chore: import upstream snapshot with attribution

tensorflow/python/data/ops/map_op.py

@@ -0,0 +1,238 @@
+# Copyright 2022 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.
+# ==============================================================================
+"""The implementation of `tf.data.Dataset.map`."""
+
+import warnings
+
+from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.data.ops import debug_mode
+from tensorflow.python.data.ops import structured_function
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import gen_dataset_ops
+
+
+def _map_v2(
+    input_dataset,  # pylint: disable=unused-private-name
+    map_func,
+    num_parallel_calls=None,
+    deterministic=None,
+    synchronous=None,
+    use_unbounded_threadpool=None,
+    name=None,
+):
+  """See `Dataset.map()` for details."""
+  if num_parallel_calls is None or debug_mode.DEBUG_MODE:
+    if deterministic is not None and not debug_mode.DEBUG_MODE:
+      warnings.warn(
+          "The `deterministic` argument has no effect unless the "
+          "`num_parallel_calls` argument is specified."
+      )
+    return _MapDataset(
+        input_dataset,
+        map_func,
+        preserve_cardinality=True,
+        force_synchronous=False if synchronous is None else synchronous,
+        name=name,
+    )
+  else:
+    if synchronous:
+      raise ValueError(
+          "`synchronous` is not supported with `num_parallel_calls`, but"
+          " `num_parallel_calls` was set to ",
+          num_parallel_calls,
+      )
+    return _ParallelMapDataset(
+        input_dataset,
+        map_func,
+        num_parallel_calls=num_parallel_calls,
+        deterministic=deterministic,
+        preserve_cardinality=True,
+        use_unbounded_threadpool=use_unbounded_threadpool,
+        name=name)
+
+
+def _map_v1(
+    input_dataset,  # pylint: disable=unused-private-name
+    map_func,
+    num_parallel_calls=None,
+    deterministic=None,
+    synchronous=None,
+    use_unbounded_threadpool=None,  # pylint: disable=unused-argument
+):
+  """See `Dataset.map()` for details."""
+  if num_parallel_calls is None or debug_mode.DEBUG_MODE:
+    return dataset_ops.DatasetV1Adapter(
+        _MapDataset(
+            input_dataset,
+            map_func,
+            preserve_cardinality=False,
+            force_synchronous=False if synchronous is None else synchronous,
+        )
+    )
+  else:
+    if synchronous:
+      raise ValueError(
+          "`synchronous` is not supported with `num_parallel_calls`, but"
+          " `num_parallel_calls` was set to ",
+          num_parallel_calls,
+      )
+    return dataset_ops.DatasetV1Adapter(
+        _ParallelMapDataset(
+            input_dataset,
+            map_func,
+            num_parallel_calls,
+            deterministic,
+            preserve_cardinality=False,
+            use_unbounded_threadpool=False))
+
+
+def _map_v1_with_legacy_function(  # pylint: disable=unused-private-name
+    input_dataset,
+    map_func,
+    num_parallel_calls=None,
+    deterministic=None,
+    synchronous=False,
+):
+  """See `Dataset.map()` for details."""
+  if num_parallel_calls is None:
+    if deterministic is not None:
+      warnings.warn("The `deterministic` argument has no effect unless the "
+                    "`num_parallel_calls` argument is specified.")
+    return dataset_ops.DatasetV1Adapter(
+        _MapDataset(
+            input_dataset,
+            map_func,
+            force_synchronous=synchronous,
+            preserve_cardinality=False,
+            use_legacy_function=True,
+        )
+    )
+  else:
+    if synchronous:
+      raise ValueError(
+          "`synchronous` is not supported with `num_parallel_calls`, but"
+          " `num_parallel_calls` was set to ",
+          num_parallel_calls,
+      )
+    return dataset_ops.DatasetV1Adapter(
+        _ParallelMapDataset(
+            input_dataset,
+            map_func,
+            num_parallel_calls,
+            deterministic,
+            preserve_cardinality=False,
+            use_legacy_function=True,
+            use_unbounded_threadpool=False))
+
+
+class _MapDataset(dataset_ops.UnaryDataset):
+  """A `Dataset` that maps a function over elements in its input."""
+
+  def __init__(
+      self,
+      input_dataset,
+      map_func,
+      force_synchronous=False,
+      use_inter_op_parallelism=True,
+      preserve_cardinality=True,
+      use_legacy_function=False,
+      name=None,
+  ):
+    self._input_dataset = input_dataset
+    self._use_inter_op_parallelism = use_inter_op_parallelism
+    self._preserve_cardinality = preserve_cardinality
+    self._map_func = structured_function.StructuredFunctionWrapper(
+        map_func,
+        self._transformation_name(),
+        dataset=input_dataset,
+        use_legacy_function=use_legacy_function)
+    self._force_synchronous = force_synchronous
+    self._name = name
+    variant_tensor = gen_dataset_ops.map_dataset(
+        input_dataset._variant_tensor,  # pylint: disable=protected-access
+        self._map_func.function.captured_inputs,
+        f=self._map_func.function,
+        use_inter_op_parallelism=self._use_inter_op_parallelism,
+        preserve_cardinality=self._preserve_cardinality,
+        force_synchronous=self._force_synchronous,
+        **self._common_args
+    )
+    super().__init__(input_dataset, variant_tensor)
+
+  def _functions(self):
+    return [self._map_func]
+
+  @property
+  def element_spec(self):
+    return self._map_func.output_structure
+
+  def _transformation_name(self):
+    return "Dataset.map()"
+
+
+class _ParallelMapDataset(dataset_ops.UnaryDataset):
+  """A `Dataset` that maps a function over elements in its input in parallel."""
+
+  def __init__(self,
+               input_dataset,
+               map_func,
+               num_parallel_calls,
+               deterministic,
+               use_inter_op_parallelism=True,
+               preserve_cardinality=False,
+               use_legacy_function=False,
+               use_unbounded_threadpool=False,
+               name=None):
+    """See `Dataset.map()` for details."""
+    self._input_dataset = input_dataset
+    self._use_inter_op_parallelism = use_inter_op_parallelism
+    self._map_func = structured_function.StructuredFunctionWrapper(
+        map_func,
+        self._transformation_name(),
+        dataset=input_dataset,
+        use_legacy_function=use_legacy_function)
+    if deterministic is None:
+      self._deterministic = "default"
+    elif deterministic:
+      self._deterministic = "true"
+    else:
+      self._deterministic = "false"
+    self._preserve_cardinality = preserve_cardinality
+    self._num_parallel_calls = ops.convert_to_tensor(
+        num_parallel_calls, dtype=dtypes.int64, name="num_parallel_calls")
+    self._use_unbounded_threadpool = use_unbounded_threadpool
+    self._name = name
+    variant_tensor = gen_dataset_ops.parallel_map_dataset_v2(
+        input_dataset._variant_tensor,  # pylint: disable=protected-access
+        self._map_func.function.captured_inputs,
+        f=self._map_func.function,
+        num_parallel_calls=self._num_parallel_calls,
+        deterministic=self._deterministic,
+        use_inter_op_parallelism=self._use_inter_op_parallelism,
+        preserve_cardinality=self._preserve_cardinality,
+        use_unbounded_threadpool=self._use_unbounded_threadpool,
+        **self._common_args)
+    super().__init__(input_dataset, variant_tensor)
+
+  def _functions(self):
+    return [self._map_func]
+
+  @property
+  def element_spec(self):
+    return self._map_func.output_structure
+
+  def _transformation_name(self):
+    return "Dataset.map()"