Bump T2T version to 1.15.5

With this change Travis will turn green.

When we import compat.v1, we shouldn't do tf.compat.v1 anymore.

Also the following to unclog Travis:
six>=1.12.0 is required by tf-hub 0.8.0, one of the core dependencies seems to
be installing tf-hub, so pinning tf-hub to 0.7.0 (which is in the extras
section) doesn't seem to help.

Locally the previous setup.py installs fine, but only errors on Travis for some
reason.

PiperOrigin-RevId: 307203166

setup.py

@@ -5,7 +5,7 @@
 
 setup(
     name='tensor2tensor',
-    version='1.15.4',
+    version='1.15.5',
     description='Tensor2Tensor',
     long_description=(
         'Tensor2Tensor, or T2T for short, is a library of '
@@ -61,7 +61,7 @@
         'pypng',
         'requests',
         'scipy',
-        'six',
+        'six>=1.12.0',
         'sympy',
         'tensorflow-datasets',
         'tensorflow-gan',

tensor2tensor/layers/common_attention_test.py

@@ -34,7 +34,7 @@
 
 tfe = contrib.tfe()
 # from tensorflow.contrib.eager.python import tfe as tfe
-tf.compat.v1.enable_eager_execution()
+tf.enable_eager_execution()
 
 
 class CommonAttentionTest(parameterized.TestCase, tf.test.TestCase):

tensor2tensor/layers/common_layers.py

@@ -2743,7 +2743,7 @@ def _fn_with_custom_grad(fn, inputs, grad_fn, use_global_vars=False):
   Returns:
     fn(*inputs)
   """
-  vs = tf.compat.v1.get_variable_scope()
+  vs = tf.get_variable_scope()
   get_vars_fn = (
       vs.global_variables if use_global_vars else vs.trainable_variables)
   len_before_vars = len(get_vars_fn())
@@ -3145,7 +3145,7 @@ def grad_fn(inputs, variables, outputs, output_grads):
 
   @fn_with_custom_grad(grad_fn)
   def fn_with_recompute(*args):
-    cached_vs.append(tf.compat.v1.get_variable_scope())
+    cached_vs.append(tf.get_variable_scope())
     cached_arg_scope.append(contrib.framework().current_arg_scope())
     return fn(*args)
 
@@ -3160,7 +3160,7 @@ def dense(x, units, **kwargs):
     # We need to find the layer parameters using scope name for the layer, so
     # check that the layer is named. Otherwise parameters for different layers
     # may get mixed up.
-    layer_name = tf.compat.v1.get_variable_scope().name
+    layer_name = tf.get_variable_scope().name
     if (not layer_name) or ("name" not in kwargs):
       raise ValueError(
           "Variable scope and layer name cannot be empty. Actual: "
@@ -3491,7 +3491,7 @@ def should_generate_summaries():
   if name_scope and "while/" in name_scope:
     # Summaries don't work well within tf.while_loop()
     return False
-  if tf.compat.v1.get_variable_scope().reuse:
+  if tf.get_variable_scope().reuse:
     # Avoid generating separate summaries for different data shards
     return False
   return True

tensor2tensor/layers/common_layers_test.py

@@ -28,7 +28,7 @@
 
 import tensorflow.compat.v1 as tf
 
-tf.compat.v1.enable_eager_execution()
+tf.enable_eager_execution()
 
 
 class CommonLayersTest(parameterized.TestCase, tf.test.TestCase):

tensor2tensor/utils/avg_checkpoints.py

@@ -114,4 +114,4 @@ def main(_):
 
 
 if __name__ == "__main__":
-  tf.compat.v1.app.run()
+  tf.app.run()