Adds missing copyright notices.

PiperOrigin-RevId: 445531928
Change-Id: Ia00efca37d927141b2969105a1dea72cec64cd60

Author: Johannes Ballé

models/toy_sources/compression_model.py

@@ -1,3 +1,17 @@
+# Copyright 2020 Google LLC. 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.
+# ==============================================================================
 """Base class for coding experiment."""
 
 import abc

models/toy_sources/ntc.py

@@ -1,3 +1,17 @@
+# Copyright 2020 Google LLC. 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.
+# ==============================================================================
 """Nonlinear transform coding."""
 
 import matplotlib.pyplot as plt
@@ -10,11 +24,6 @@
 tfpd = tfp.distributions
 
 
-@tf.custom_gradient
-def st_round(inputs):
-  return tf.round(inputs), lambda dy: dy
-
-
 class NTCModel(compression_model.CompressionModel):
   """Nonlinear transform coding model."""
 
@@ -158,7 +167,7 @@ def perturb(inputs, dither, prior, offset):
       else:
         if guess_offset:
           offset += tfc.quantization_offset(prior)
-        return st_round(inputs - offset) + offset
+        return tfc.round_st(inputs, offset)
 
     assert x.shape[-1] == self.ndim_source
     y = self.analysis(x)

models/toy_sources/vecvq.py

@@ -1,3 +1,17 @@
+# Copyright 2020 Google LLC. 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.
+# ==============================================================================
 """Variational entropy-constrained vector quantization."""
 
 import tensorflow as tf