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      1 # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
      2 #
      3 # Licensed under the Apache License, Version 2.0 (the "License");
      4 # you may not use this file except in compliance with the License.
      5 # You may obtain a copy of the License at
      6 #
      7 # http://www.apache.org/licenses/LICENSE-2.0
      8 #
      9 # Unless required by applicable law or agreed to in writing, software
     10 # distributed under the License is distributed on an "AS IS" BASIS,
     11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 # See the License for the specific language governing permissions and
     13 # limitations under the License.
     14 # ==============================================================================
     15 """Tests for specs-related summarization functions."""
     16 
     17 from __future__ import absolute_import
     18 from __future__ import division
     19 from __future__ import print_function
     20 
     21 import numpy as np
     22 
     23 from tensorflow.contrib.specs.python import specs
     24 from tensorflow.contrib.specs.python import summaries
     25 from tensorflow.python.framework import constant_op
     26 from tensorflow.python.ops import variables
     27 from tensorflow.python.platform import test
     28 
     29 
     30 def _rand(*size):
     31   return np.random.uniform(size=size).astype("f")
     32 
     33 
     34 class SummariesTest(test.TestCase):
     35 
     36   def testStructure(self):
     37     with self.test_session():
     38       inputs_shape = (1, 18, 19, 5)
     39       inputs = constant_op.constant(_rand(*inputs_shape))
     40       spec = "net = Cr(64, [5, 5])"
     41       outputs = specs.create_net(spec, inputs)
     42       variables.global_variables_initializer().run()
     43       result = outputs.eval()
     44       self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     45       self.assertEqual(
     46           summaries.tf_spec_structure(
     47               spec, input_shape=inputs_shape),
     48           "_ variablev2 conv variablev2 biasadd relu")
     49 
     50   def testStructureFromTensor(self):
     51     with self.test_session():
     52       inputs = constant_op.constant(_rand(1, 18, 19, 5))
     53       spec = "net = Cr(64, [5, 5])"
     54       outputs = specs.create_net(spec, inputs)
     55       variables.global_variables_initializer().run()
     56       result = outputs.eval()
     57       self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     58       self.assertEqual(
     59           summaries.tf_spec_structure(spec, inputs),
     60           "_ variablev2 conv variablev2 biasadd relu")
     61 
     62   def testPrint(self):
     63     with self.test_session():
     64       inputs = constant_op.constant(_rand(1, 18, 19, 5))
     65       spec = "net = Cr(64, [5, 5])"
     66       outputs = specs.create_net(spec, inputs)
     67       variables.global_variables_initializer().run()
     68       result = outputs.eval()
     69       self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     70       summaries.tf_spec_print(spec, inputs)
     71 
     72   def testSummary(self):
     73     with self.test_session():
     74       inputs = constant_op.constant(_rand(1, 18, 19, 5))
     75       spec = "net = Cr(64, [5, 5])"
     76       outputs = specs.create_net(spec, inputs)
     77       variables.global_variables_initializer().run()
     78       result = outputs.eval()
     79       self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     80       summaries.tf_spec_summary(spec, inputs)
     81 
     82 
     83 if __name__ == "__main__":
     84   test.main()
     85