meridian.backend.rank

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."

numpy compatibility

Equivalent to np.ndim