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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 the Bernoulli distribution."""
     16 
     17 from __future__ import absolute_import
     18 from __future__ import division
     19 from __future__ import print_function
     20 
     21 from tensorflow.contrib import distributions
     22 from tensorflow.contrib.distributions.python.kernel_tests import distribution_test
     23 from tensorflow.python.framework import dtypes
     24 from tensorflow.python.framework import tensor_shape
     25 from tensorflow.python.platform import test
     26 
     27 
     28 class ConditionalDistributionTest(distribution_test.DistributionTest):
     29 
     30   def _GetFakeDistribution(self):
     31     class _FakeDistribution(distributions.ConditionalDistribution):
     32       """Fake Distribution for testing _set_sample_static_shape."""
     33 
     34       def __init__(self, batch_shape=None, event_shape=None):
     35         self._static_batch_shape = tensor_shape.TensorShape(batch_shape)
     36         self._static_event_shape = tensor_shape.TensorShape(event_shape)
     37         super(_FakeDistribution, self).__init__(
     38             dtype=dtypes.float32,
     39             reparameterization_type=distributions.NOT_REPARAMETERIZED,
     40             validate_args=True,
     41             allow_nan_stats=True,
     42             name="DummyDistribution")
     43 
     44       def _batch_shape(self):
     45         return self._static_batch_shape
     46 
     47       def _event_shape(self):
     48         return self._static_event_shape
     49 
     50       def _sample_n(self, unused_shape, unused_seed, arg1, arg2):
     51         raise ValueError(arg1, arg2)
     52 
     53       def _log_prob(self, _, arg1, arg2):
     54         raise ValueError(arg1, arg2)
     55 
     56       def _prob(self, _, arg1, arg2):
     57         raise ValueError(arg1, arg2)
     58 
     59       def _cdf(self, _, arg1, arg2):
     60         raise ValueError(arg1, arg2)
     61 
     62       def _log_cdf(self, _, arg1, arg2):
     63         raise ValueError(arg1, arg2)
     64 
     65       def _log_survival_function(self, _, arg1, arg2):
     66         raise ValueError(arg1, arg2)
     67 
     68       def _survival_function(self, _, arg1, arg2):
     69         raise ValueError(arg1, arg2)
     70 
     71     return _FakeDistribution
     72 
     73   def testNotImplemented(self):
     74     d = self._GetFakeDistribution()(batch_shape=[], event_shape=[])
     75     for name in ["sample", "log_prob", "prob", "log_cdf", "cdf",
     76                  "log_survival_function", "survival_function"]:
     77       method = getattr(d, name)
     78       with self.assertRaisesRegexp(ValueError, "b1.*b2"):
     79         method([] if name == "sample" else 1.0, arg1="b1", arg2="b2")
     80 
     81 
     82 if __name__ == "__main__":
     83   test.main()
     84