tf.compat.v1.ones_initializer | TensorFlow v2.16.1 (original) (raw)

Initializer that generates tensors initialized to 1.

View aliases

Compat aliases for migration

tf.compat.v1.initializers.ones

tf.compat.v1.ones_initializer(
    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

Used in the notebooks

Used in the guide
Use TF1.x models in TF2 workflows

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 ofget_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=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.