tf.contrib.layers.bias_add
Adds a bias to the inputs.
tf.contrib.layers.bias_add( inputs, activation_fn=None, initializer=tf.zeros_initializer(), regularizer=None, reuse=None, variables_collections=None, outputs_collections=None, trainable=True, data_format=DATA_FORMAT_NHWC, scope=None )
Can be used as a normalizer function for conv2d and fully_connected.
Args | |
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inputs |
A tensor of with at least rank 2 and value for the last dimension, e.g. [batch_size, depth] , [None, None, None, depth] . |
activation_fn |
Activation function, default set to None to skip it and maintain a linear activation. |
initializer |
An initializer for the bias, defaults to 0. |
regularizer |
A regularizer like the result of l1_regularizer or l2_regularizer . |
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 collections for the variables. |
outputs_collections |
Collections to add the outputs. |
trainable |
If True also add variables to the graph collection GraphKeys.TRAINABLE_VARIABLES (see tf.Variable). |
data_format |
A string. 'NHWC' and 'NCHW' are supported. |
scope |
Optional scope for variable_scope. |
Returns | |
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A tensor representing the result of adding biases to the inputs. |
Raises | |
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ValueError |
If data_format is neither NHWC nor NCHW . |
ValueError |
If data_format is NCHW and rank of inputs is not 4. |
ValueError |
If the rank of inputs is undefined. |
ValueError |
If rank or C dimension of inputs is undefined. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/layers/bias_add