Module: TensorFlow::Linalg

Defined in:
lib/tensorflow/linalg.rb

Class Method Summary collapse

Class Method Details

.cholesky(input) ⇒ Object

def band_part end



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# File 'lib/tensorflow/linalg.rb', line 10

def cholesky(input)
  RawOps.cholesky(input: input)
end

.cross(a, b) ⇒ Object

def cholesky_solve end



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# File 'lib/tensorflow/linalg.rb', line 17

def cross(a, b)
  RawOps.cross(a: a, b: b)
end

.diag(diagonal) ⇒ Object

def det end



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# File 'lib/tensorflow/linalg.rb', line 24

def diag(diagonal)
  RawOps.diag(diagonal: diagonal)
end

.diag_part(input) ⇒ Object 



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# File 'lib/tensorflow/linalg.rb', line 28

def diag_part(input)
  RawOps.diag_part(input: input)
end

.eye(num_rows, num_columns: nil) ⇒ Object

def expm end



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# File 'lib/tensorflow/linalg.rb', line 44

def eye(num_rows, num_columns: nil)
  num_columns ||= num_rows
  zeros = TensorFlow.zeros([num_rows, num_columns])
  ones = TensorFlow.ones([num_rows])
  RawOps.matrix_set_diag(input: zeros, diagonal: ones)
end

.inv(x) ⇒ Object

def global_norm end



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# File 'lib/tensorflow/linalg.rb', line 54

def inv(x)
  RawOps.inv(x: x)
end

.lu(input, output_idx_type: nil) ⇒ Object

def lstsq end



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# File 'lib/tensorflow/linalg.rb', line 70

def lu(input, output_idx_type: nil)
  RawOps.lu(input: input, output_idx_type: output_idx_type)
end

.matmul(a, b, transpose_a: false, transpose_b: false) ⇒ Object 



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# File 'lib/tensorflow/linalg.rb', line 74

def matmul(a, b, transpose_a: false, transpose_b: false)
  RawOps.mat_mul(a: a, b: b, transpose_a: transpose_a, transpose_b: transpose_b)
end

.qr(input, full_matrices: nil) ⇒ Object

def normalize end



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# File 'lib/tensorflow/linalg.rb', line 90

def qr(input, full_matrices: nil)
  RawOps.qr(input: input, full_matrices: full_matrices)
end

.svd(input, compute_uv: nil, full_matrices: nil) ⇒ Object

def sqrtm end



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# File 'lib/tensorflow/linalg.rb', line 106

def svd(input, compute_uv: nil, full_matrices: nil)
  RawOps.svd(input: input, compute_uv: compute_uv, full_matrices: full_matrices)
end

.tridiagonal_solve(diagonals, rhs, partial_pivoting: nil) ⇒ Object

def tridiagonal_matmul end



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# File 'lib/tensorflow/linalg.rb', line 128

def tridiagonal_solve(diagonals, rhs, partial_pivoting: nil)
  RawOps.tridiagonal_solve(diagonals: diagonals, rhs: rhs, partial_pivoting: partial_pivoting)
end