| /external/blktrace/doc/ |
| blkiomon.8 | 19 and variance. For this purpose, it consumes D and C traces read from stdin.
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| fused_batchnorm_test.py | 84 y, mean, variance = nn.fused_batch_norm(
89 variance=var_ref,
96 variance], {t_val: x_val,
124 variance=None,
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| geometric_test.py | 150 self.assertEqual([3], geom.variance().get_shape())
151 self.assertAllClose(expected_vars, geom.variance().eval())
249 self.assertEqual([], geom.variance().get_shape())
250 self.assertAllClose(expected_variance, geom.variance().eval())
|
| poisson_test.py | 152 self.assertEqual(poisson.variance().get_shape(), (3,))
153 self.assertAllClose(poisson.variance().eval(), stats.poisson.var(lam_v))
154 self.assertAllClose(poisson.variance().eval(), lam_v)
219 # variance should be within `k` std. deviations of actual up to rtol
|
| chi2_test.py | 75 self.assertEqual(chi2.variance().get_shape(), (3,))
76 self.assertAllClose(chi2.variance().eval(), expected_variances)
|
| /external/tensorflow/tensorflow/contrib/timeseries/examples/ |
| predict_test.py | 46 # Check that variance hasn't blown up too much. This is a relatively good
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_ApplyCenteredRMSProp.pbtxt | 68 (i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
| api_def_ResourceApplyCenteredRMSProp.pbtxt | 62 (i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
| api_def_ResourceSparseApplyCenteredRMSProp.pbtxt | 68 (i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
| api_def_SparseApplyCenteredRMSProp.pbtxt | 74 (i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
| /external/tensorflow/tensorflow/docs_src/api_guides/python/ |
| contrib.bayesflow.monte_carlo.md | 20 variance `Var[f(Z)] / n`.
|
| /external/webrtc/webrtc/modules/audio_processing/intelligibility/ |
| intelligibility_utils.cc | 102 // Compute the variance with Welford's algorithm, adding some fudge to
130 // Compute the variance from the beginning, with exponential decaying of the
157 // Windowed variance computation. On each step, the variances for the
188 // Variance with a window of blocks. Within each block, the variances are
|
| /cts/apps/CameraITS/tests/scene1/ |
| test_raw_burst_sensitivity.py | 81 # is increasing). Use the variance of the center stats grid cell.
103 pylab.ylabel("Image Center Patch Variance")
|
| /external/deqp/modules/glshared/ |
| glsStateChangePerfTestCases.cpp | 59 double variance; member in struct:deqp::gls::__anon18892::ResultStats
79 result.variance += (val - result.mean) * (val - result.mean);
82 result.variance /= (double)values.size();
548 log << TestLog::Message << "Interleaved variance: " << interleaved.variance << TestLog::EndMessage;
554 log << TestLog::Message << "Batched variance: " << batched.variance << TestLog::EndMessage;
702 log << TestLog::Message << "Iteration variance time: " << varIteration << TestLog::EndMessage;
|
| /external/drrickorang/LoopbackApp/app/src/main/jni/ |
| jni_sles.c | 104 // variance has units ns^2 so we have to square the conversion factor
138 // variance has units ns^2 so we have to square the conversion factor
|
| /external/libvpx/libvpx/test/ |
| comp_avg_pred_test.cc | 54 // This is called as part of the sub pixel variance. As such it must be one of
55 // the variance block sizes.
|
| /external/libvpx/libvpx/vp8/common/x86/ |
| mfqe_sse2.asm | 167 ; unsigned int *variance, 4
257 ; (variance + 128) >> 8
|
| /external/libvpx/libvpx/vp9/common/x86/ |
| vp9_mfqe_sse2.asm | 168 ; unsigned int *variance, 4
258 ; (variance + 128) >> 8
|
| /external/libvpx/libvpx/vp9/encoder/ |
| vp9_aq_complexity.c | 144 // Test rate against a threshold value and variance against a threshold.
145 // Increasing segment number (higher variance and complexity) = higher Q.
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| normal_conjugate_posteriors.py | 30 and known variance `scale**2`. The "known scale posterior" is
89 and known variance `scale**2`. The "known scale predictive"
|
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| training_test.py | 127 mean, variance = session.run([moving_mean, moving_variance])
130 self.assertAllClose(variance, [1] * 4)
136 variance = moving_variance.eval()
140 self.assertAllClose(variance, expected_var)
160 mean, variance = session.run([moving_mean, moving_variance])
163 self.assertAllClose(variance, [1] * 4)
169 variance = moving_variance.eval()
173 self.assertAllClose(variance, [1] * 4)
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| normalization.py | 46 epsilon: Small float added to variance to avoid dividing by zero.
57 moving_variance_initializer: Initializer for the moving variance.
|
| normalization_test.py | 88 # centered on 5.0, variance 10.0
107 # centered on 5.0, variance 10.0
|
| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| exponential_test.py | 98 self.assertEqual(exponential.variance().get_shape(), (3,))
102 self.assertAllClose(exponential.variance().eval(), expected_variance)
|
| /external/webrtc/webrtc/modules/audio_coding/test/ |
| utility.cc | 193 // to calculate variance we have to update
253 int16_t CircularBuffer::Variance(double& var) {
|
