# 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 models.tutorials.rnn.ptb.reader."""
from
 __future__ 
import
 absolute_import

from
 __future__ 
import
 division

from
 __future__ 
import
 print_function


import
 os.path


import
 tensorflow 
as
 tf


import
 reader



class
PtbReaderTest
(tf.test.TestCase)
:
def
setUp
(self)
:

    self._string_data = 
"\n"
.join(
        [
" hello there i am"
,

" rain as day"
,

" want some cheesy puffs ?"
])


def
testPtbRawData
(self)
:

    tmpdir = tf.test.get_temp_dir()

for
 suffix 
in
"train"
, 
"valid"
, 
"test"
:
      filename = os.path.join(tmpdir, 
"ptb.%s.txt"
 % suffix)

with
 tf.gfile.GFile(filename, 
"w"
) 
as
 fh:
        fh.write(self._string_data)

# Smoke test

    output = reader.ptb_raw_data(tmpdir)
    self.assertEqual(len(output), 
4
)


def
testPtbProducer
(self)
:

    raw_data = [
4
, 
3
, 
2
, 
1
, 
0
, 
5
, 
6
, 
1
, 
1
, 
1
, 
1
, 
0
, 
3
, 
4
, 
1
]
    batch_size = 
3

    num_steps = 
2

    x, y = reader.ptb_producer(raw_data, batch_size, num_steps)

with
 self.test_session() 
as
 session:
      coord = tf.train.Coordinator()
      tf.train.start_queue_runners(session, coord=coord)

try
:
        xval, yval = session.run([x, y])
        self.assertAllEqual(xval, [[
4
, 
3
], [
5
, 
6
], [
1
, 
0
]])
        self.assertAllEqual(yval, [[
3
, 
2
], [
6
, 
1
], [
0
, 
3
]])
        xval, yval = session.run([x, y])
        self.assertAllEqual(xval, [[
2
, 
1
], [
1
, 
1
], [
3
, 
4
]])
        self.assertAllEqual(yval, [[
1
, 
0
], [
1
, 
1
], [
4
, 
1
]])

finally
:
        coord.request_stop()
        coord.join()



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