Remove circular dependencies by removing submodule imports from ragged package.

(If ragged/__init__.py imports all ragged modules, then it's impossible to depend on one ragged module without depending on all of them.)

PiperOrigin-RevId: 299479545
Change-Id: I469e160a49efdd47c137497328ea47800a621e85

tensorflow/python/__init__.py

@@ -98,6 +98,7 @@ from tensorflow.python.ops.distributions import distributions
 from tensorflow.python.ops.linalg import linalg
 from tensorflow.python.ops.linalg.sparse import sparse
 from tensorflow.python.ops.losses import losses
+from tensorflow.python.ops.ragged import ragged_ops as _ragged_ops
 from tensorflow.python.ops.signal import signal
 from tensorflow.python.profiler import profiler
 from tensorflow.python.profiler import profiler_client
@@ -108,6 +109,9 @@ from tensorflow.python.tpu import api
 from tensorflow.python.user_ops import user_ops
 from tensorflow.python.util import compat
 
+# Update the RaggedTensor package docs w/ a list of ops that support dispatch.
+ragged.__doc__ += _ragged_ops.ragged_dispatch.ragged_op_list()
+
 # Import to make sure the ops are registered.
 from tensorflow.python.ops import gen_audio_ops
 from tensorflow.python.ops import gen_boosted_trees_ops

tensorflow/python/framework/test_util.py

@@ -67,11 +67,12 @@ from tensorflow.python.framework import versions
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import control_flow_util
 from tensorflow.python.ops import control_flow_util_v2
-from tensorflow.python.ops.ragged import ragged_tensor
-from tensorflow.python.ops.ragged import ragged_tensor_value
 from tensorflow.python.ops import script_ops
 from tensorflow.python.ops import summary_ops_v2
 from tensorflow.python.ops import variables
+from tensorflow.python.ops.ragged import ragged_ops  # pylint: disable=unused-import
+from tensorflow.python.ops.ragged import ragged_tensor
+from tensorflow.python.ops.ragged import ragged_tensor_value
 from tensorflow.python.platform import googletest
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.training import server_lib
@@ -80,9 +81,9 @@ from tensorflow.python.util import deprecation
 from tensorflow.python.util import nest
 from tensorflow.python.util import tf_decorator
 from tensorflow.python.util import tf_inspect
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.protobuf import compare
 from tensorflow.python.util.tf_export import tf_export
-from tensorflow.python.util.compat import collections_abc
 
 
 # If the below import is made available through the BUILD rule, then this

tensorflow/python/ops/parsing_config.py

@@ -29,21 +29,12 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import sparse_ops
+from tensorflow.python.ops.ragged import ragged_math_ops
+from tensorflow.python.ops.ragged import ragged_tensor
 from tensorflow.python.platform import tf_logging
-from tensorflow.python.util.lazy_loader import LazyLoader
 from tensorflow.python.util.tf_export import tf_export
 
 
-# Avoid circular dependencies with RaggedTensor.
-# TODO(b/141170488) Refactor ragged modules so this is unnecessary.
-ragged_tensor = LazyLoader(
-    "ragged_tensor", globals(),
-    "tensorflow.python.ops.ragged.ragged_tensor")
-ragged_math_ops = LazyLoader(
-    "ragged_math_ops", globals(),
-    "tensorflow.python.ops.ragged.ragged_math_ops")
-
-
 # TODO(b/122887740) Refactor code:
 #   * Move input verification to feature configuration objects (e.g.,
 #     VarLenFeature should check that dtype is a valid dtype).

tensorflow/python/ops/ragged/BUILD

@@ -41,6 +41,7 @@ py_library(
         ":ragged_map_ops",
         ":ragged_math_ops",
         ":ragged_operators",
+        ":ragged_ops",
         ":ragged_string_ops",
         ":ragged_tensor",
         ":ragged_tensor_shape",
@@ -231,6 +232,35 @@ py_library(
     ],
 )
 
+py_library(
+    name = "ragged_ops",
+    srcs = ["ragged_ops.py"],
+    srcs_version = "PY2AND3",
+    deps = [
+        ":ragged_array_ops",
+        ":ragged_batch_gather_ops",
+        ":ragged_batch_gather_with_default_op",
+        ":ragged_concat_ops",
+        ":ragged_config",
+        ":ragged_conversion_ops",
+        ":ragged_dispatch",
+        ":ragged_factory_ops",
+        ":ragged_functional_ops",
+        ":ragged_gather_ops",
+        ":ragged_getitem",
+        ":ragged_map_ops",
+        ":ragged_math_ops",
+        ":ragged_operators",
+        ":ragged_string_ops",
+        ":ragged_tensor",
+        ":ragged_tensor_shape",
+        ":ragged_tensor_value",
+        ":ragged_util",
+        ":ragged_where_op",
+        ":segment_id_ops",
+    ],
+)
+
 py_library(
     name = "ragged_string_ops",
     srcs = ["ragged_string_ops.py"],

tensorflow/python/ops/ragged/__init__.py

@@ -27,26 +27,3 @@ and the [Ragged Tensor Guide](/guide/ragged_tensors).
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
-
-from tensorflow.python.ops.ragged import ragged_array_ops
-from tensorflow.python.ops.ragged import ragged_batch_gather_ops
-from tensorflow.python.ops.ragged import ragged_batch_gather_with_default_op
-from tensorflow.python.ops.ragged import ragged_concat_ops
-from tensorflow.python.ops.ragged import ragged_conversion_ops
-from tensorflow.python.ops.ragged import ragged_dispatch
-from tensorflow.python.ops.ragged import ragged_factory_ops
-from tensorflow.python.ops.ragged import ragged_functional_ops
-from tensorflow.python.ops.ragged import ragged_gather_ops
-from tensorflow.python.ops.ragged import ragged_getitem
-from tensorflow.python.ops.ragged import ragged_map_ops
-from tensorflow.python.ops.ragged import ragged_math_ops
-from tensorflow.python.ops.ragged import ragged_operators
-from tensorflow.python.ops.ragged import ragged_string_ops
-from tensorflow.python.ops.ragged import ragged_tensor
-from tensorflow.python.ops.ragged import ragged_tensor_shape
-from tensorflow.python.ops.ragged import ragged_tensor_value
-from tensorflow.python.ops.ragged import ragged_where_op
-from tensorflow.python.ops.ragged import segment_id_ops
-
-# Add a list of the ops that support Ragged Tensors.
-__doc__ += ragged_dispatch.ragged_op_list()  # pylint: disable=redefined-builtin

tensorflow/python/ops/ragged/ragged_ops.py

@@ -0,0 +1,50 @@
+# Copyright 2020 The TensorFlow 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 all modules in the `ragged` package that define exported symbols.
+
+Additional, import ragged_dispatch (which has the side-effect of registering
+dispatch handlers for many standard TF ops) and ragged_operators (which has the
+side-effect of overriding RaggedTensor operators, such as RaggedTensor.__add__).
+
+We don't import these modules from ragged/__init__.py, since we want to avoid
+circular dependencies.
+"""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+
+# pylint: disable=unused-import
+from tensorflow.python.ops.ragged import ragged_array_ops
+from tensorflow.python.ops.ragged import ragged_batch_gather_ops
+from tensorflow.python.ops.ragged import ragged_batch_gather_with_default_op
+from tensorflow.python.ops.ragged import ragged_concat_ops
+from tensorflow.python.ops.ragged import ragged_conversion_ops
+from tensorflow.python.ops.ragged import ragged_dispatch
+from tensorflow.python.ops.ragged import ragged_factory_ops
+from tensorflow.python.ops.ragged import ragged_functional_ops
+from tensorflow.python.ops.ragged import ragged_gather_ops
+from tensorflow.python.ops.ragged import ragged_getitem
+from tensorflow.python.ops.ragged import ragged_map_ops
+from tensorflow.python.ops.ragged import ragged_math_ops
+from tensorflow.python.ops.ragged import ragged_operators
+from tensorflow.python.ops.ragged import ragged_squeeze_op
+from tensorflow.python.ops.ragged import ragged_string_ops
+from tensorflow.python.ops.ragged import ragged_tensor
+from tensorflow.python.ops.ragged import ragged_tensor_shape
+from tensorflow.python.ops.ragged import ragged_tensor_value
+from tensorflow.python.ops.ragged import ragged_where_op
+from tensorflow.python.ops.ragged import segment_id_ops

tensorflow/python/ops/ragged/ragged_tensor.py

@@ -2117,15 +2117,50 @@ class RaggedTensor(composite_tensor.CompositeTensor):
     return isinstance(rt, ops.EagerTensor)
 
   #=============================================================================
-  # Indexing & Slicing
+  # Operators
   #=============================================================================
-  def __getitem__(self, key):
-    """Returns the specified piece of this RaggedTensor."""
-    # See ragged_getitem.py for the documentation and implementation of this
-    # method.
-    #
-    # Note: the imports in ragged/__init__.py ensure that this method always
-    # gets overridden before it is called.
+  # To avoid circular dependencies, we define stub methods for operators here,
+  # and then override them when the ragged_operators module is imported.
+
+  def _overloaded_operator(name):  # pylint: disable=no-self-argument
+    def stub(*args, **kwargs):
+      del args, kwargs
+      raise ValueError(
+          "You must import 'tensorflow.python.ops.ragged.ragged_ops' "
+          "before using RaggedTensor.%s" % name)
+    return stub
+
+  __getitem__ = _overloaded_operator("__getitem__")
+  __ge__ = _overloaded_operator("__ge__")
+  __gt__ = _overloaded_operator("__gt__")
+  __le__ = _overloaded_operator("__le__")
+  __lt__ = _overloaded_operator("__lt__")
+  __and__ = _overloaded_operator("__and__")
+  __rand__ = _overloaded_operator("__rand__")
+  __invert__ = _overloaded_operator("__invert__")
+  __ror__ = _overloaded_operator("__ror__")
+  __or__ = _overloaded_operator("__or__")
+  __xor__ = _overloaded_operator("__xor__")
+  __rxor__ = _overloaded_operator("__rxor__")
+  __abs__ = _overloaded_operator("__abs__")
+  __add__ = _overloaded_operator("__add__")
+  __radd__ = _overloaded_operator("__radd__")
+  __div__ = _overloaded_operator("__div__")
+  __rdiv__ = _overloaded_operator("__rdiv__")
+  __floordiv__ = _overloaded_operator("__floordiv__")
+  __rfloordiv__ = _overloaded_operator("__rfloordiv__")
+  __mod__ = _overloaded_operator("__mod__")
+  __rmod__ = _overloaded_operator("__rmod__")
+  __mul__ = _overloaded_operator("__mul__")
+  __rmul__ = _overloaded_operator("__rmul__")
+  __neg__ = _overloaded_operator("__neg__")
+  __pow__ = _overloaded_operator("__pow__")
+  __rpow__ = _overloaded_operator("__rpow__")
+  __sub__ = _overloaded_operator("__sub__")
+  __rsub__ = _overloaded_operator("__rsub__")
+  __truediv__ = _overloaded_operator("__truediv__")
+  __rtruediv__ = _overloaded_operator("__rtruediv__")
+  del _overloaded_operator
 
   #=============================================================================
   # Name Scope