330154d9f5344f0a6ab39b3a313626c4b574dbbd,kronecker.py,,determinant,#Any#,6

Before Change

  for core_idx in range(kron_a.ndims()):
    core = cores[core_idx]
    core_det = tf.matrix_determinant(core[0, :, :, 0])
    core_pow = pows / core.get_shape()[1].value

    det *= tf.pow(core_det, core_pow)
  return det

After Change

  else:
    i_shapes = raw_shape(kron_a)[0]

  if shapes_defined:
    if i_shapes != j_shapes:
      raise ValueError("The argument should be a Kronecker product of square "
                       "matrices (tt-cores must be square)")
      
  pows = tf.cast(tf.reduce_prod(i_shapes), kron_a.dtype)
  cores = kron_a.tt_cores
  det = 1
  for core_idx in range(kron_a.ndims()):

Instances