chore: import upstream snapshot with attribution

test/distribution/mock_data.py

@@ -0,0 +1,65 @@
+# Copyright (c) 2021 PaddlePaddle 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.
+
+import paddle
+
+
+class Exponential(paddle.distribution.ExponentialFamily):
+    """mock exponential distribution, which support computing entropy and
+    kl use bregman divergence
+    """
+
+    _mean_carrier_measure = 0
+
+    def __init__(self, rate):
+        self._rate = rate
+        super().__init__(batch_shape=rate.shape)
+
+    @property
+    def rate(self):
+        return self._rate
+
+    def entropy(self):
+        return 1.0 - paddle.log(self._rate)
+
+    @property
+    def _natural_parameters(self):
+        return (-self._rate,)
+
+    def _log_normalizer(self, x):
+        return -paddle.log(-x)
+
+
+class DummyExpFamily(paddle.distribution.ExponentialFamily):
+    """dummy class extend from exponential family"""
+
+    def __init__(self, *args):
+        pass
+
+    def entropy(self):
+        return 1.0
+
+    @property
+    def _natural_parameters(self):
+        return (1.0,)
+
+    def _log_normalizer(self, x):
+        return -paddle.log(-x)
+
+
+@paddle.distribution.register_kl(Exponential, Exponential)
+def _kl_exponential_exponential(p, q):
+    rate_ratio = q.rate / p.rate
+    t1 = -rate_ratio.log()
+    return t1 + rate_ratio - 1