tf.shape_n
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Returns shape of a list of tensors.
tf.shape_n(
input,
out_type=tf.dtypes.int32
,
name=None
)
Given a list of tensors, tf.shape_n
is much faster than applying tf.shape
to each tensor individually.
>>> a = tf.ones([1, 2])
>>> b = tf.ones([2, 3])
>>> c = tf.ones([3, 4])
>>> tf.shape_n([a, b, c])
[<tf.Tensor: shape=(2,), dtype=int32, numpy=array([1, 2], dtype=int32)>,
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([2, 3], dtype=int32)>,
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([3, 4], dtype=int32)>]
Args |
input
|
A list of at least 1 Tensor object with the same dtype.
|
out_type
|
The specified output type of the operation (int32 or int64 ).
Defaults to tf.int32 (optional).
|
name
|
A name for the operation (optional).
|
Returns |
A list of Tensor specifying the shape of each input tensor with type of
out_type .
|
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Last updated 2023-10-06 UTC.
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