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tf.contrib.framework.convolutional_orthogonal_1d

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Initializer that generates a 1D orthogonal kernel for ConvNets.

The shape of the tensor must have length 3. The number of input filters must not exceed the number of output filters. The orthogonality(==isometry) is exact when the inputs are circular padded. There are finite-width effects with non-circular padding (e.g. zero padding). See algorithm 1 in (Xiao et al., 2018).

gain Multiplicative factor to apply to the orthogonal matrix. Default is 1. The 2-norm of an input is multiplied by a factor of gain after applying this convolution.
seed A Python integer. Used to create random seeds. See tf.compat.v1.set_random_seed for behavior.
dtype Default data type, used if no dtype argument is provided when calling the initializer. Only floating point types are supported.

References:

Xiao et al., 2018 (pdf)

Methods

from_config

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Instantiates an initializer from a configuration dictionary.

Example:

initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)

Args
config A Python dictionary. It will typically be the output of get_config.

Returns
An Initializer instance.

get_config

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Returns the configuration of the initializer as a JSON-serializable dict.

Returns
A JSON-serializable Python dict.

__call__

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Returns a tensor object initialized as specified by the initializer.

Args
shape Shape of the tensor.
dtype Optional dtype of the tensor. If not provided use the initializer dtype.
partition_info Optional information about the possible partitioning of a tensor.