class tf.orthogonal_initializer

See the guide: Variables > Sharing Variables

Initializer that generates an orthogonal matrix.

If the shape of the tensor to initialize is two-dimensional, i is initialized with an orthogonal matrix obtained from the singular value decomposition of a matrix of uniform random numbers.

If the shape of the tensor to initialize is more than two-dimensional, a matrix of shape (shape[0] * ... * shape[n - 2], shape[n - 1]) is initialized, where n is the length of the shape vector. The matrix is subsequently reshaped to give a tensor of the desired shape.


  • gain: multiplicative factor to apply to the orthogonal matrix
  • dtype: The type of the output.
  • seed: A Python integer. Used to create random seeds. See tf.set_random_seed for behavior.


__init__(gain=1.0, dtype=tf.float32, seed=None)

Defined in tensorflow/python/ops/