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Initializer that generates tensors initialized to 1.
tf.compat.v1.keras.initializers.Ones(
dtype=tf.dtypes.float32
)
Migrate to TF2
This API is compatible with TF2 behavior and tf.function
, and can be
migrated immediately with tf.keras.initializers.ones
.
Before:
>>> initializer = tf.compat.v1.keras.initializers.ones()
>>> initializer((1, 1))
<tf.Tensor: shape=(1, 1), dtype=float32, numpy=array([[1.]], dtype=float32)>
After:
>>> initializer = tf.keras.initializers.ones()
>>> initializer((1, 1))
<tf.Tensor: shape=(1, 1), dtype=float32, numpy=array([[1.]], dtype=float32)>
Description
Methods
from_config
@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
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. |