| /external/tensorflow/tensorflow/contrib/quantize/python/ |
| D | fold_batch_norms_test.py | 97 activation_fn = None if with_bypass else relu
107 activation_fn=None,
118 if activation_fn is not None:
119 node = activation_fn(node)
128 activation_fn=activation_fn,
197 activation_fn = relu
206 activation_fn=None,
212 layer1 = activation_fn(layer1)
219 activation_fn=activation_fn,
227 _ = activation_fn(layer2)
[all …]
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| D | quantize_test.py | 57 activation_fn=None, scope='test')
79 activation_fn=None, scope='test/test')
119 activation_fn=None, scope='test/test')
160 activation_fn=None,
213 activation_fn=nn_ops.relu6,
240 activation_fn=None,
263 activation_fn=nn_ops.relu6,
273 activation_fn=nn_ops.relu6,
301 activation_fn=nn_ops.relu6,
312 activation_fn=None,
[all …]
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| D | quantize_parameterized_test.py | 186 activation_fn = None if with_bypass else activation
196 activation_fn=activation_fn,
238 activation_fn = None if with_bypass else activation
246 activation_fn=activation_fn,
285 activation_fn = None if with_bypass else activation
297 activation_fn=activation_fn,
336 activation_fn = None if with_bypass else activation
348 activation_fn=activation_fn,
521 activation_fn=None,
575 activation_fn=None,
[all …]
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| D | quantize_graph_test.py | 451 activation_fn=None)
474 activation_fn=None,
502 activation_fn=None,
|
| /external/tensorflow/tensorflow/contrib/specs/python/ |
| D | specs_ops.py | 81 Cs = Fun(layers.conv2d, activation_fn=math_ops.sigmoid)
82 Ct = Fun(layers.conv2d, activation_fn=math_ops.tanh)
83 Cr = Fun(layers.conv2d, activation_fn=nn_ops.relu)
84 Cm = Fun(layers.conv2d, activation_fn=nn_ops.softmax)
85 Cl = Fun(layers.conv2d, activation_fn=None)
90 Fs = Fun(layers.fully_connected, activation_fn=math_ops.sigmoid)
91 Ft = Fun(layers.fully_connected, activation_fn=math_ops.tanh)
92 Fr = Fun(layers.fully_connected, activation_fn=nn_ops.relu)
93 Fm = Fun(layers.fully_connected, activation_fn=nn_ops.softmax)
94 Fl = Fun(layers.fully_connected, activation_fn=None)
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | dnn.py | 72 def _get_activation_fn(activation_fn): argument
73 if not isinstance(activation_fn, six.string_types):
74 return activation_fn
75 if activation_fn not in _ACTIVATION_FUNCTIONS.keys():
77 (", ".join(_ACTIVATION_FUNCTIONS.keys()), activation_fn))
78 return _ACTIVATION_FUNCTIONS[activation_fn]
128 activation_fn = _get_activation_fn(params.get("activation_fn"))
175 activation_fn=activation_fn,
188 activation_fn=None,
308 activation_fn=nn.relu, argument
[all …]
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| D | composable_model.py | 278 activation_fn=nn.relu, argument
315 self._activation_fn = activation_fn
384 activation_fn=self._activation_fn,
399 activation_fn=None,
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | layers.py | 180 activation_fn=None, argument
424 if activation_fn is not None:
425 outputs = activation_fn(outputs)
435 activation_fn=None, argument
586 activation_fn=activation_fn,
664 if activation_fn is not None:
665 outputs = activation_fn(outputs)
835 if activation_fn is not None:
836 outputs = activation_fn(outputs)
842 activation_fn=None, argument
[all …]
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| D | normalization.py | 46 activation_fn=None, argument
160 if activation_fn is not None:
161 outputs = activation_fn(outputs)
173 activation_fn=None, argument
382 if activation_fn is not None:
383 outputs = activation_fn(outputs)
|
| /external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
| D | layers.py | 103 activation_fn=nn.relu, argument
249 if activation_fn is not None:
250 outputs = activation_fn(outputs)
262 activation_fn=nn.relu, argument
359 if activation_fn is not None:
360 outputs = activation_fn(outputs)
|
| /external/tensorflow/tensorflow/contrib/slim/python/slim/nets/ |
| D | resnet_v2.py | 101 inputs, activation_fn=nn_ops.relu, scope='preact')
110 activation_fn=None,
122 activation_fn=None,
213 [layers_lib.conv2d], activation_fn=None, normalizer_fn=None):
221 net, activation_fn=nn_ops.relu, scope='postnorm')
229 activation_fn=None,
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| D | vgg.py | 67 activation_fn=nn_ops.relu,
125 activation_fn=None,
190 activation_fn=None,
255 activation_fn=None,
|
| D | resnet_v1.py | 113 activation_fn=None,
121 residual, depth, [1, 1], stride=1, activation_fn=None, scope='conv3')
215 activation_fn=None,
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| D | overfeat.py | 51 activation_fn=nn_ops.relu,
121 activation_fn=None,
|
| D | alexnet.py | 55 activation_fn=nn_ops.relu,
125 activation_fn=None,
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| D | resnet_utils.py | 259 activation_fn=nn_ops.relu,
|
| D | inception_v3.py | 609 activation_fn=None,
634 activation_fn=None,
726 activation_fn=nn_ops.relu,
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/hybrid/python/models/ |
| D | hard_decisions_to_data_then_nn.py | 59 inference_result, output_size, activation_fn=nn_ops.softmax)
|
| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.estimator.experimental.pbtxt | 21 …argspec: "args=[\'units\', \'hidden_units\', \'feature_columns\', \'activation_fn\', \'dropout\', …
|
| D | tensorflow.estimator.-d-n-n-regressor.pbtxt | 24 …model_dir\', \'label_dimension\', \'weight_column\', \'optimizer\', \'activation_fn\', \'dropout\'…
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| D | tensorflow.estimator.-d-n-n-estimator.pbtxt | 24 …'hidden_units\', \'feature_columns\', \'model_dir\', \'optimizer\', \'activation_fn\', \'dropout\'…
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| D | tensorflow.estimator.-d-n-n-classifier.pbtxt | 24 …_classes\', \'weight_column\', \'label_vocabulary\', \'optimizer\', \'activation_fn\', \'dropout\'…
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.estimator.-d-n-n-estimator.pbtxt | 25 …'hidden_units\', \'feature_columns\', \'model_dir\', \'optimizer\', \'activation_fn\', \'dropout\'…
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| D | tensorflow.estimator.-d-n-n-classifier.pbtxt | 25 …_classes\', \'weight_column\', \'label_vocabulary\', \'optimizer\', \'activation_fn\', \'dropout\'…
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| /external/tensorflow/tensorflow/contrib/tensor_forest/hybrid/python/ |
| D | hybrid_model.py | 85 inference_result, output_size, activation_fn=array_ops.identity)
|