| /external/tensorflow/tensorflow/contrib/nn/python/ops/ |
| alpha_dropout.py | 30 def alpha_dropout(x, keep_prob, noise_shape=None, seed=None, name=None): # pylint: disable=invalid-name
43 noise_shape: A 1-D `Tensor` of type `int32`, representing the
72 noise_shape = noise_shape if noise_shape is not None else array_ops.shape(x)
73 random_tensor = random_ops.random_uniform(noise_shape,
|
| alpha_dropout_test.py | 51 _ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, y_dim + 10])
53 _ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, y_dim, 5])
55 _ = alpha_dropout(t, keep_prob, noise_shape=[x_dim + 3])
57 _ = alpha_dropout(t, keep_prob, noise_shape=[x_dim])
60 _ = alpha_dropout(t, keep_prob, noise_shape=[y_dim])
61 _ = alpha_dropout(t, keep_prob, noise_shape=[1, y_dim])
62 _ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, 1])
63 _ = alpha_dropout(t, keep_prob, noise_shape=[1, 1])
|
| /external/tensorflow/tensorflow/python/layers/ |
| core.py | 267 noise_shape: 1D tensor of type `int32` representing the shape of the
272 `noise_shape=[batch_size, 1, features]`.
280 noise_shape=None,
286 self.noise_shape = noise_shape
291 # which will override `self.noise_shape`, and allows for custom noise
293 if self.noise_shape is None:
294 return self.noise_shape
295 return nn_ops._get_noise_shape(inputs, self.noise_shape)
301 noise_shape=self._get_noise_shape(inputs)
[all...] |
| core_test.py | 368 self.assertEqual(dp.noise_shape, None)
400 noise_shape = [None, 1, None]
401 dp = core_layers.Dropout(0.5, noise_shape=noise_shape, seed=1)
410 noise_shape = [5, 1, 2]
411 dp = core_layers.Dropout(0.5, noise_shape=noise_shape, seed=1)
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
| noise.py | 148 def __init__(self, rate, noise_shape=None, seed=None, **kwargs):
151 self.noise_shape = noise_shape
156 return self.noise_shape if self.noise_shape else K.shape(inputs)
160 noise_shape = self._get_noise_shape(inputs)
168 K.random_uniform(noise_shape, seed=seed), rate)
|
| core.py | 104 noise_shape: 1D integer tensor representing the shape of the
109 you can use `noise_shape=(batch_size, 1, features)`.
113 def __init__(self, rate, noise_shape=None, seed=None, **kwargs):
117 noise_shape=noise_shape,
134 'noise_shape': self.noise_shape,
174 noise_shape = (input_shape[0], 1, input_shape[2])
175 return noise_shape
|
| /external/tensorflow/tensorflow/python/ops/ |
| nn_test.py | 315 dropout = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, 1])
340 dropout = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, 1])
383 x, keep_prob, noise_shape=array_ops.placeholder(dtypes.int32))
394 # Set noise_shape=[None, 1] which means [x_dim, 1].
395 dropout = nn_ops.dropout(t, keep_prob, noise_shape=[None, 1])
433 _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, y_dim + 10])
435 _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, y_dim, 5])
437 _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim + 3])
439 _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim])
441 _ = nn_ops.dropout(t, keep_prob, noise_shape=[y_dim]
[all...] |
| nn_ops.py | [all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| layers.py | [all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| backend.py | [all...] |
