| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | parameterized_truncated_normal_op_test.py | 93 moments = [0.0] * (max_moment + 1)
96 for k in range(len(moments)):
97 moments[k] += value
99 for i in range(len(moments)):
100 moments[i] /= len(samples)
101 return moments
132 moments = calculate_moments(samples, self.max_moment)
135 for i in range(1, len(moments)):
137 z_test(moments, expected_moments, i, num_samples), self.z_limit)
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| /external/tensorflow/tensorflow/core/lib/random/ |
| D | random_distributions_test.cc | 83 std::vector<double> moments(max_moments + 1); in CheckSamplesMoments() local
84 double* const moments_data = &moments[0]; in CheckSamplesMoments()
106 moments[i] /= moments_sample_count[i]; in CheckSamplesMoments()
130 fabs((moments[i] - moments_i_mean) / sqrt(total_variance)); in CheckSamplesMoments()
136 << " measured moments: " << moments[i] in CheckSamplesMoments()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_BatchNormWithGlobalNormalization.pbtxt | 13 This is the first output from tf.nn.moments,
21 This is the second output from tf.nn.moments,
|
| D | api_def_BatchNormWithGlobalNormalizationGrad.pbtxt | 13 This is the first output from tf.nn.moments,
21 This is the second output from tf.nn.moments,
|
| D | api_def_QuantizedBatchNormWithGlobalNormalization.pbtxt | 25 This is the first output from tf.nn.moments,
45 This is the second output from tf.nn.moments,
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| /external/tensorflow/tensorflow/contrib/nn/python/ops/ |
| D | alpha_dropout_test.py | 39 t_mean, t_std = nn_impl.moments(t, axes=[0, 1])
40 output_mean, output_std = nn_impl.moments(output, axes=[0, 1])
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | normalization.py | 155 mean, variance = nn.moments(inputs, moments_axes, keep_dims=True)
365 mean, variance = nn.moments(inputs, moments_axes, keep_dims=True)
|
| D | layers.py | 774 mean, variance = nn.moments(inputs, moments_axes, keep_dims=True)
778 mean, variance = nn.moments(inputs, moments_axes)
2313 mean, variance = nn.moments(inputs, norm_axes, keep_dims=True)
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| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| D | virtual_batchnorm_test.py | 59 mom_mean, mom_var = nn.moments(tensors, axes)
82 mom_mean, mom_variance = nn.moments(full_batch, reduction_axes)
|
| /external/tensorflow/tensorflow/contrib/autograph/examples/benchmarks/ |
| D | cartpole_benchmark.py | 162 mean, variance = tf.nn.moments(discounted_rewards, [0])
347 mean, variance = tf.nn.moments(discounted_rewards, [0])
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| D | batch_normalization.py | 269 _, v = nn.moments(y, axes=reduction_axes, keep_dims=True)
|
| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| D | classifier_metrics_impl.py | 630 m, var = nn_impl.moments(real_activations, axes=[0])
631 m_w, var_w = nn_impl.moments(generated_activations, axes=[0])
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| D | sliced_wasserstein_impl.py | 128 mean, variance = nn.moments(patches, [1, 2, 3], keep_dims=True)
|
| /external/tensorflow/tensorflow/python/keras/ |
| D | optimizers.py | 196 moments = [K.zeros(shape) for shape in shapes]
197 self.weights = [self.iterations] + moments
198 for p, g, m in zip(params, grads, moments):
|
| D | backend_test.py | 1742 mean, var = nn.moments(x, (0, 1), None, None, False)
1750 mean, var = nn.moments(x, (0, 1, 2), None, None, False)
1758 mean, var = nn.moments(x, (0, 2, 3), None, None, False)
|
| /external/ImageMagick/MagickCore/ |
| D | statistic.c | 1712 *moments; in GetImagePerceptualHash() local
1738 moments=GetImageMoments(hash_image,exception); in GetImagePerceptualHash()
1742 if (moments == (ChannelMoments *) NULL) in GetImagePerceptualHash()
1747 (-MagickLog10(moments[channel].invariant[j])); in GetImagePerceptualHash()
1748 moments=(ChannelMoments *) RelinquishMagickMemory(moments); in GetImagePerceptualHash()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | batch_norm_benchmark.py | 99 mean, variance = nn_impl.moments(tensor, axes, keep_dims=keep_dims)
|
| D | nn_impl.py | 928 def moments( function
1025 return moments(x=x, axes=axes, shift=shift, name=name, keep_dims=keepdims)
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| D | nn_fused_batchnorm_test.py | 101 mean, var = nn_impl.moments(
|
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | normalization.py | 566 return nn.moments(inputs, reduction_axes, keep_dims=keep_dims)
975 mean, variance = nn.moments(inputs, self.norm_axis, keep_dims=True)
|
| /external/python/cpython2/Doc/library/ |
| D | htmllib.rst | 53 The parser will call these at appropriate moments: :meth:`start_tag` or
|
| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.nn.pbtxt | 228 name: "moments"
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| D | math_utils.py | 893 mean, variance = nn.moments(
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| /external/ImageMagick/Magick++/lib/Magick++/ |
| D | Image.h | 1093 ImageMoments moments(void) const;
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.nn.pbtxt | 280 name: "moments"
|