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Initializer that generates tensors with a uniform distribution.
tf.compat.v1.random_uniform_initializer(
minval=0.0,
maxval=None,
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.RandomUniform
or tf.keras.initializers.RandomUniform
(neither from compat.v1
) and
pass the dtype when calling the initializer. Keep in mind that
the default minval, maxval and the behavior of fixed seeds have changed.
Structural Mapping to TF2
Before:
initializer = tf.compat.v1.random_uniform_initializer(
minval=minval,
maxval=maxval,
seed=seed,
dtype=dtype)
weight_one = tf.Variable(initializer(shape_one))
weight_two = tf.Variable(initializer(shape_two))
After:
initializer = tf.initializers.RandomUniform(
minval=minval,
maxval=maxval,
seed=seed)
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 |
---|---|---|
minval |
minval |
Default changes from 0 to -0.05 |
maxval |
maxval |
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 | |
---|---|
minval
|
A python scalar or a scalar tensor. Lower bound of the range of random values to generate. |
maxval
|
A python scalar or a scalar tensor. Upper bound of the range of random values to generate. Defaults to 1 for float types. |
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.
|
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. |