Initializer that generates tensors with a normal distribution.
tf.compat.v1.random_normal_initializer( mean=0.0, stddev=1.0, seed=None, dtype=tf.dtypes.float32 )
Args | |
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mean | a python scalar or a scalar tensor. Mean of the random values to generate. |
stddev | a python scalar or a scalar tensor. Standard deviation of the random values to generate. |
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. |
from_config
@classmethod from_config( config )
Instantiates an initializer from a configuration dictionary.
initializer = RandomUniform(-1, 1) config = initializer.get_config() initializer = RandomUniform.from_config(config)
Args | |
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config | A Python dictionary. It will typically be the output of get_config . |
Returns | |
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An Initializer instance. |
get_config
get_config()
Returns the configuration of the initializer as a JSON-serializable dict.
Returns | |
---|---|
A JSON-serializable Python dict. |
__call__
__call__( shape, dtype=None, partition_info=None )
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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/random_normal_initializer