Remove hourglass imports for python/keras/engine/...

Previously there was python/keras/engine/__init__.py, which required every import of Layer (for example) to also import Network (since Python will not import a file in a directory without running its __init__.py file).

I'm working on adding automatic attribute tracking to Checkpointable (and Network) and so need to insert things between Layer and Network.

PiperOrigin-RevId: 201743850

1 files changed, 4 insertions, 4 deletions

diff --git a/tensorflow/contrib/coder/python/layers/entropybottleneck.py b/tensorflow/contrib/coder/python/layers/entropybottleneck.py
index 0fbe3081af..0c997bd4fd 100644
--- a/tensorflow/contrib/coder/python/layers/entropybottleneck.py
+++ b/tensorflow/contrib/coder/python/layers/entropybottleneck.py
@@ -28,7 +28,7 @@ from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_shape
-from tensorflow.python.keras import engine
+from tensorflow.python.keras.engine import base_layer
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import functional_ops
 from tensorflow.python.ops import init_ops
@@ -40,7 +40,7 @@ from tensorflow.python.ops import variable_scope
 from tensorflow.python.summary import summary
 
 
-class EntropyBottleneck(engine.Layer):
+class EntropyBottleneck(base_layer.Layer):
   """Entropy bottleneck layer.
 
   This layer can be used to model the entropy (the amount of information
@@ -262,7 +262,7 @@ class EntropyBottleneck(engine.Layer):
     self._range_coder_precision = int(range_coder_precision)
     self._data_format = data_format
     self._channel_axis(2)  # trigger ValueError early
-    self.input_spec = engine.InputSpec(min_ndim=2)
+    self.input_spec = base_layer.InputSpec(min_ndim=2)
 
   @property
   def init_scale(self):
@@ -357,7 +357,7 @@ class EntropyBottleneck(engine.Layer):
     channels = input_shape[channel_axis].value
     if channels is None:
       raise ValueError("The channel dimension of the inputs must be defined.")
-    self.input_spec = engine.InputSpec(
+    self.input_spec = base_layer.InputSpec(
         ndim=input_shape.ndims, axes={channel_axis: channels})
     filters = (1,) + self.filters + (1,)
     scale = self.init_scale ** (1 / (len(self.filters) + 1))