Creates a constant tensor.
tf.compat.v2.constant( value, dtype=None, shape=None, name='Const' )
The resulting tensor is populated with values of type dtype
, as specified by arguments value
and (optionally) shape
(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 shape
argument (if specified). In the case where the list length is less than the number of elements specified by shape
, the last element in the list will be used to fill the remaining entries.
The argument shape
is optional. If present, it specifies the dimensions of the resulting tensor. If not present, the shape of value
is used.
If the argument dtype
is not specified, then the type is inferred from the type of value
.
# Constant 1-D Tensor populated with value list. tensor = tf.constant([1, 2, 3, 4, 5, 6]) => [1 2 3 4 5 6] # Constant 1-D Tensor populated with value list. tensor = tf.constant([1, 2, 3, 4, 5, 6], shape=(2,3)) => [[1 2 3], [4 5 6]] # Constant 2-D tensor populated with scalar value -1. tensor = tf.constant(-1.0, shape=[2, 3]) => [[-1. -1. -1.] [-1. -1. -1.]]
tf.constant
differs from tf.fill
in a few ways:
tf.constant
supports arbitrary constants, not just uniform scalar Tensors like tf.fill
.tf.constant
creates a Const
node in the computation graph with the exact value at graph construction time. On the other hand, tf.fill
creates an Op in the graph that is expanded at runtime.tf.constant
only embeds constant values in the graph, it does not support dynamic shapes based on other runtime Tensors, whereas tf.fill
does.Args | |
---|---|
value | A constant value (or list) of output type dtype . |
dtype | The type of the elements of the resulting tensor. |
shape | Optional dimensions of resulting tensor. |
name | Optional name for the tensor. |
Returns | |
---|---|
A Constant Tensor. |
Raises | |
---|---|
TypeError | if shape is incorrectly specified or unsupported. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/compat/v2/constant