Noise layers

Noise layers

Dropout

Dropout layer

class braid.berry.layers.Dropout(incoming, p, **kwargs)

Dropout layer

Sets values to zero with probability p. See notes for disabling dropout during testing.

incoming

: a Layer instance or a tuple

the layer feeding into this layer, or the expected input shape

p

: float, optional (default = 0.5)

The probability of setting a value to zero

name

: string, optional (default = None)

Name of the layer. Should be specified for better readability ( inherited from Layer).

Note

The dropout layer is a regularizer that randomly sets input values to zero; see [1], [2] for why this might improve generalization.

For ease of use, see get_aux_inputs() to get the value of p during training and testing.

[1]	Hinton, G., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R. R. (2012): Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580.

[2]	Srivastava Nitish, Hinton, G., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2014): Dropout: A Simple Way to Prevent Neural Networks from Overfitting. Journal of Machine Learning Research, 5(Jun)(2), 1929-1958.

get_aux_inputs()

This function returns the auxiliary inputs required for the layer.

list of tuples

[(tf.placeholder.name, (train_phase_value, test_phase_value)),]

>>> l = Dropout(l_in, p=0.5)
>>> print l.get_aux_inputs()
[(u'drop_1/p:0', (0.5, 1.0))]

get_fan_out()

Output receptive field

int

fan_in * p

get_output_for()

Perform the dropout operation and returns the output tf.Tensor

tf.Tensor

Output tensor of this layer.

get_output_shape_for(input_shape)

Shape of the output tensor

input_shape

: tuple or list

Shape of the input layer.

tuple

Same as the input_shape

validate_input_layer(incoming)

Validate the input layer shape

Returns True if the input layer is 2D else, raise an exceptions.AssertError.