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

tf.compat.v1.zeros_initializer

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Initializer that generates tensors initialized to 0.

View aliases

Compat aliases for migration

SeeMigration guide for more details.

tf.compat.v1.initializers.zeros

tf.compat.v1.zeros_initializer(
    dtype=tf.dtypes.float32
)

Migrate to TF2

tf.compat.v1.zeros_initializer is compatible with eager execution and tf.function.

To migrate to TF2, please use tf.zeros_initializer instead. The dtypeargument in tf.compat.v1.zeros_initializer._ init_() does not exist intf.zeros_initializer._ init_(). However, you can specify the dtype in__call__() in both cases.

Structural Mapping to TF2

Before:

initializer = tf.compat.v1.zeros_initializer(dtype=tf.float32)
variable = tf.Variable(initializer(shape=[3, 3]))

After:

initializer = tf.zeros_initializer()
variable = tf.Variable(initializer(shape=[3, 3], dtype=tf.float32))

How to Map Arguments

TF1 Arg Name TF2 Arg Name Note
dtype dtype In __call__() method
partition_info - (__call__ arg in TF1) Not supported

Before & After Usage Example

Before:

initializer = tf.compat.v1.zeros_initializer(dtype=tf.float32) tf.Variable(initializer(shape=[3])).numpy() array([0., 0., 0.], dtype=float32) tf.Variable(initializer(shape=[3, 3])).numpy() array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]], dtype=float32) initializer = tf.compat.v1.zeros_initializer() tf.Variable(initializer(shape=[3], dtype=tf.float32)).numpy() array([0., 0., 0.], dtype=float32) tf.Variable(initializer(shape=[3, 3], dtype=tf.float32)).numpy() array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]], dtype=float32)

After:

initializer = tf.zeros_initializer() tf.Variable(initializer(shape=[3], dtype=tf.float32)).numpy() array([0., 0., 0.], dtype=float32) tf.Variable(initializer(shape=[3, 3], dtype=tf.float32)).numpy() array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]], dtype=float32)

Description

Used in the notebooks

Used in the guide
Migrating model checkpoints

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.