View source on GitHub |
Creates a tensor filled with a scalar value.
tf.fill(
dims, value, name=None
)
See also tf.ones
, tf.zeros
, tf.one_hot
, tf.eye
.
This operation creates a tensor of shape dims
and fills it with value
.
For example:
tf.fill([2, 3], 9)
<tf.Tensor: shape=(2, 3), dtype=int32, numpy=
array([[9, 9, 9],
[9, 9, 9]], dtype=int32)>
tf.fill
evaluates at graph runtime and supports dynamic shapes based on
other runtime tf.Tensors
, unlike tf.constant(value, shape=dims)
, which
embeds the value as a Const
node.
Args | |
---|---|
dims
|
A 1-D sequence of non-negative numbers. Represents the shape of the
output tf.Tensor . Entries should be of type: int32 , int64 .
|
value
|
A value to fill the returned tf.Tensor .
|
name
|
Optional string. The name of the output tf.Tensor .
|
Returns | |
---|---|
A tf.Tensor with shape dims and the same dtype as value .
|
Raises | |
---|---|
InvalidArgumentError
|
dims contains negative entries.
|
NotFoundError
|
dims contains non-integer entries.
|
numpy compatibility
Similar to np.full
. In numpy
, more parameters are supported. Passing a
number argument as the shape (np.full(5, value)
) is valid in numpy
for
specifying a 1-D shaped result, while TensorFlow does not support this syntax.