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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
)
Migrate to TF2
Although it is a legacy compat.v1 API, this symbol is compatible with eager execution and tf.function.
To switch to TF2, switch to using either tf.initializers.RandomNormal or tf.keras.initializers.RandomNormal (neither from compat.v1) and pass the dtype when calling the initializer. Keep in mind that the default stddev and the behavior of fixed seeds have changed.
Structural Mapping to TF2
Before:
initializer = tf.compat.v1.random_normal_initializer(
mean=mean,
stddev=stddev,
seed=seed,
dtype=dtype)
weight_one = tf.Variable(initializer(shape_one))
weight_two = tf.Variable(initializer(shape_two))
After:
initializer = tf.initializers.RandomNormal(
mean=mean,
seed=seed,
stddev=stddev)
weight_one = tf.Variable(initializer(shape_one, dtype=dtype))
weight_two = tf.Variable(initializer(shape_two, dtype=dtype))
How to Map Arguments
| TF1 Arg Name | TF2 Arg Name | Note |
|---|---|---|
mean | mean | No change to defaults |
stddev | stddev | Default changes from 1.0 to 0.05 |
seed | seed | |
dtype | dtype | The TF2 native api only takes it as a __call__ arg, not a constructor arg. |
partition_info | - | (__call__ arg in TF1) Not supported. |
Description
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.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. |
Methods
from_config
@classmethodfrom_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
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. |