| /external/tensorflow/tensorflow/python/ops/ |
| D | embedding_ops.py | 40 def _clip(params, ids, max_norm): argument
72 if max_norm is None:
78 max_norm,
88 max_norm=None, argument
134 ids, max_norm)
209 result = transform_fn(_clip(result, pids, max_norm))
246 ret = _clip(ret, ids, max_norm)
257 max_norm=None): argument
315 max_norm=max_norm,
323 max_norm=None, argument
[all …]
|
| D | clip_ops_test.py | 34 def _testClipTensorByNorm(self, inputs, max_norm, expected): argument
37 clipped = clip_ops.clip_by_norm(input_op, max_norm)
42 def _testClipIndexedSlicesByNorm(self, values, indices, shape, max_norm, argument
50 clipped = clip_ops.clip_by_norm(indixed_slices, max_norm, axes)
57 dense_clipped = clip_ops.clip_by_norm(dense_tensor, max_norm, axes)
|
| /external/tensorflow/tensorflow/python/tpu/ |
| D | feature_column.py | 109 max_norm=None,
140 max_norm=None,
159 max_norm=None,
215 max_norm=None, argument
228 max_norm=max_norm,
238 max_norm=None, argument
313 max_norm=None, argument
324 max_norm=max_norm,
335 max_norm=None, argument
|
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| D | training.py | 297 def clip_gradient_norms(gradients_to_variables, max_norm): argument
311 tmp = clip_ops.clip_by_norm(grad.values, max_norm)
314 grad = clip_ops.clip_by_norm(grad, max_norm)
319 def clip_gradient_norms_fn(max_norm): argument
322 return clip_gradient_norms(gradients_to_variables, max_norm)
|
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | normalization_test.py | 82 max_norm = keras.constraints.max_norm
84 gamma_constraint=max_norm, beta_constraint=max_norm)
86 self.assertEqual(layer.gamma.constraint, max_norm)
87 self.assertEqual(layer.beta.constraint, max_norm)
449 max_norm = keras.constraints.max_norm
451 gamma_constraint=max_norm, beta_constraint=max_norm)
453 self.assertEqual(layer.gamma.constraint, max_norm)
454 self.assertEqual(layer.beta.constraint, max_norm)
|
| D | simplernn_test.py | 85 k_constraint = keras.constraints.max_norm(0.01)
86 r_constraint = keras.constraints.max_norm(0.01)
87 b_constraint = keras.constraints.max_norm(0.01)
|
| D | local_test.py | 104 k_constraint = keras.constraints.max_norm(0.01)
105 b_constraint = keras.constraints.max_norm(0.01)
221 k_constraint = keras.constraints.max_norm(0.01)
222 b_constraint = keras.constraints.max_norm(0.01)
|
| D | gru_test.py | 191 k_constraint = keras.constraints.max_norm(0.01)
192 r_constraint = keras.constraints.max_norm(0.01)
193 b_constraint = keras.constraints.max_norm(0.01)
|
| D | lstm_test.py | 104 k_constraint = keras.constraints.max_norm(0.01)
105 r_constraint = keras.constraints.max_norm(0.01)
106 b_constraint = keras.constraints.max_norm(0.01)
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | embedding_ops.py | 55 max_norm=None): argument
162 max_norm=max_norm)
591 max_norm=None): argument
675 max_norm=max_norm,
719 max_norm=None, argument
732 if max_norm is not None:
737 return clip_ops.clip_by_norm(x, max_norm, axes=list(range(1, ndims)))
|
| D | feature_column.py | 1091 max_norm=None, argument
1114 max_norm,
1156 max_norm=self.max_norm,
1290 max_norm=args.max_norm)
1324 max_norm=None, argument
1361 max_norm=max_norm, trainable=trainable)
1371 max_norm=None, argument
1435 shared_embedding_name, max_norm=max_norm,
1479 max_norm=max_norm, trainable=trainable))
1537 max_norm=None,
|
| D | optimizers.py | 380 max_norm, log_mean = _adaptive_max_norm(norm, std_factor, decay,
385 summary.scalar("global_norm/adaptive_max_gradient_norm", max_norm)
388 factor = array_ops.where(norm < max_norm,
|
| /external/tensorflow/tensorflow/python/keras/ |
| D | constraints_test.py | 56 norm_instance = keras.constraints.max_norm(m)
61 norm_instance = keras.constraints.max_norm(2.0)
|
| D | constraints.py | 173 max_norm = MaxNorm variable
179 maxnorm = max_norm
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| D | variable_clipping_optimizer.py | 56 max_norm, argument
80 self._max_norm = max_norm
|
| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.feature_column.pbtxt | 29 …r\', \'initializer\', \'ckpt_to_load_from\', \'tensor_name_in_ckpt\', \'max_norm\', \'trainable\']…
65 …ng_collection_name\', \'ckpt_to_load_from\', \'tensor_name_in_ckpt\', \'max_norm\', \'trainable\']…
|
| D | tensorflow.keras.constraints.max_norm.pbtxt | 1 path: "tensorflow.keras.constraints.max_norm"
|
| D | tensorflow.keras.constraints.pbtxt | 24 name: "max_norm"
|
| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.feature_column.pbtxt | 29 …r\', \'initializer\', \'ckpt_to_load_from\', \'tensor_name_in_ckpt\', \'max_norm\', \'trainable\']…
73 …ng_collection_name\', \'ckpt_to_load_from\', \'tensor_name_in_ckpt\', \'max_norm\', \'trainable\']…
|
| D | tensorflow.keras.constraints.max_norm.pbtxt | 1 path: "tensorflow.keras.constraints.max_norm"
|
| D | tensorflow.keras.constraints.pbtxt | 24 name: "max_norm"
|
| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| D | learning.py | 280 def clip_gradient_norms(gradients_to_variables, max_norm): argument
294 tmp = clip_ops.clip_by_norm(grad.values, max_norm)
297 grad = clip_ops.clip_by_norm(grad, max_norm)
|
| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| D | clip_weights_impl.py | 78 max_norm=weight_clip,
|
| /external/tensorflow/tensorflow/contrib/keras/api/keras/constraints/ |
| D | __init__.py | 23 from tensorflow.python.keras.constraints import max_norm
|
| /external/tensorflow/tensorflow/python/feature_column/ |
| D | feature_column_v2.py | 824 max_norm=None, argument
918 max_norm=max_norm,
930 max_norm=None, argument
1089 max_norm=max_norm,
1103 max_norm=None, argument
1256 categorical_column=column, combiner=combiner, max_norm=max_norm))
3069 max_norm=self.max_norm)
3241 def __call__(self, categorical_column, combiner, max_norm): argument
3242 return SharedEmbeddingColumn(categorical_column, self, combiner, max_norm)
3336 max_norm=self.max_norm)
|