# Copyright 2017 Google Inc.
#
# 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.
# ==============================================================================
"""DNC util ops and modules."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import numpy as np
import tensorflow as tf


def batch_invert_permutation(permutations):
  """Returns batched `tf.invert_permutation` for every row in `permutations`."""
  with tf.name_scope('batch_invert_permutation', values=[permutations]):
    unpacked = tf.unstack(permutations)
    inverses = [tf.invert_permutation(permutation) for permutation in unpacked]
    return tf.stack(inverses)


def batch_gather(values, indices):
  """Returns batched `tf.gather` for every row in the input."""
  with tf.name_scope('batch_gather', values=[values, indices]):
    unpacked = zip(tf.unstack(values), tf.unstack(indices))
    result = [tf.gather(value, index) for value, index in unpacked]
    return tf.stack(result)


def one_hot(length, index):
  """Return an nd array of given `length` filled with 0s and a 1 at `index`."""
  result = np.zeros(length)
  result[index] = 1
  return result