tensorflow/tensorflow/python/ops/linalg_ops_impl.py at master · codeplaysoftware/tensorflow · GitHub

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# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

# http://www.apache.org/licenses/LICENSE-2.0

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

# ==============================================================================

"""Operations for linear algebra."""

from __future__ import absolute_import

from __future__ import division

from __future__ import print_function

import numpy as np

from tensorflow.python.framework import dtypes

from tensorflow.python.framework import ops

from tensorflow.python.ops import array_ops

from tensorflow.python.ops import math_ops

from tensorflow.python.util import compat

# Names below are lower_case.

# pylint: disable=invalid-name

def eye(num_rows,

num_columns=None,

batch_shape=None,

dtype=dtypes.float32,

name=None):

"""Construct an identity matrix, or a batch of matrices.

See `linalg_ops.eye`.

"""

with ops.name_scope(

name, default_name='eye', values=[num_rows, num_columns, batch_shape]):

is_square = num_columns is None

batch_shape = [] if batch_shape is None else batch_shape

num_columns = num_rows if num_columns is None else num_columns

if isinstance(num_rows, ops.Tensor) or isinstance(

num_columns, ops.Tensor) or isinstance(batch_shape, ops.Tensor):

batch_shape = ops.convert_to_tensor(

batch_shape, name='shape', dtype=dtypes.int32)

diag_size = math_ops.minimum(num_rows, num_columns)

diag_shape = array_ops.concat((batch_shape, [diag_size]), 0)

if not is_square:

shape = array_ops.concat((batch_shape, [num_rows, num_columns]), 0)

else:

if not isinstance(num_rows, compat.integral_types) or not isinstance(

num_columns, compat.integral_types):

raise TypeError(

'num_rows and num_columns must be positive integer values.')

batch_shape = [dim for dim in batch_shape]

is_square = num_rows == num_columns

diag_shape = batch_shape + [np.minimum(num_rows, num_columns)]

if not is_square:

shape = batch_shape + [num_rows, num_columns]

diag_ones = array_ops.ones(diag_shape, dtype=dtype)

if is_square:

return array_ops.matrix_diag(diag_ones)

else:

zero_matrix = array_ops.zeros(shape, dtype=dtype)

return array_ops.matrix_set_diag(zero_matrix, diag_ones)

# pylint: enable=invalid-name,redefined-builtin

tensorflow/tensorflow/python/ops/linalg_ops_impl.py at master · codeplaysoftware/tensorflow · GitHub

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