tensoreflusso:: ops:: MatrixSetDiagV2

#include <array_ops.h>

Restituisce un tensore di matrice in batch con nuovi valori diagonali in batch.

Riepilogo

Dati input e diagonal , questa operazione restituisce un tensore con la stessa forma e gli stessi valori di input , ad eccezione delle diagonali specificate delle matrici più interne. Questi verranno sovrascritti dai valori in diagonal .

input ha r+1 dimensioni [I, J, ..., L, M, N] . Quando k è scalare o k[0] == k[1] , diagonal ha r dimensioni [I, J, ..., L, max_diag_len] . Altrimenti, ha r+1 dimensioni [I, J, ..., L, num_diags, max_diag_len] . num_diags è il numero di diagonali, num_diags = k[1] - k[0] + 1 . max_diag_len è la diagonale più lunga nell'intervallo [k[0], k[1]] , max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))

L'output è un tensore di rango k+1 con dimensioni [I, J, ..., L, M, N] . Se k è scalare o 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

Altrimenti,

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
dove d = n - m , diag_index = k[1] - d e index_in_diag = n - max(d, 0) .

Per esempio: 

# 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]]]

  

  
Arguments:
    
      
  • 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
 produzione 
 
::tensorflow::Output output
 Funzioni pubbliche 
 MatrixSetDiagV2 
 
 MatrixSetDiagV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input diagonal,
  ::tensorflow::Input k
)
 nodo 
 
::tensorflow::Node * node() const 
 operatore::tensorflow::Input 
 
 operator::tensorflow::Input() const 
 operatore::tensorflow::Output
 
 operator::tensorflow::Output() const