# tf.contrib.framework.convolutional_delta_orthogonal

## Class convolutional_delta_orthogonal

Inherits From: Initializer

Defined in tensorflow/python/ops/init_ops.py.

Initializer that generates a delta orthogonal kernel for ConvNets.

The shape of the tensor must have length 3, 4 or 5. The number of input filters must not exceed the number of output filters. The center pixels of the tensor form an orthogonal matrix. Other pixels are set to be zero.

#### Args:

• gain: multiplicative factor to apply to the orthogonal matrix. Default is 1. The 2-norm of an input is multiplied by a factor of 'sqrt(gain)' after applying this convolution.
• dtype: The type of the output.
• seed: A Python integer. Used to create random seeds. See tf.set_random_seed for behavior.

## Methods

### __init__

__init__(
gain=1.0,
seed=None,
dtype=tf.float32
)


### __call__

__call__(
shape,
dtype=None,
partition_info=None
)


### from_config

from_config(
cls,
config
)


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

get_config()