Initializer that generates tensors with a uniform distribution.
tf . random_uniform_initializer (
minval =- 0.05 , maxval = 0.05 , seed = None
)
Initializers allow you to pre-specify an initialization strategy, encoded in
the Initializer object, without knowing the shape and dtype of the variable
being initialized.
Examples:
def make_variables ( k , initializer ):
return ( tf . Variable ( initializer ( shape = [ k ], dtype = tf . float32 )),
tf . Variable ( initializer ( shape = [ k , k ], dtype = tf . float32 )))
v1 , v2 = make_variables ( 3 , tf . ones_initializer ())
v1
<tf . Variable ... shape = ( 3 ,) ... numpy = array ([ 1. , 1. , 1. ], dtype = float32 ) >
v2
<tf . Variable ... shape = ( 3 , 3 ) ... numpy =
array ([[ 1. , 1. , 1. ],
[ 1. , 1. , 1. ],
[ 1. , 1. , 1. ]], dtype = float32 ) >
make_variables ( 4 , tf . random_uniform_initializer ( minval =- 1. , maxval = 1. ))
( <tf . Variable ... shape = ( 4 ,) dtype = float32 ... >, <tf . Variable ... shape = ( 4 , 4 ) ...
Args
minval
A python scalar or a scalar tensor. Lower bound of the range of
random values to generate (inclusive).
maxval
A python scalar or a scalar tensor. Upper bound of the range of
random values to generate (exclusive).
seed
A Python integer. Used to create random seeds. See
tf.random.set_seed
for behavior.
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 of get_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 = tf . dtypes . float32
,
** kwargs
)
Returns a tensor object initialized as specified by the initializer.
Args
shape
Shape of the tensor.
dtype
Optional dtype of the tensor. Only floating point and integer
types are supported.
**kwargs
Additional keyword arguments.
Raises
ValueError
If the dtype is not numeric.