tf.random_normal_initializer
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Initializer that generates tensors with a normal distribution.
tf.random_normal_initializer(
mean=0.0, stddev=0.05, seed=None
)
Used in the notebooks
Initializers allow you to pre-specify an initialization strategy, encoded in
the Initializer object, without knowing the shape and dtype of the variable
being initialized.
Examples:
def make_variables(k, initializer):
return (tf.Variable(initializer(shape=[k], dtype=tf.float32)),
tf.Variable(initializer(shape=[k, k], dtype=tf.float32)))
v1, v2 = make_variables(3,
tf.random_normal_initializer(mean=1., stddev=2.))
v1
<tf.Variable ... shape=(3,) ... numpy=array([...], dtype=float32)>
v2
<tf.Variable ... shape=(3, 3) ... numpy=
make_variables(4, tf.random_uniform_initializer(minval=-1., maxval=1.))
(<tf.Variable...shape=(4,) dtype=float32...>, <tf.Variable...shape=(4, 4) ...
Args |
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.random.set_seed for behavior.
|
Methods
from_config
View source
@classmethod
from_config(
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
View source
get_config()
Returns the configuration of the initializer as a JSON-serializable dict.
Returns |
A JSON-serializable Python dict.
|
__call__
View source
__call__(
shape,
dtype=tf.dtypes.float32
,
**kwargs
)
Returns a tensor object initialized as specified by the initializer.
Args |
shape
|
Shape of the tensor.
|
dtype
|
Optional dtype of the tensor. Only floating point types are
supported.
|
**kwargs
|
Additional keyword arguments.
|
Raises |
ValueError
|
If the dtype is not floating point
|
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Last updated 2024-04-26 UTC.
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