num_samples) override {
31 wav_writer_.WriteSamples(audio, num_samples);
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| output_audio_file.h | 37 bool WriteArray(const int16_t* audio, size_t num_samples) override {
39 return fwrite(audio, sizeof(*audio), num_samples, out_file_) == num_samples;
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| audio_checksum.h | 29 bool WriteArray(const int16_t* audio, size_t num_samples) override {
36 checksum_.Update(audio, num_samples * sizeof(*audio));
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| /external/webrtc/webrtc/modules/video_coding/utility/ |
| moving_average.h | 24 bool GetAverage(size_t num_samples, T* average);
44 bool MovingAverage<T>::GetAverage(size_t num_samples, T* avg) {
45 if (num_samples > samples_.size())
49 while (num_samples < samples_.size()) {
54 *avg = sum_ / static_cast<T>(num_samples);
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| /external/webrtc/webrtc/common_audio/ |
| wav_header.h | 39 size_t num_samples);
50 size_t num_samples);
60 size_t* num_samples);
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| wav_file.h | 31 virtual size_t num_samples() const = 0;
50 void WriteSamples(const float* samples, size_t num_samples);
51 void WriteSamples(const int16_t* samples, size_t num_samples);
55 size_t num_samples() const override { return num_samples_; }
78 size_t ReadSamples(size_t num_samples, float* samples);
79 size_t ReadSamples(size_t num_samples, int16_t* samples);
83 size_t num_samples() const override { return num_samples_; }
109 size_t num_samples);
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| wav_file.cc | 45 << (1.f * num_samples()) / (num_channels() * sample_rate()) << " s";
67 size_t WavReader::ReadSamples(size_t num_samples, int16_t* samples) {
72 num_samples = std::min(num_samples, num_samples_remaining_);
74 fread(samples, sizeof(*samples), num_samples, file_handle_);
76 RTC_CHECK(read == num_samples || feof(file_handle_));
82 size_t WavReader::ReadSamples(size_t num_samples, float* samples) {
85 for (size_t i = 0; i < num_samples; i += kChunksize) {
87 size_t chunk = std::min(kChunksize, num_samples - i);
121 void WavWriter::WriteSamples(const int16_t* samples, size_t num_samples) {
[all...] |
| /external/mesa3d/src/mesa/drivers/dri/i965/ |
| gen8_multisample_state.c | 34 gen8_emit_3dstate_multisample(struct brw_context *brw, unsigned num_samples)
36 assert(num_samples <= 16);
38 unsigned log2_samples = ffs(MAX2(num_samples, 1)) - 1;
77 gen8_emit_3dstate_multisample(brw, brw->num_samples);
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| brw_formatquery.c | 99 size_t num_samples; local
102 num_samples = brw_query_samples_for_format(ctx, target, internalFormat,
104 params[0] = (GLint) num_samples;
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| gen6_multisample_state.c | 127 unsigned num_samples)
135 switch (num_samples) {
150 unreachable("Unrecognized num_samples in gen6_emit_3dstate_multisample");
172 unsigned num_samples = brw->num_samples; local
184 if (num_samples > 1) {
185 int coverage_int = (int) (num_samples * coverage + 0.5f);
188 coverage_bits ^= (1 << num_samples) - 1;
211 gen6_emit_3dstate_multisample(brw, brw->num_samples);
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| /external/webrtc/webrtc/common_audio/vad/mock/ |
| mock_vad.h | 27 size_t num_samples,
|
| /external/libxaac/decoder/ |
| ixheaacd_mps_hybfilter.h | 28 WORD32 num_bands, WORD32 num_samples,
33 WORD32 num_bands, WORD32 num_samples,
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| /external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
| dataset.py | 41 def __init__(self, data_sources, reader, decoder, num_samples,
50 num_samples: The number of samples in the dataset.
58 kwargs['num_samples'] = num_samples
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| data_provider.py | 51 def __init__(self, items_to_tensors, num_samples):
56 num_samples: the number of samples in the dataset being provided.
59 self._num_samples = num_samples
90 def num_samples(self): member in class:DataProvider
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| /external/webrtc/webrtc/modules/audio_coding/neteq/ |
| statistics_calculator.h | 40 // Reports that |num_samples| samples were produced through expansion, and
42 void ExpandedVoiceSamples(size_t num_samples);
44 // Reports that |num_samples| samples were produced through expansion, and
46 void ExpandedNoiseSamples(size_t num_samples);
48 // Reports that |num_samples| samples were produced through preemptive
50 void PreemptiveExpandedSamples(size_t num_samples);
52 // Reports that |num_samples| samples were removed through accelerate.
53 void AcceleratedSamples(size_t num_samples);
55 // Reports that |num_samples| zeros were inserted into the output.
56 void AddZeros(size_t num_samples);
[all...] |
| statistics_calculator.cc | 143 void StatisticsCalculator::ExpandedVoiceSamples(size_t num_samples) {
144 expanded_speech_samples_ += num_samples;
147 void StatisticsCalculator::ExpandedNoiseSamples(size_t num_samples) {
148 expanded_noise_samples_ += num_samples;
151 void StatisticsCalculator::PreemptiveExpandedSamples(size_t num_samples) {
152 preemptive_samples_ += num_samples;
155 void StatisticsCalculator::AcceleratedSamples(size_t num_samples) {
156 accelerate_samples_ += num_samples;
159 void StatisticsCalculator::AddZeros(size_t num_samples) {
160 added_zero_samples_ += num_samples;
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| local_test.py | 31 num_samples = 2
51 input_shape=(num_samples, num_steps, input_dim))
54 num_samples = 2
69 layer.build((num_samples, num_steps, input_dim))
72 keras.backend.variable(np.ones((num_samples, num_steps, input_dim))))
85 layer.build((num_samples, num_steps, input_dim))
90 num_samples = 8
114 input_shape=(num_samples, num_row, num_col, stack_size))
117 num_samples = 8
131 input_shape=(num_samples, num_row, num_col, stack_size)
[all...] |
| gru_test.py | 31 num_samples = 2
40 input_shape=(num_samples, timesteps, embedding_dim))
43 num_samples = 2
52 x = np.random.random((num_samples, timesteps, embedding_dim))
53 y = np.random.random((num_samples, units))
57 num_samples = 2
67 input_shape=(num_samples, timesteps, embedding_dim))
70 num_samples = 2
80 input_shape=(num_samples, timesteps, embedding_dim))
83 num_samples =
[all...] |
| simplernn_test.py | 31 num_samples = 2
40 input_shape=(num_samples, timesteps, embedding_dim))
43 num_samples = 2
52 x = np.random.random((num_samples, timesteps, embedding_dim))
53 y = np.random.random((num_samples, units))
57 num_samples = 2
67 input_shape=(num_samples, timesteps, embedding_dim))
70 num_samples = 2
80 input_shape=(num_samples, timesteps, embedding_dim))
83 num_samples =
[all...] |
| lstm_test.py | 31 num_samples = 2
40 input_shape=(num_samples, timesteps, embedding_dim))
44 num_samples = 2
59 num_samples = 2
68 x = np.random.random((num_samples, timesteps, embedding_dim))
69 y = np.random.random((num_samples, units))
73 num_samples = 2
83 input_shape=(num_samples, timesteps, embedding_dim))
86 num_samples = 2
96 input_shape=(num_samples, timesteps, embedding_dim)
[all...] |
| /external/opencv/ml/src/ |
| mltestset.cpp | 60 int num_samples,
87 if( num_samples < 1 )
88 CV_ERROR( CV_StsBadArg, "num_samples parameter must be positive" );
105 CV_CALL( *samples = cvCreateMat( num_samples, num_features, CV_32FC1 ) );
106 CV_CALL( *responses = cvCreateMat( 1, num_samples, CV_32SC1 ) );
133 num_classes = MIN( num_samples, num_classes );
136 for( i = 0, cur_class = 0; i < num_samples; ++cur_class )
141 last_idx = num_samples * (cur_class + 1) / num_classes - 1;
145 for( ; elem.d <= max_dst && i < num_samples; ++i )
148 if( i < num_samples - 1
[all...] |
| /system/extras/memtrack/ |
| memtrack.h | 57 size_t num_samples; member in struct:__anon2993
119 size_t num_samples) {
120 *running_avg = (*running_avg/(num_samples+1))*num_samples
121 + (double)cur_avg/(num_samples+1);
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| input_pipeline_test.py | 50 def _make_csv_time_series(num_features, num_samples, test_tmpdir):
54 for i in range(num_samples)],
59 def _make_tfexample_series(num_features, num_samples, test_tmpdir):
62 for i in range(num_samples):
74 def _make_numpy_time_series(num_features, num_samples):
75 times = numpy.arange(num_samples)
124 filename = _make_csv_time_series(num_features=1, num_samples=50,
131 num_features=1, num_samples=50,
143 data = _make_numpy_time_series(num_features=1, num_samples=50)
148 filename = _make_csv_time_series(num_features=1, num_samples=50
[all...] |
| /external/brotli/research/ |
| deorummolae.h | 18 * @param num_samples number of samples
24 size_t num_samples, const size_t* sample_sizes,
|
