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tf.linalg.inv

Computes the inverse of one or more square invertible matrices or their

Aliases:

  • tf.compat.v1.linalg.inv
  • tf.compat.v1.matrix_inverse
  • tf.compat.v2.linalg.inv
  • tf.linalg.inv
  • tf.matrix_inverse
tf.linalg.inv(
    input,
    adjoint=False,
    name=None
)

Defined in generated file: python/ops/gen_linalg_ops.py

adjoints (conjugate transposes).

The input is a tensor of shape [..., M, M] whose inner-most 2 dimensions form square matrices. The output is a tensor of the same shape as the input containing the inverse for all input submatrices [..., :, :].

The op uses LU decomposition with partial pivoting to compute the inverses.

If a matrix is not invertible there is no guarantee what the op does. It may detect the condition and raise an exception or it may simply return a garbage result.

Args:

  • input: A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128. Shape is [..., M, M].
  • adjoint: An optional bool. Defaults to False.
  • name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input.