Initializer that generates tensors with constant values.
tf.compat.v1.keras.initializers.Constant( value=0, dtype=tf.dtypes.float32, verify_shape=False )
The resulting tensor is populated with values of type dtype
, as specified by arguments value
following the desired shape
of the new tensor (see examples below).
The argument value
can be a constant value, or a list of values of type dtype
. If value
is a list, then the length of the list must be less than or equal to the number of elements implied by the desired shape of the tensor. In the case where the total number of elements in value
is less than the number of elements required by the tensor shape, the last element in value
will be used to fill the remaining entries. If the total number of elements in value
is greater than the number of elements required by the tensor shape, the initializer will raise a ValueError
.
Args | |
---|---|
value | A Python scalar, list or tuple of values, or a N-dimensional numpy array. All elements of the initialized variable will be set to the corresponding value in the value argument. |
dtype | Default data type, used if no dtype argument is provided when calling the initializer. |
verify_shape | Boolean that enables verification of the shape of value . If True , the initializer will throw an error if the shape of value is not compatible with the shape of the initialized tensor. |
Raises | |
---|---|
TypeError | If the input value is not one of the expected types. |
The following example can be rewritten using a numpy.ndarray instead of the value
list, even reshaped, as shown in the two commented lines below the value
list initialization.
value = [0, 1, 2, 3, 4, 5, 6, 7] init = tf.compat.v1.constant_initializer(value) # fitting shape with tf.compat.v1.Session(): x = tf.compat.v1.get_variable('x', shape=[2, 4], initializer=init) x.initializer.run() print(x.eval()) [[0. 1. 2. 3.] [4. 5. 6. 7.]] # Larger shape with tf.compat.v1.Session(): y = tf.compat.v1.get_variable('y', shape=[3, 4], initializer=init) y.initializer.run() print(y.eval()) [[0. 1. 2. 3.] [4. 5. 6. 7.] [7. 7. 7. 7.]] # Smaller shape with tf.compat.v1.Session(): z = tf.compat.v1.get_variable('z', shape=[2, 3], initializer=init) Traceback (most recent call last): ValueError: Too many elements provided. Needed at most 6, but received 8 # Shape verification init_verify = tf.compat.v1.constant_initializer(value, verify_shape=True) with tf.compat.v1.Session(): u = tf.compat.v1.get_variable('u', shape=[3, 4], initializer=init_verify) Traceback (most recent call last): TypeError: Expected Tensor's shape: (3, 4), got (8,).
from_config
@classmethod from_config( config )
Instantiates an initializer from a configuration dictionary.
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, verify_shape=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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/keras/initializers/Constant