| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_fused_batchnorm_test.py | 85 is_training=False)
130 is_training=True)
188 is_training=True): argument
198 if is_training:
211 is_training=is_training)
227 is_training=is_training)
248 is_training=True, argument
261 if is_training:
274 is_training=is_training)
278 if is_training:
[all …]
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| D | nn_grad.py | 863 is_training = op.get_attr("is_training")
867 if is_training:
876 is_training=is_training)
891 is_training=is_training)
914 is_training=True): argument
941 if is_training:
1003 is_training = op.get_attr("is_training")
1017 grad_y, x, scale, pop_mean, pop_var, epsilon, data_format, is_training)
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| /external/tensorflow/tensorflow/examples/speech_commands/ |
| D | models.py | 96 is_training, runtime_settings=None): argument
131 is_training)
133 return create_conv_model(fingerprint_input, model_settings, is_training)
136 is_training)
139 is_training, runtime_settings)
142 is_training)
161 def create_single_fc_model(fingerprint_input, model_settings, is_training): argument
186 if is_training:
197 if is_training:
203 def create_conv_model(fingerprint_input, model_settings, is_training): argument
[all …]
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| /external/tensorflow/tensorflow/contrib/slim/python/slim/nets/ |
| D | vgg.py | 76 is_training=True, argument
118 net, dropout_keep_prob, is_training=is_training, scope='dropout6')
121 net, dropout_keep_prob, is_training=is_training, scope='dropout7')
141 is_training=True, argument
183 net, dropout_keep_prob, is_training=is_training, scope='dropout6')
186 net, dropout_keep_prob, is_training=is_training, scope='dropout7')
206 is_training=True, argument
248 net, dropout_keep_prob, is_training=is_training, scope='dropout6')
251 net, dropout_keep_prob, is_training=is_training, scope='dropout7')
|
| D | resnet_v1.py | 131 is_training=True, argument
198 with arg_scope([layers.batch_norm], is_training=is_training):
253 is_training=True, argument
269 is_training,
279 is_training=True, argument
295 is_training,
305 is_training=True, argument
321 is_training,
331 is_training=True, argument
347 is_training,
|
| D | resnet_v2.py | 133 is_training=True, argument
202 with arg_scope([layers.batch_norm], is_training=is_training):
266 is_training=True, argument
282 is_training,
292 is_training=True, argument
308 is_training,
318 is_training=True, argument
334 is_training,
344 is_training=True, argument
360 is_training,
|
| D | vgg_test.py | 59 for is_training in [True, False]:
62 _, end_points = vgg.vgg_a(inputs, num_classes, is_training=is_training)
112 logits, _ = vgg.vgg_a(eval_inputs, is_training=False)
134 eval_inputs, is_training=False, spatial_squeeze=False)
180 for is_training in [True, False]:
183 _, end_points = vgg.vgg_16(inputs, num_classes, is_training=is_training)
246 logits, _ = vgg.vgg_16(eval_inputs, is_training=False)
268 eval_inputs, is_training=False, spatial_squeeze=False)
314 for is_training in [True, False]:
317 _, end_points = vgg.vgg_19(inputs, num_classes, is_training=is_training)
[all …]
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| D | overfeat.py | 61 is_training=True, argument
114 net, dropout_keep_prob, is_training=is_training, scope='dropout6')
117 net, dropout_keep_prob, is_training=is_training, scope='dropout7')
|
| D | alexnet.py | 65 is_training=True, argument
118 net, dropout_keep_prob, is_training=is_training, scope='dropout6')
121 net, dropout_keep_prob, is_training=is_training, scope='dropout7')
|
| /external/tensorflow/tensorflow/contrib/quantize/python/ |
| D | quantize_test.py | 44 for is_training in params:
45 test_fn(is_training)
50 def _TestInsertQuantOpFailsWhenOpsNotConnected(self, is_training): argument
63 quantize._InsertQuantOp('test', is_training, conv.op, [relu.op],
71 def _TestInsertQuantOpForAddAfterConv2d(self, is_training): argument
86 quantize.Quantize(graph, is_training, weight_bits=8, activation_bits=8)
110 def _TestInsertQuantOpForAddAfterSeparableConv2d(self, is_training): argument
126 quantize.Quantize(graph, is_training, weight_bits=8, activation_bits=8)
147 def _TestInsertQuantOpInSeparableConv2d(self, is_training): argument
168 quantize.Quantize(graph, is_training, weight_bits=8, activation_bits=8)
[all …]
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| D | quantize_graph.py | 27 is_training=True, argument
73 is_training=is_training)
76 is_training,
120 is_training=True,
143 _create_graph(input_graph=input_graph, is_training=False)
199 is_training=True,
244 is_training=False,
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| D | quantize.py | 47 is_training, argument
100 is_training,
128 is_training,
149 is_training,
172 is_training,
207 is_training,
220 is_training,
230 is_training, argument
268 is_training,
648 is_training, argument
[all …]
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| D | fold_batch_norms.py | 37 def FoldBatchNorms(graph, is_training, freeze_batch_norm_delay=None): argument
53 graph, is_training, freeze_batch_norm_delay=freeze_batch_norm_delay)
56 is_training=is_training,
60 def _FoldFusedBatchNorms(graph, is_training, freeze_batch_norm_delay): argument
93 if is_training:
266 is_training = bn_op.get_attr('is_training')
267 if is_training:
502 def _FoldUnfusedBatchNorms(graph, is_training, freeze_batch_norm_delay): argument
531 is_training=is_training)
717 is_training): argument
[all …]
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| D | quant_ops.py | 68 is_training=True, argument
123 if not is_training:
193 is_training=True, argument
249 if not is_training:
|
| D | quant_ops_test.py | 100 is_training=True,
115 is_training=True,
126 is_training=True,
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| D | imagenet_input.py | 35 image_bytes=image_bytes, is_training=False)
73 def __init__(self, is_training, argument
82 self.is_training = is_training
127 is_training=self.is_training,
159 self.data_dir, 'train-*' if self.is_training else 'validation-*')
160 dataset = tf.data.Dataset.list_files(file_pattern, shuffle=self.is_training)
162 if self.is_training and not self.cache:
|
| /external/tensorflow/tensorflow/contrib/receptive_field/python/util/examples/ |
| D | rf_benchmark.py | 127 images, num_classes=None, is_training=False, global_pool=False)
130 images, num_classes=None, is_training=False, global_pool=False)
133 images, num_classes=None, is_training=False, global_pool=False)
136 images, num_classes=None, is_training=False, global_pool=False)
139 images, num_classes=None, is_training=False, global_pool=False)
142 images, num_classes=None, is_training=False, global_pool=False)
145 images, num_classes=None, is_training=False, global_pool=False)
148 images, num_classes=None, is_training=False, global_pool=False)
478 is_training=False) as arg_sc:
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_FusedBatchNormGrad.pbtxt | 24 When is_training is True, a 1D Tensor for the computed batch
25 mean to be reused in gradient computation. When is_training is
33 When is_training is True, a 1D Tensor for the computed batch
35 gradient computation. When is_training is False, a 1D Tensor
91 name: "is_training"
|
| D | api_def_FusedBatchNormGradV2.pbtxt | 24 When is_training is True, a 1D Tensor for the computed batch
25 mean to be reused in gradient computation. When is_training is
33 When is_training is True, a 1D Tensor for the computed batch
35 gradient computation. When is_training is False, a 1D Tensor
97 name: "is_training"
|
| D | api_def_CudnnRNNV2.pbtxt | 32 is_training: Indicates whether this operation is used for inferenece or
35 is only produced if is_training is true.
37 only produced if is_training is true. It is output on host memory rather than
|
| /external/tensorflow/tensorflow/contrib/cudnn_rnn/python/ops/ |
| D | cudnn_rnn_ops.py | 956 is_training, argument
1017 "is_training": is_training,
1048 is_training, argument
1095 return _cudnn_rnn(inputs, input_h, input_c, params, is_training, CUDNN_LSTM,
1103 is_training, argument
1152 inputs, input_h, input_c, params, is_training, rnn_mode, sequence_lengths,
1160 is_training, argument
1205 return _cudnn_rnn_no_input_c(inputs, input_h, params, is_training, CUDNN_GRU,
1213 is_training, argument
1257 return _cudnn_rnn_no_input_c(inputs, input_h, params, is_training,
[all …]
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| /external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/ |
| D | cudnn_rnn_ops_test.py | 74 is_training=True, argument
82 if is_training and not np.isclose(dropout, 0):
155 is_training=is_training,
162 if is_training:
188 if is_training:
450 is_training=False,
483 is_training=False,
524 is_training=False,
539 is_training=False,
558 is_training=True, argument
[all …]
|
| /external/tensorflow/tensorflow/python/compiler/tensorrt/test/ |
| D | quantization_mnist_test.py | 161 def _Run(self, is_training, use_trt, batch_size, num_epochs, model_dir): argument
216 if is_training:
247 model_dir=model_dir if is_training else None,
250 if is_training:
271 is_training=False,
283 is_training=False,
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | composable_model.py | 90 def build_model(self, features, feature_columns, is_training): argument
228 def build_model(self, features, feature_columns, is_training): argument
355 def build_model(self, features, feature_columns, is_training): argument
388 if self._dropout is not None and is_training:
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| D | fused_batchnorm_test.py | 106 is_training=False)
149 is_training=True)
236 is_training=True)
286 is_training=False)
290 grad, x, scale, mean, var, data_format=data_format, is_training=False)
|