텐서플로우:: 작전:: MatrixSetDiagV3

#include <array_ops.h>

새로운 배치 대각선 값을 갖는 배치 행렬 텐서를 반환합니다.

요약

input 및 diagonal 주어지면 이 연산은 가장 안쪽 행렬의 지정된 대각선을 제외하고 input 과 동일한 모양 및 값을 가진 텐서를 반환합니다. 이는 diagonal 값으로 덮어쓰여집니다.

input r+1 차원 [I, J, ..., L, M, N] 이 있습니다. k 가 스칼라이거나 k[0] == k[1] 인 경우 diagonal r 차원 [I, J, ..., L, max_diag_len] 을 갖습니다. 그렇지 않으면 r+1 차원 [I, J, ..., L, num_diags, max_diag_len] 을 갖습니다. num_diags 는 대각선 수입니다. num_diags = k[1] - k[0] + 1 . max_diag_len [k[0], k[1]] 범위에서 가장 긴 대각선입니다 max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))

출력은 [I, J, ..., L, M, N] 차원을 갖는 k+1 순위의 텐서입니다. k 가 스칼라이거나 k[0] == k[1] 인 경우: 

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

그렇지 않으면, 

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
 여기서 d = n - m , diag_index = k[1] - d 및 index_in_diag = n - max(d, 0) + offset .

대각선 정렬이 오른쪽인 경우를 제외하고 offset 은 0입니다.

offset = max_diag_len - diag_len(d) ; if (`align` in {RIGHT_LEFT, RIGHT_RIGHT}
                                           and `d >= 0`) or
                                         (`align` in {LEFT_RIGHT, RIGHT_RIGHT}
                                           and `d <= 0`)
         0                          ; otherwise
 여기서 diag_len(d) = min(cols - max(d, 0), rows + min(d, 0)) .

예를 들어: 

# 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(input, 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(input, 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([[[0, 9, 1],  # Diagonal shape: (2, 4, 3)
                       [6, 5, 8],
                       [1, 2, 3],
                       [4, 5, 0]],
                      [[0, 1, 2],
                       [5, 6, 4],
                       [6, 1, 2],
                       [3, 4, 0]]])
tf.matrix_set_diag(input, diagonals, k = (-1, 2))
  ==> [[[1, 6, 9, 7],  # Output shape: (2, 3, 4)
        [4, 2, 5, 1],
        [7, 5, 3, 8]],
       [[6, 5, 1, 7],
        [3, 1, 6, 2],
        [7, 4, 2, 4]]]

# LEFT_RIGHT alignment.
diagonals = np.array([[[9, 1, 0],  # Diagonal shape: (2, 4, 3)
                       [6, 5, 8],
                       [1, 2, 3],
                       [0, 4, 5]],
                      [[1, 2, 0],
                       [5, 6, 4],
                       [6, 1, 2],
                       [0, 3, 4]]])
tf.matrix_set_diag(input, diagonals, k = (-1, 2), align="LEFT_RIGHT")
  ==> [[[1, 6, 9, 7],  # Output shape: (2, 3, 4)
        [4, 2, 5, 1],
        [7, 5, 3, 8]],
       [[6, 5, 1, 7],
        [3, 1, 6, 2],
        [7, 4, 2, 4]]]

  

  
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].
    • 
    

  
Optional attributes (see Attrs):
    
      
  • align: Some diagonals are shorter than max_diag_len and need to be padded. align is a string specifying how superdiagonals and subdiagonals should be aligned, respectively. There are four possible alignments: "RIGHT_LEFT" (default), "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals to the right (left-pads the row) and subdiagonals to the left (right-pads the row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is the opposite alignment.
    • 
    

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

                                              




        
Constructors and Destructors

      		





        MatrixSetDiagV3(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input diagonal, ::tensorflow::Input k)
        

      		





        MatrixSetDiagV3(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input diagonal, ::tensorflow::Input k, const MatrixSetDiagV3::Attrs & attrs)
        

      		




                                                          




        
Public attributes

      		





        operation
      

        
      





        output
      

        
      




                                                                              




        
Public functions

      		





        node() const 
      

        

          ::tensorflow::Node *
        

      		





        operator::tensorflow::Input() const 
      

        

          
        

      		





        operator::tensorflow::Output() const 
      

        

          
        

      		




                                      




        
Public static functions

      		





        Align(StringPiece x)
      

        
      




                                      




        
Structs

      		





        tensorflow::ops::MatrixSetDiagV3::Attrs
      

        
Optional attribute setters for MatrixSetDiagV3. 

      		




  
Public attributes

  

    
operation

    
Operation operation
 산출 
::tensorflow::Output output
 공공 기능 
 MatrixSetDiagV3 
 MatrixSetDiagV3(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input diagonal,
  ::tensorflow::Input k
)
 MatrixSetDiagV3 
 MatrixSetDiagV3(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input,
  ::tensorflow::Input diagonal,
  ::tensorflow::Input k,
  const MatrixSetDiagV3::Attrs & attrs
)
 마디 
::tensorflow::Node * node() const 
 연산자::텐서플로우::입력 
 operator::tensorflow::Input() const 
 연산자::텐서플로우::출력 
 operator::tensorflow::Output() const 
 공개 정적 함수 
 맞추다 
Attrs Align(
  StringPiece x
)