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meridian.backend.rank
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Returns the rank of a tensor.
meridian.backend.rank(
input, name=None
)
See also tf.shape.
Returns a 0-D int32 Tensor representing the rank of input.
For example:
# shape of tensor 't' is [2, 2, 3]
t = tf.constant([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]])
tf.rank(t) # 3
Note: The rank of a tensor is not the same as the rank of a matrix. The
rank of a tensor is the number of indices required to uniquely select each
element of the tensor. Rank is also known as "order", "degree", or "ndims."
Args |
|---|
input
|
A Tensor or SparseTensor.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor of type int32.
|
Equivalent to np.ndim
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Last updated 2025-09-05 UTC.
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