tensorflow:: ops:: MatrixSetDiagV2

#include <array_ops.h>

Returns a batched matrix tensor with new batched diagonal values.

Summary

Given input and diagonal , this operation returns a tensor with the same shape and values as input , except for the specified diagonals of the innermost matrices. These will be overwritten by the values in diagonal .

input has r+1 dimensions [I, J, ..., L, M, N] . When k is scalar or k[0] == k[1] , diagonal has r dimensions [I, J, ..., L, max_diag_len] . Otherwise, it has r+1 dimensions [I, J, ..., L, num_diags, max_diag_len] . num_diags is the number of diagonals, num_diags = k[1] - k[0] + 1 . max_diag_len is the longest diagonal in the range [k[0], k[1]] , max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))

The output is a tensor of rank k+1 with dimensions [I, J, ..., L, M, N] . If k is scalar or k[0] == k[1] : 

output[i, j, ..., l, m, n]
  = diagonal[i, j, ..., l, n-max(k[1], 0)] ; if n - m == k[1]
    input[i, j, ..., l, m, n]              ; otherwise

Otherwise, 

output[i, j, ..., l, m, n]
  = diagonal[i, j, ..., l, diag_index, index_in_diag] ; if k[0] <= d <= k[1]
    input[i, j, ..., l, m, n]                         ; otherwise
 where d = n - m , diag_index = k[1] - d , and index_in_diag = n - max(d, 0) .

For example: 

# The main diagonal.
input = np.array([[[7, 7, 7, 7],              # Input shape: (2, 3, 4)
                   [7, 7, 7, 7],
                   [7, 7, 7, 7]],
                  [[7, 7, 7, 7],
                   [7, 7, 7, 7],
                   [7, 7, 7, 7]]])
diagonal = np.array([[1, 2, 3],               # Diagonal shape: (2, 3)
                     [4, 5, 6]])
tf.matrix_set_diag(diagonal) ==> [[[1, 7, 7, 7],  # Output shape: (2, 3, 4)
                                   [7, 2, 7, 7],
                                   [7, 7, 3, 7]],
                                  [[4, 7, 7, 7],
                                   [7, 5, 7, 7],
                                   [7, 7, 6, 7]]]
 

# A superdiagonal (per batch).
tf.matrix_set_diag(diagonal, k = 1)
  ==> [[[7, 1, 7, 7],  # Output shape: (2, 3, 4)
        [7, 7, 2, 7],
        [7, 7, 7, 3]],
       [[7, 4, 7, 7],
        [7, 7, 5, 7],
        [7, 7, 7, 6]]]
 

# A band of diagonals.
diagonals = np.array([[[1, 2, 3],  # Diagonal shape: (2, 2, 3)
                       [4, 5, 0]],
                      [[6, 1, 2],
                       [3, 4, 0]]])
tf.matrix_set_diag(diagonals, k = (-1, 0))
  ==> [[[1, 7, 7, 7],  # Output shape: (2, 3, 4)
        [4, 2, 7, 7],
        [0, 5, 3, 7]],
       [[6, 7, 7, 7],
        [3, 1, 7, 7],
        [7, 4, 2, 7]]]
 


  

  

   Args:
   
    
    
  • 
     scope: A
     
      Scope
     
     object
    
    • 
    
  • 
     input: Rank
     
      r+1
     
     , where
     
      r >= 1
     
     .
    
    • 
    
  • 
     diagonal: Rank
     
      r
     
     when
     
      k
     
     is an integer or
     
      k[0] == k[1]
     
     . Otherwise, it has rank
     
      r+1
     
     .
     
      k >= 1
     
     .
    
    • 
    
  • 
     k: Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main diagonal, and negative value means subdiagonals.
     
      k
     
     can be a single integer (for a single diagonal) or a pair of integers specifying the low and high ends of a matrix band.
     
      k[0]
     
     must not be larger than
     
      k[1]
     
     .
    
    • 
   

  

  

   Returns:
   
    
    
  • 
     
      
       Output
      
     
     : Rank
     
      r+1
     
     , with
     
      output.shape = input.shape
     
     .
    
    • 
   

  

  

   

    
     

      Constructors and Destructors
     

    		
   

   

    
     
      
       MatrixSetDiagV2
      
      (const ::
      
       tensorflow::Scope
      
      & scope, ::
      
       tensorflow::Input
      
      input, ::
      
       tensorflow::Input
      
      diagonal, ::
      
       tensorflow::Input
      
      k)
     
     

    		
   

  

  

   

    
     

      Public attributes
     

    		
   

   

    
     
      
       operation
      
     
    
    
     
    
   

   

    
     
      
       output
      
     
    
    
     
    
   

  

  

   

    
     

      Public functions
     

    		
   

   

    
     
      
       node
      
      () const
     
    
    
     

      
       ::tensorflow::Node *
      
     

    		
   

   

    
     
      
       operator::tensorflow::Input
      
      () const
     
    
    
     

      
      
     

    		
   

   

    
     
      
       operator::tensorflow::Output
      
      () const
     
    
    
     

      
      
     

    		
   

  

  

   Public attributes
  

  

   

    operation
   

   
Operation operation

   

   

  

  

   

    output
   

   
::tensorflow::Output output

   

   

  

  

   Public functions
  

  

   

    MatrixSetDiagV2
   

   
 MatrixSetDiagV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input diagonal,
  ::tensorflow::Input k
)

   

   

  

  

   

    node
   

   
::tensorflow::Node * node() const 

   

   

  

  

   

    operator::tensorflow::Input
   

   
 operator::tensorflow::Input() const 

   

   

  

  

   

    operator::tensorflow::Output
   

   
 operator::tensorflow::Output() const