Searched refs:stop_gradient (Results 1 – 25 of 37) sorted by relevance
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/external/tensorflow/tensorflow/contrib/nn/python/ops/ |
D | sampling_ops.py | 81 sampled = math_ops.cast(array_ops.stop_gradient(sampled), dtypes.int64) 82 true_expected_count = array_ops.stop_gradient(true_expected_count) 83 sampled_expected_count = array_ops.stop_gradient(sampled_expected_count)
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/external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
D | monte_carlo_impl.py | 178 center = array_ops.stop_gradient(_sample_max(log_values)) 335 stop = array_ops.stop_gradient # For readability.
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/external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
D | spectral_normalization_impl.py | 90 u = array_ops.stop_gradient(u) 91 v = array_ops.stop_gradient(v)
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D | virtual_batchnorm_impl.py | 67 shift = array_ops.stop_gradient(math_ops.reduce_mean(y, axes, keepdims=True))
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
D | rev_block_lib.py | 99 y1_stop = array_ops.stop_gradient(y1) 100 g_side_input = [array_ops.stop_gradient(t) for t in g_side_input] 104 x2_stop = array_ops.stop_gradient(x2) 105 f_side_input = [array_ops.stop_gradient(t) for t in f_side_input] 694 zero = array_ops.stop_gradient(epsilon * first_compute_sum)
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/external/tensorflow/tensorflow/contrib/training/python/training/ |
D | resample.py | 97 sample_indices = array_ops.stop_gradient(sample_indices)
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/external/tensorflow/tensorflow/python/ops/ |
D | gradients_impl.py | 323 math_ops.multiply(grad_elem, array_ops.stop_gradient(v_elem))
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D | gradients_test.py | 323 if "a" in stop_gradients: a = array_ops.stop_gradient(a) 325 if "b" in stop_gradients: b = array_ops.stop_gradient(b) 327 if "c" in stop_gradients: c = array_ops.stop_gradient(c) 329 if "d" in stop_gradients: d = array_ops.stop_gradient(d) 603 out = array_ops.stop_gradient(inp)
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D | nn_impl.py | 978 math_ops.squared_difference(y, array_ops.stop_gradient(mean)), 1454 array_ops.stop_gradient(s) for s in sampled_values) 1953 labels = array_ops.stop_gradient(labels, name="labels_stop_gradient")
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D | nn_grad.py | 221 return (array_ops.stop_gradient(op.inputs[0]), 664 return (array_ops.stop_gradient(op.inputs[0]), 953 math_ops.squared_difference(x, array_ops.stop_gradient(mean_x)),
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/external/tensorflow/tensorflow/contrib/gan/python/losses/python/ |
D | losses_impl.py | 927 array_ops.stop_gradient(weight_factor) * adversarial_loss) 934 array_ops.stop_gradient(adv_coeff) * adversarial_loss)
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/external/tensorflow/tensorflow/contrib/factorization/examples/ |
D | mnist.py | 151 all_scores = tf.stop_gradient(all_scores)
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/external/tensorflow/tensorflow/python/kernel_tests/random/ |
D | random_grad_test.py | 183 sample_sg = array_ops.stop_gradient(sample)
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/external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
D | util_test.py | 717 zeros_like_x_pl = (x_pl * array_ops.stop_gradient(x_pl - 1.) 718 - array_ops.stop_gradient(x_pl * (x_pl - 1.))) 792 zeros_like_x_pl = (x_pl * array_ops.stop_gradient(x_pl - 1.) 793 - array_ops.stop_gradient(x_pl * (x_pl - 1.)))
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/external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
D | masked_autoregressive.py | 576 return x + array_ops.stop_gradient(clip_x - x)
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/external/tensorflow/tensorflow/contrib/recurrent/python/ops/ |
D | functional_rnn.py | 67 lambda x: array_ops.stop_gradient(array_ops.gather(x, 0)), seq_inputs)
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/external/tensorflow/tensorflow/python/ops/parallel_for/ |
D | array_test.py | 225 for op in [array_ops.identity, array_ops.stop_gradient]:
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/external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
D | README.md | 3 …ss in the implementation by the authors. This saves us from using `tf.stop_gradient` and makes the…
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/external/tensorflow/tensorflow/contrib/keras/api/keras/backend/ |
D | __init__.py | 145 from tensorflow.python.keras.backend import stop_gradient
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | control_flow_ops_py_test.py | 3538 r = gradients_impl.gradients(array_ops.stop_gradient(rx), y)[0] 3540 r = gradients_impl.gradients(array_ops.stop_gradient(ry), y)[0] 3544 array_ops.stop_gradient(math_ops.square(rx)), y)[0] 3547 array_ops.stop_gradient(math_ops.add(rx, ry)), x)[0] 3550 array_ops.stop_gradient(math_ops.add(rx, ry)), y)[0] 3556 math_ops.add(rx, array_ops.stop_gradient(ry)), y)[0] 3559 math_ops.add(array_ops.stop_gradient(rx), ry), y)[0] 3572 y1 = array_ops.stop_gradient(math_ops.square(y)) 3593 y1 = array_ops.stop_gradient(math_ops.square(y, name="stopped")) 3620 grad_theta_stopped = array_ops.stop_gradient(grad_theta) [all …]
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | normalization.py | 671 r = _broadcast(array_ops.stop_gradient(r, name='renorm_r')) 672 d = _broadcast(array_ops.stop_gradient(d, name='renorm_d'))
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/external/tensorflow/tensorflow/python/eager/ |
D | backprop_test.py | 528 lambda x: array_ops.stop_gradient(math_ops.argmax(x))) 535 return array_ops.stop_gradient(i) 880 return array_ops.stop_gradient(z)
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/external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
D | dnn_tree_combined_estimator.py | 283 dnn_logits_fixed = array_ops.stop_gradient(dnn_logits)
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/external/tensorflow/tensorflow/python/ops/losses/ |
D | losses_impl.py | 780 onehot_labels = array_ops.stop_gradient(
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/external/tensorflow/tensorflow/contrib/legacy_seq2seq/python/ops/ |
D | seq2seq.py | 106 emb_prev = array_ops.stop_gradient(emb_prev)
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