/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
D | 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 …]
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D | 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 = 2 [all …]
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D | 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 = 2 [all …]
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D | 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 …]
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D | convolutional_test.py | 33 num_samples = 2 44 input_shape=(num_samples, length, stack_size)) 103 num_samples = 2 115 input_shape=(num_samples, num_row, num_col, stack_size)) 177 num_samples = 2 189 input_shape=(num_samples, num_row, num_col, stack_size)) 241 num_samples = 2 254 input_shape=(num_samples, depth, num_row, num_col, stack_size)) 306 num_samples = 2 317 input_shape=(num_samples, length, stack_size)) [all …]
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D | convolutional_recurrent_test.py | 34 num_samples = 1 41 inputs = np.random.rand(num_samples, sequence_len, 45 inputs = np.random.rand(num_samples, sequence_len, 85 num_samples = 1 90 inputs = np.random.rand(num_samples, sequence_len, 137 num_samples = 1 142 inputs = np.random.rand(num_samples, sequence_len,
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/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
D | input_pipeline_test.py | 50 def _make_csv_time_series(num_features, num_samples, test_tmpdir): argument 54 for i in range(num_samples)], 59 def _make_tfexample_series(num_features, num_samples, test_tmpdir): argument 62 for i in range(num_samples): 74 def _make_numpy_time_series(num_features, num_samples): argument 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 …]
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/external/tensorflow/tensorflow/python/keras/_impl/keras/ |
D | model_subclassing_test.py | 174 num_samples = 100 185 x = np.ones((num_samples, input_dim)) 186 y = np.zeros((num_samples, num_classes)) 194 num_samples = 1000 205 x1 = np.ones((num_samples, input_dim)) 206 x2 = np.ones((num_samples, input_dim)) 207 y1 = np.zeros((num_samples, num_classes[0])) 208 y2 = np.zeros((num_samples, num_classes[1])) 216 num_samples = 10 225 x = array_ops.ones((num_samples, input_dim)) [all …]
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/external/webrtc/webrtc/common_audio/ |
D | wav_file.cc | 45 << (1.f * num_samples()) / (num_channels() * sample_rate()) << " s"; in FormatAsString() 67 size_t WavReader::ReadSamples(size_t num_samples, int16_t* samples) { in ReadSamples() argument 72 num_samples = std::min(num_samples, num_samples_remaining_); in ReadSamples() 74 fread(samples, sizeof(*samples), num_samples, file_handle_); in ReadSamples() 76 RTC_CHECK(read == num_samples || feof(file_handle_)); in ReadSamples() 82 size_t WavReader::ReadSamples(size_t num_samples, float* samples) { in ReadSamples() argument 85 for (size_t i = 0; i < num_samples; i += kChunksize) { in ReadSamples() 87 size_t chunk = std::min(kChunksize, num_samples - i); in ReadSamples() 121 void WavWriter::WriteSamples(const int16_t* samples, size_t num_samples) { in WriteSamples() argument 126 fwrite(samples, sizeof(*samples), num_samples, file_handle_); in WriteSamples() [all …]
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D | wav_header_unittest.cc | 98 size_t num_samples = 0; in TEST() local 123 &bytes_per_sample, &num_samples)); in TEST() 144 &bytes_per_sample, &num_samples)); in TEST() 165 &bytes_per_sample, &num_samples)); in TEST() 187 &bytes_per_sample, &num_samples)); in TEST() 210 &bytes_per_sample, &num_samples)); in TEST() 229 &bytes_per_sample, &num_samples)); in TEST() 241 &bytes_per_sample, &num_samples)); in TEST() 275 size_t num_samples = 0; in TEST() local 279 &bytes_per_sample, &num_samples)); in TEST() [all …]
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D | 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_; } in num_samples() function 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_; } in num_samples() function 109 size_t num_samples);
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D | wav_header.cc | 66 size_t num_samples) { in CheckWavParameters() argument 104 if (num_samples > max_samples) in CheckWavParameters() 108 if (num_samples % num_channels != 0) in CheckWavParameters() 153 size_t num_samples) { in WriteWavHeader() argument 155 bytes_per_sample, num_samples)); in WriteWavHeader() 158 const size_t bytes_in_payload = bytes_per_sample * num_samples; in WriteWavHeader() 188 size_t* num_samples) { in ReadWavHeader() argument 217 *num_samples = bytes_in_payload / *bytes_per_sample; in ReadWavHeader() 239 *bytes_per_sample, *num_samples); in ReadWavHeader()
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/external/tensorflow/tensorflow/python/kernel_tests/random/ |
D | multinomial_op_test.py | 40 def composed_sampler(logits, num_samples): argument 43 tensor_shape.TensorShape([num_samples]))) 64 num_samples = 1000 66 logits, num_samples, output_dtype=output_dtype)) 67 self.assertAllEqual([[1] * num_samples, [2] * num_samples], samples) 110 num_samples = 21000 120 composed_freqs = self._do_sampling(logits, num_samples, composed_sampler) 121 native_freqs = self._do_sampling(logits, num_samples, native_sampler) 136 def _make_ops(self, num_samples, seed=None): argument 140 sample_op1 = random_ops.multinomial(logits, num_samples, seed) [all …]
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/external/webrtc/webrtc/modules/audio_coding/neteq/ |
D | statistics_calculator.cc | 143 void StatisticsCalculator::ExpandedVoiceSamples(size_t num_samples) { in ExpandedVoiceSamples() argument 144 expanded_speech_samples_ += num_samples; in ExpandedVoiceSamples() 147 void StatisticsCalculator::ExpandedNoiseSamples(size_t num_samples) { in ExpandedNoiseSamples() argument 148 expanded_noise_samples_ += num_samples; in ExpandedNoiseSamples() 151 void StatisticsCalculator::PreemptiveExpandedSamples(size_t num_samples) { in PreemptiveExpandedSamples() argument 152 preemptive_samples_ += num_samples; in PreemptiveExpandedSamples() 155 void StatisticsCalculator::AcceleratedSamples(size_t num_samples) { in AcceleratedSamples() argument 156 accelerate_samples_ += num_samples; in AcceleratedSamples() 159 void StatisticsCalculator::AddZeros(size_t num_samples) { in AddZeros() argument 160 added_zero_samples_ += num_samples; in AddZeros() [all …]
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D | statistics_calculator.h | 42 void ExpandedVoiceSamples(size_t num_samples); 46 void ExpandedNoiseSamples(size_t num_samples); 50 void PreemptiveExpandedSamples(size_t num_samples); 53 void AcceleratedSamples(size_t num_samples); 56 void AddZeros(size_t num_samples); 62 void LostSamples(size_t num_samples); 67 void IncreaseCounter(size_t num_samples, int fs_hz); 73 void SecondaryDecodedSamples(int num_samples);
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/external/libxaac/decoder/ |
D | ixheaacd_mps_hybrid_filt.c | 50 WORD32 num_samples, WORD32 *filt_coeff) in ixheaacd_mps_hyb_filt_type1() argument 63 for (i = 0; i < num_samples; i++) { in ixheaacd_mps_hyb_filt_type1() 110 WORD32 num_samples, WORD32 *filt_coeff) in ixheaacd_mps_hyb_filt_type2() argument 123 for (i = 0; i < num_samples; i++) { in ixheaacd_mps_hyb_filt_type2() 175 WORD32 num_bands, WORD32 num_samples, in ixheaacd_mps_qmf_hybrid_analysis() argument 184 lf_samples_shift = BUFFER_LEN_LF_MPS - num_samples; in ixheaacd_mps_qmf_hybrid_analysis() 185 hf_samples_shift = BUFFER_LEN_HF_MPS - num_samples; in ixheaacd_mps_qmf_hybrid_analysis() 191 handle->lf_buffer[k][n].re = handle->lf_buffer[k][n + num_samples].re; in ixheaacd_mps_qmf_hybrid_analysis() 192 handle->lf_buffer[k][n].im = handle->lf_buffer[k][n + num_samples].im; in ixheaacd_mps_qmf_hybrid_analysis() 197 for (n = 0; n < num_samples; n++) { in ixheaacd_mps_qmf_hybrid_analysis() [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | multinomial_op.cc | 50 int num_classes, int num_samples, 62 int num_classes, int num_samples, in operator ()() 71 auto DoWork = [ctx, num_samples, num_classes, &gen, &output, &logits]( in operator ()() 79 gen_copy.Skip(start_row * (num_samples + 3) / 4); in operator ()() 113 for (int64 j = 0; j < num_samples; ++j) { in operator ()() 122 50 * (num_samples * std::log(num_classes) / std::log(2) + num_classes); in operator ()() 150 const int num_samples = num_samples_t.scalar<int>()(); in Compute() local 151 OP_REQUIRES(ctx, num_samples >= 0, in Compute() 153 "num_samples should be nonnegative, got ", num_samples)); in Compute() 170 ctx, ctx->allocate_output(0, TensorShape({batch_size, num_samples}), in Compute() [all …]
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D | random_poisson_op.cc | 73 int num_rate, int num_samples, 80 int num_rate, int num_samples, in operator ()() 105 auto DoWork = [num_samples, num_rate, &rng, samples_flat, rate_flat]( in operator ()() 115 const int64 rate_idx = output_idx / num_samples; in operator ()() 134 for (int64 sample_idx = output_idx % num_samples; in operator ()() 135 sample_idx < num_samples && output_idx < limit_output; in operator ()() 196 for (int64 sample_idx = output_idx % num_samples; in operator ()() 197 sample_idx < num_samples && output_idx < limit_output; in operator ()() 269 num_rate * num_samples, kElementCost, DoWork); in operator ()() 294 const int64 num_samples = samples_shape.num_elements(); in Compute() local [all …]
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D | multinomial_op_gpu.cu.cc | 42 const int32 num_samples, const float* scores, in MultinomialKernel() argument 61 int num_classes, int num_samples, in operator ()() 73 bsc.set(1, num_samples); in operator ()() 81 oso.set(1, num_samples); in operator ()() 84 Eigen::array<int, 3> bsc{batch_size, num_samples, num_classes}; in operator ()() 86 Eigen::array<int, 3> oso{1, num_samples, 1}; in operator ()() 106 const int32 work_items = batch_size * num_samples * num_classes; in operator ()() 110 num_samples, scores.data(), maxima.data(), in operator ()()
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/external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
D | test_util.py | 42 num_samples=int(1e5), num_threshold=int(1e3), seed=42, argument 84 y = dist.sample(num_samples, seed=seed) 85 y = array_ops.reshape(y, shape=[num_samples, -1]) 100 self.assertAllClose(probs_, counts_ / num_samples, 105 num_samples=int(1e5), seed=24, argument 128 x = math_ops.to_float(dist.sample(num_samples, seed=seed)) 200 num_samples=int(1e5), argument 290 def monte_carlo_hypersphere_volume(dist, num_samples, radius, center): argument 292 x = dist.sample(num_samples, seed=seed) 301 … values=[num_samples, radius, center] + dist._graph_parents): # pylint: disable=protected-access [all …]
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/external/mesa3d/src/mesa/drivers/dri/i965/ |
D | gen6_multisample_state.c | 127 unsigned num_samples) in gen6_emit_3dstate_multisample() argument 135 switch (num_samples) { in gen6_emit_3dstate_multisample() 172 unsigned num_samples = brw->num_samples; in gen6_determine_sample_mask() local 184 if (num_samples > 1) { in gen6_determine_sample_mask() 185 int coverage_int = (int) (num_samples * coverage + 0.5f); in gen6_determine_sample_mask() 188 coverage_bits ^= (1 << num_samples) - 1; in gen6_determine_sample_mask() 211 gen6_emit_3dstate_multisample(brw, brw->num_samples); in upload_multisample_state()
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/external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
D | halton_sequence_test.py | 45 sample = halton.sample(2, num_samples=5) 52 sample_direct = halton.sample(dim, num_samples=10) 60 sample_float32 = halton.sample(dim, num_samples=10, dtype=dtypes.float32) 61 sample_float64 = halton.sample(dim, num_samples=10, dtype=dtypes.float64) 82 cdf_sample = halton.sample(2, num_samples=n, dtype=dtypes.float64) 103 num_samples = 1000 106 sample = halton.sample(dim, num_samples=num_samples) 121 sample_indices = math_ops.range(start=1000, limit=1000 + num_samples,
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/external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
D | training_utils_test.py | 31 num_samples = 1000 44 x = np.random.random((num_samples, input_dim)) 45 y = np.random.random((num_samples, output_dim)) 57 num_samples = 1000 76 a_x = np.random.random((num_samples, input_dim_a)) 77 b_x = np.random.random((num_samples, input_dim_b)) 78 a_y = np.random.random((num_samples, output_dim_a)) 79 b_y = np.random.random((num_samples, output_dim_b))
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/external/webrtc/webrtc/modules/video_coding/utility/ |
D | moving_average.h | 24 bool GetAverage(size_t num_samples, T* average); 44 bool MovingAverage<T>::GetAverage(size_t num_samples, T* avg) { in GetAverage() argument 45 if (num_samples > samples_.size()) in GetAverage() 49 while (num_samples < samples_.size()) { in GetAverage() 54 *avg = sum_ / static_cast<T>(num_samples); in GetAverage()
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | bincount_op_test.py | 66 num_samples = 10000 70 arr = np.random.randint(0, 1000, num_samples) 72 weights = np.random.randint(-100, 100, num_samples) 74 weights = np.random.random(num_samples) 79 num_samples = 10000 83 arr = np.random.randint(0, 1000, num_samples) 84 weights = np.ones(num_samples).astype(dtype)
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