[tf.data] move StructuredFunctionWrapper into a common module

refactor using structured_function module

use the new API location of structured_function

move DEBUG_MODE to dataset_ops

tensorflow/python/data/benchmarks/from_tensor_slices_benchmark.py

@@ -22,6 +22,7 @@
 from tensorflow.python.data.benchmarks import benchmark_base
 from tensorflow.python.data.experimental.ops import get_single_element
 from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.data.ops import structured_function
 from tensorflow.python.eager import def_function
 from tensorflow.python.framework import sparse_tensor
 from tensorflow.python.ops import gen_dataset_ops
@@ -33,7 +34,7 @@ class SingleThreadedFlatMapDataset(dataset_ops.UnaryDataset):
   def __init__(self, input_dataset, map_func):
     """See `Dataset.flat_map()` for details."""
     self._input_dataset = input_dataset
-    self._map_func = dataset_ops.StructuredFunctionWrapper(
+    self._map_func = structured_function.StructuredFunctionWrapper(
         map_func,
         self._transformation_name(),
         dataset=input_dataset,

tensorflow/python/data/experimental/ops/batching.py

@@ -18,6 +18,7 @@
 from __future__ import print_function
 
 from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.data.ops import structured_function
 from tensorflow.python.data.util import convert
 from tensorflow.python.data.util import nest
 from tensorflow.python.framework import dtypes
@@ -331,7 +332,7 @@ def __init__(self, input_dataset, map_func, batch_size, num_parallel_calls,
                drop_remainder, use_legacy_function=False):
     self._input_dataset = input_dataset
 
-    self._map_func = dataset_ops.StructuredFunctionWrapper(
+    self._map_func = structured_function.StructuredFunctionWrapper(
         map_func,
         "tf.data.experimental.map_and_batch()",
         dataset=input_dataset,
@@ -437,7 +438,7 @@ def to_ragged_variant(value):
         return spec._to_tensor_list(value)[0]  # pylint: disable=protected-access
 
     # Tuples are automatically unpacked by `dataset.map` so we repack them.
-    if dataset_ops._should_unpack(input_dataset.element_spec):  # pylint: disable=protected-access
+    if structured_function._should_unpack(input_dataset.element_spec):  # pylint: disable=protected-access
       map_fn = lambda *value: nest.map_structure(to_ragged_variant, value)
     else:
       map_fn = lambda value: nest.map_structure(to_ragged_variant, value)

tensorflow/python/data/experimental/ops/grouping.py

@@ -18,6 +18,7 @@
 from __future__ import print_function
 
 from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.data.ops import structured_function
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import structure
 from tensorflow.python.framework import dtypes
@@ -285,7 +286,7 @@ def __init__(self, input_dataset, key_func, reducer):
 
   def _make_key_func(self, key_func, input_dataset):
     """Make wrapping defun for key_func."""
-    self._key_func = dataset_ops.StructuredFunctionWrapper(
+    self._key_func = structured_function.StructuredFunctionWrapper(
         key_func, self._transformation_name(), dataset=input_dataset)
     if not self._key_func.output_structure.is_compatible_with(
         tensor_spec.TensorSpec([], dtypes.int64)):
@@ -296,7 +297,7 @@ def _make_key_func(self, key_func, input_dataset):
 
   def _make_init_func(self, init_func):
     """Make wrapping defun for init_func."""
-    self._init_func = dataset_ops.StructuredFunctionWrapper(
+    self._init_func = structured_function.StructuredFunctionWrapper(
         init_func,
         self._transformation_name(),
         input_structure=tensor_spec.TensorSpec([], dtypes.int64))
@@ -313,7 +314,7 @@ def _make_reduce_func(self, reduce_func, input_dataset):
     need_to_rerun = True
     while need_to_rerun:
 
-      wrapped_func = dataset_ops.StructuredFunctionWrapper(
+      wrapped_func = structured_function.StructuredFunctionWrapper(
           reduce_func,
           self._transformation_name(),
           input_structure=(self._state_structure, input_dataset.element_spec),
@@ -366,7 +367,7 @@ def _make_reduce_func(self, reduce_func, input_dataset):
 
   def _make_finalize_func(self, finalize_func):
     """Make wrapping defun for finalize_func."""
-    self._finalize_func = dataset_ops.StructuredFunctionWrapper(
+    self._finalize_func = structured_function.StructuredFunctionWrapper(
         finalize_func, self._transformation_name(),
         input_structure=self._state_structure)
 

tensorflow/python/data/experimental/ops/io.py

@@ -23,6 +23,7 @@
 
 from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.data.ops import structured_function
 from tensorflow.python.data.util import structure
 from tensorflow.python.eager import context
 from tensorflow.python.framework import dtypes
@@ -176,7 +177,7 @@ def _set_save_dataset_attributes(dataset, shard_func, path):
   else:
     use_shard_func = True
 
-  wrapped_func = dataset_ops.StructuredFunctionWrapper(
+  wrapped_func = structured_function.StructuredFunctionWrapper(
       shard_func,
       "save()",
       input_structure=dataset.element_spec,
@@ -221,7 +222,7 @@ def __init__(self, path, element_spec=None, compression=None,
     else:
       self._element_spec = element_spec
     self._compression = compression
-    self._reader_func = dataset_ops.StructuredFunctionWrapper(
+    self._reader_func = structured_function.StructuredFunctionWrapper(
         reader_func,
         "load()",
         # Dataset of datasets of input elements

tensorflow/python/data/experimental/ops/prefetching_ops.py

@@ -19,6 +19,7 @@
 
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.ops import iterator_ops
+from tensorflow.python.data.ops import structured_function
 from tensorflow.python.data.util import structure
 from tensorflow.python.eager import function
 from tensorflow.python.framework import device as framework_device
@@ -238,7 +239,7 @@ def __init__(self, input_dataset, map_func, use_inter_op_parallelism=True):
     self._input_dataset = input_dataset
     self._use_inter_op_parallelism = use_inter_op_parallelism
 
-    self._map_func = dataset_ops.StructuredFunctionWrapper(
+    self._map_func = structured_function.StructuredFunctionWrapper(
         map_func,
         self._transformation_name(),
         dataset=input_dataset,

tensorflow/python/data/ops/BUILD

@@ -3,13 +3,27 @@ package(
     licenses = ["notice"],
 )
 
+py_library(
+    name = "structured_function",
+    srcs = ["structured_function.py"],
+    srcs_version = "PY3",
+    deps = [
+        "//tensorflow/python:framework_ops",
+        "//tensorflow/python:function",
+        "//tensorflow/python:util",
+        "//tensorflow/python/data/util:nest",
+        "//tensorflow/python/data/util:structure",
+    ],
+)
+
 py_library(
     name = "dataset_ops",
     srcs = ["dataset_ops.py"],
     srcs_version = "PY3",
     deps = [
         ":iterator_ops",
         ":options",
+        ":structured_function",
         "//tensorflow/python:constant_op",
         "//tensorflow/python:control_flow_ops",
         "//tensorflow/python:dataset_ops_gen",