# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Tests for tensorflow.ops.tf.gather."""

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

from absl.testing import parameterized
import numpy as np

from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test

_TEST_TYPES = (dtypes.int64, dtypes.float32,
               dtypes.complex64, dtypes.complex128)


class GatherTest(test.TestCase, parameterized.TestCase):

  def _buildParams(self, data, dtype):
    data = data.astype(dtype.as_numpy_dtype)
    # For complex types, add an index-dependent imaginary component so we can
    # tell we got the right value.
    if dtype.is_complex:
      return data + 10j * data
    return data

  @parameterized.parameters(dtypes.int32, dtypes.int64)
  def testSimpleGather(self, indices_dtype):
    data = np.array([0, 1, 2, 3, 7, 5, 8, 9, 10, 11, 15, 13])
    indices = [3, 4]
    with self.test_session(use_gpu=True):
      for dtype in _TEST_TYPES:
        params_np = self._buildParams(data, dtype)
        params = constant_op.constant(params_np)
        indices_tf = constant_op.constant(indices, dtype=indices_dtype)
        gather_t = array_ops.batch_gather(params, indices_tf)
        expected_result = np.array([3, 7])
        np_val = self._buildParams(expected_result, dtype)
        gather_val = gather_t.eval()
        self.assertAllEqual(np_val, gather_val)
        self.assertEqual(np_val.shape, gather_t.get_shape())

  @parameterized.parameters(dtypes.int32, dtypes.int64)
  def test2DArray(self, indices_dtype):
    data = np.array([[0, 1, 2, 3, 7, 5], [8, 9, 10, 11, 15, 13]])
    indices = [[3], [4]]
    with self.test_session(use_gpu=True):
      for dtype in _TEST_TYPES:
        params_np = self._buildParams(data, dtype)
        params = constant_op.constant(params_np)
        indices_tf = constant_op.constant(indices, dtype=indices_dtype)
        gather_t = array_ops.batch_gather(params, indices_tf)
        expected_result = np.array([[3], [15]])
        np_val = self._buildParams(expected_result, dtype)
        gather_val = gather_t.eval()
        self.assertAllEqual(np_val, gather_val)
        self.assertEqual(np_val.shape, gather_t.get_shape())

  def testHigherRank(self):
    data = np.array([[[0, 1, 2], [3, 7, 5]], [[8, 9, 10], [11, 15, 13]]])
    indices = [[[2, 0], [1, 2]], [[2, 0], [0, 1]]]
    with self.test_session(use_gpu=True):
      for dtype in _TEST_TYPES:
        params_np = self._buildParams(data, dtype)
        params = constant_op.constant(params_np)
        indices_tf = constant_op.constant(indices)
        gather_t = array_ops.batch_gather(params, indices_tf)
        gather_val = gather_t.eval()
        expected_result = np.array([[[2, 0], [7, 5]], [[10, 8], [11, 15]]])
        np_val = self._buildParams(expected_result, dtype)
        self.assertAllEqual(np_val, gather_val)
        self.assertEqual(np_val.shape, gather_t.get_shape())

  def testString(self):
    params = np.array([[b"asdf", b"zxcv"], [b"qwer", b"uiop"]])
    with self.cached_session():
      indices_tf = constant_op.constant([1])
      self.assertAllEqual([[b"qwer", b"uiop"]],
                          array_ops.batch_gather(params, indices_tf).eval())

  def testUnknownIndices(self):
    params = constant_op.constant([[0, 1, 2]])
    indices = array_ops.placeholder(dtypes.int32, shape=[None, None])
    gather_t = array_ops.batch_gather(params, indices)
    self.assertEqual([1, None], gather_t.get_shape().as_list())

  def testBadIndicesCPU(self):
    with self.test_session(use_gpu=False):
      params = [[0, 1, 2], [3, 4, 5]]
      with self.assertRaisesOpError(r"indices\[0\] = 7 is not in \[0, 2\)"):
        array_ops.batch_gather(params, [7]).eval()

  def testEmptySlices(self):
    with self.test_session(use_gpu=True):
      for dtype in _TEST_TYPES:
        for itype in np.int32, np.int64:
          params = np.zeros((7, 0, 0), dtype=dtype.as_numpy_dtype)
          indices = np.array([3, 4], dtype=itype)
          gather = array_ops.batch_gather(params, indices)
          self.assertAllEqual(gather.eval(), np.zeros((2, 0, 0)))

if __name__ == "__main__":
  test.main()