Adds a convolution2d_transpose with an optional batch normalization layer.
View aliases
Main aliases
`tf.contrib.layers.convolution2d_transpose`
tf.contrib.layers.conv2d_transpose(
inputs, num_outputs, kernel_size, stride=1, padding='SAME',
data_format=DATA_FORMAT_NHWC, activation_fn=tf.nn.relu, normalizer_fn=None,
normalizer_params=None, weights_initializer=initializers.xavier_initializer(),
weights_regularizer=None, biases_initializer=tf.zeros_initializer(),
biases_regularizer=None, reuse=None, variables_collections=None,
outputs_collections=None, trainable=True, scope=None
)
The function creates a variable called weights
, representing the
kernel, that is convolved with the input. If normalizer_fn
is None
, a
second variable called 'biases' is added to the result of the operation.
Args |
inputs
|
A 4-D Tensor of type float and shape [batch, height, width,
in_channels] for NHWC data format or [batch, in_channels, height,
width] for NCHW data format.
|
num_outputs
|
Integer, the number of output filters.
|
kernel_size
|
A list of length 2 holding the [kernel_height, kernel_width] of
of the filters. Can be an int if both values are the same.
|
stride
|
A list of length 2: [stride_height, stride_width]. Can be an int if
both strides are the same. Note that presently both strides must have the
same value.
|
padding
|
One of 'VALID' or 'SAME'.
|
data_format
|
A string. NHWC (default) and NCHW are supported.
|
activation_fn
|
Activation function. The default value is a ReLU function.
Explicitly set it to None to skip it and maintain a linear activation.
|
normalizer_fn
|
Normalization function to use instead of biases . If
normalizer_fn is provided then biases_initializer and
biases_regularizer are ignored and biases are not created nor added.
default set to None for no normalizer function
|
normalizer_params
|
Normalization function parameters.
|
weights_initializer
|
An initializer for the weights.
|
weights_regularizer
|
Optional regularizer for the weights.
|
biases_initializer
|
An initializer for the biases. If None skip biases.
|
biases_regularizer
|
Optional regularizer for the biases.
|
reuse
|
Whether or not the layer and its variables should be reused. To be
able to reuse the layer scope must be given.
|
variables_collections
|
Optional list of collections for all the variables or
a dictionary containing a different list of collection per variable.
|
outputs_collections
|
Collection to add the outputs.
|
trainable
|
Whether or not the variables should be trainable or not.
|
scope
|
Optional scope for variable_scope.
|
Returns |
A tensor representing the output of the operation.
|
Raises |
ValueError
|
If 'kernel_size' is not a list of length 2.
|
ValueError
|
If data_format is neither NHWC nor NCHW .
|
ValueError
|
If C dimension of inputs is None.
|