aliran tensor:: operasi:: MatriksSetDiagV2

#include <array_ops.h>

Mengembalikan tensor matriks batch dengan nilai diagonal batch baru.

Ringkasan

Mengingat input dan diagonal , operasi ini mengembalikan tensor dengan bentuk dan nilai yang sama dengan input , kecuali untuk diagonal tertentu dari matriks terdalam. Ini akan ditimpa oleh nilai-nilai di diagonal .

input memiliki dimensi r+1 [I, J, ..., L, M, N] . Jika k adalah skalar atau k[0] == k[1] , diagonal memiliki r dimensi [I, J, ..., L, max_diag_len] . Jika tidak, ia memiliki dimensi r+1 [I, J, ..., L, num_diags, max_diag_len] . num_diags adalah jumlah diagonal, num_diags = k[1] - k[0] + 1 . max_diag_len adalah diagonal terpanjang dalam rentang [k[0], k[1]] , max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))

Outputnya adalah tensor rank k+1 dengan dimensi [I, J, ..., L, M, N] . Jika k adalah skalar atau 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

Jika tidak, 

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
 di mana d = n - m , diag_index = k[1] - d , dan index_in_diag = n - max(d, 0) .

Misalnya: 

# 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
 keluaran 
::tensorflow::Output output
 Fungsi publik 
 MatriksSetDiagV2 
 MatrixSetDiagV2(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input diagonal,
  ::tensorflow::Input k
)
 simpul 
::tensorflow::Node * node() const 
 operator::tensorflow::Masukan 
 operator::tensorflow::Input() const 
 operator::tensorflow::Keluaran 
 operator::tensorflow::Output() const