#tf-data Support Python-style zipping in tf.data.Dataset.zip

The current behavior is unchanged to avoid affecting backward compatibility but only added a new behavior to `tf.data.Dataset.zip` Python op for accepting a non-nested structure of datasets without doing the tuple.

PiperOrigin-RevId: 515389129

RELEASE.md

@@ -85,6 +85,11 @@
         `tf.nn.safe_embedding_lookup_sparse`, which enables a simplified and
         typically faster lookup procedure.
 
+*   `tf.data`
+    
+    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e.
+        `Dataset.zip(a, b, c)`.
+
 ## Bug Fixes and Other Changes
 
 * <SIMILAR TO ABOVE SECTION, BUT FOR OTHER IMPORTANT CHANGES / BUG FIXES>

tensorflow/python/data/kernel_tests/zip_test.py

@@ -134,15 +134,53 @@ class ZipTest(test_base.DatasetTestBase, parameterized.TestCase):
     dataset = dataset_ops.Dataset.zip((x, y), name="zip")
     self.assertDatasetProduces(dataset, [(4, 2)])
 
+  @combinations.generate(
+      combinations.times(test_base.default_test_combinations())
+  )
+  def testZipWithArgsAndDataset(self):
+    with self.assertRaisesRegex(
+        TypeError, r"Both `\*args` and `datasets` cannot be set."
+    ):
+      dataset_ops.Dataset.zip(
+          dataset_ops.Dataset.range(1, 4),
+          dataset_ops.Dataset.range(4, 7),
+          datasets=(
+              dataset_ops.Dataset.range(1, 4),
+              dataset_ops.Dataset.range(4, 7),
+          ),
+      )
 
-class ZipCheckpointTest(checkpoint_test_base.CheckpointTestBase,
+  @combinations.generate(
-                        parameterized.TestCase):
+      combinations.times(test_base.default_test_combinations())
+  )
+  def testZipBasicWithNoInput(self):
+    with self.assertRaisesRegex(
+        TypeError, r"Must pass at least one dataset to `zip`."
+    ):
+      dataset_ops.Dataset.zip()
+
+  @combinations.generate(
+      combinations.times(test_base.default_test_combinations())
+  )
+  def InvalidZipInputList(self):
+    with self.assertRaisesRegex(
+        TypeError,
+        r"Invalid input to `zip`. Inputs are expected to be (nested)"
+        r" structures of `tf.data.Dataset` objects. Python `list` is"
+        r" not supported and you should use `tuple` instead.",
+    ):
+      dataset_ops.Dataset.zip([1, 2, 3], [4, 5, 6])
+
+
+class ZipCheckpointTest(
+    checkpoint_test_base.CheckpointTestBase, parameterized.TestCase
+):
 
   def _build_dataset(self, arr, options=None):
     components = [
         np.tile(np.array([[1], [2], [3], [4]]), 20),
         np.tile(np.array([[12], [13], [14], [15]]), 22),
-        np.array(arr)
+        np.array(arr),
     ]
     datasets = [
         dataset_ops.Dataset.from_tensor_slices(component)
@@ -200,6 +238,19 @@ class ZipRandomAccessTest(test_base.DatasetTestBase, parameterized.TestCase):
 
   @combinations.generate(
       combinations.times(test_base.default_test_combinations()))
+  def testZipBasicWithoutTuple(self):
+    dataset = dataset_ops.Dataset.zip(
+        dataset_ops.Dataset.range(1, 4), dataset_ops.Dataset.range(4, 7)
+    )
+    expected_dataset = [(1, 4), (2, 5), (3, 6)]
+    for i in range(3):
+      self.assertEqual(
+          self.evaluate(random_access.at(dataset, index=i)), expected_dataset[i]
+      )
+
+  @combinations.generate(
+      combinations.times(test_base.default_test_combinations())
+  )
   def testZipEqual(self):
     components = [
         np.tile(np.array([[1], [2], [3], [4]]), 20),
@@ -246,6 +297,28 @@ class ZipRandomAccessTest(test_base.DatasetTestBase, parameterized.TestCase):
     with self.assertRaises(errors.OutOfRangeError):
       self.evaluate(random_access.at(dataset, index=4))
 
+  @combinations.generate(test_base.default_test_combinations())
+  def testNestedWithoutTuple(self):
+    components = [
+        np.tile(np.array([[1], [2], [3], [4]]), 20),
+        np.tile(np.array([[12], [13], [14], [15]]), 22),
+        np.array([37.0, 38.0, 39.0, 40.0]),
+    ]
+    datasets = [
+        dataset_ops.Dataset.from_tensor_slices(component)
+        for component in components
+    ]
+    dataset = dataset_ops.Dataset.zip(datasets[0], (datasets[1], datasets[2]))
+    for i in range(4):
+      result1, (result2, result3) = self.evaluate(
+          random_access.at(dataset, index=i)
+      )
+      self.assertAllEqual(components[0][i], result1)
+      self.assertAllEqual(components[1][i], result2)
+      self.assertAllEqual(components[2][i], result3)
+    with self.assertRaises(errors.OutOfRangeError):
+      self.evaluate(random_access.at(dataset, index=4))
+
   @combinations.generate(test_base.default_test_combinations())
   def testNamedTuple(self):
     Foo = collections.namedtuple("Foo", ["x", "y"])

tensorflow/python/data/ops/dataset_ops.py

@@ -1017,7 +1017,7 @@ class DatasetV2(
     # pylint: enable=g-import-not-at-top,protected-access
 
   @staticmethod
-  def zip(datasets, name=None):
+  def zip(*args, datasets=None, name=None):
     """Creates a `Dataset` by zipping together the given datasets.
 
     This method has similar semantics to the built-in `zip()` function
@@ -1026,14 +1026,14 @@ class DatasetV2(
     nesting mechanisms are documented
     [here] (https://www.tensorflow.org/guide/data#dataset_structure).
 
-    >>> # The nested structure of the `datasets` argument determines the
+    >>> # The datasets or nested structure of datasets `*args` argument
-    >>> # structure of elements in the resulting dataset.
+    >>> # determines the structure of elements in the resulting dataset.
     >>> a = tf.data.Dataset.range(1, 4)  # ==> [ 1, 2, 3 ]
     >>> b = tf.data.Dataset.range(4, 7)  # ==> [ 4, 5, 6 ]
-    >>> ds = tf.data.Dataset.zip((a, b))
+    >>> ds = tf.data.Dataset.zip(a, b)
     >>> list(ds.as_numpy_iterator())
     [(1, 4), (2, 5), (3, 6)]
-    >>> ds = tf.data.Dataset.zip((b, a))
+    >>> ds = tf.data.Dataset.zip(b, a)
     >>> list(ds.as_numpy_iterator())
     [(4, 1), (5, 2), (6, 3)]
     >>>
@@ -1041,7 +1041,7 @@ class DatasetV2(
     >>> c = tf.data.Dataset.range(7, 13).batch(2)  # ==> [ [7, 8],
     ...                                            #       [9, 10],
     ...                                            #       [11, 12] ]
-    >>> ds = tf.data.Dataset.zip((a, b, c))
+    >>> ds = tf.data.Dataset.zip(a, b, c)
     >>> for element in ds.as_numpy_iterator():
     ...   print(element)
     (1, 4, array([7, 8]))
@@ -1051,12 +1051,16 @@ class DatasetV2(
     >>> # The number of elements in the resulting dataset is the same as
     >>> # the size of the smallest dataset in `datasets`.
     >>> d = tf.data.Dataset.range(13, 15)  # ==> [ 13, 14 ]
-    >>> ds = tf.data.Dataset.zip((a, d))
+    >>> ds = tf.data.Dataset.zip(a, d)
     >>> list(ds.as_numpy_iterator())
     [(1, 13), (2, 14)]
 
     Args:
-      datasets: A (nested) structure of datasets.
+      *args: Datasets or nested structures of datasets to zip together. This
+        can't be set if `datasets` is set.
+      datasets: A (nested) structure of datasets. This can't be set if `*args`
+        is set. Note that this exists only for backwards compatibility and it is
+        preferred to use *args.
       name: (Optional.) A name for the tf.data operation.
 
     Returns:
@@ -1066,8 +1070,16 @@ class DatasetV2(
     # dataset_ops).
     # pylint: disable=g-import-not-at-top,protected-access
     from tensorflow.python.data.ops import zip_op
+
+    if not args and datasets is None:
+      raise TypeError("Must pass at least one dataset to `zip`.")
+    if args and datasets is not None:
+      raise TypeError("Both `*args` and `datasets` cannot be set.")
+    if len(args) == 1:
+      datasets = args[0]
+    elif len(args) > 1:
+      datasets = args
     return zip_op._zip(datasets, name)
-    # pylint: enable=g-import-not-at-top,protected-access
 
   def concatenate(self, dataset, name=None):
     """Creates a `Dataset` by concatenating the given dataset with this dataset.
@@ -3937,8 +3949,8 @@ class DatasetV1(DatasetV2, data_types.DatasetV1):
 
   @staticmethod
   @functools.wraps(DatasetV2.zip)
-  def zip(datasets, name=None):
+  def zip(*args, datasets=None, name=None):
-    return DatasetV1Adapter(DatasetV2.zip(datasets, name=name))
+    return DatasetV1Adapter(DatasetV2.zip(*args, datasets=datasets, name=name))
 
   @functools.wraps(DatasetV2.concatenate)
   def concatenate(self, dataset, name=None):

tensorflow/python/data/ops/zip_op.py

@@ -32,22 +32,26 @@ class _ZipDataset(dataset_ops.DatasetV2):
     for ds in nest.flatten(datasets):
       if not isinstance(ds, data_types.DatasetV2):
         if isinstance(ds, list):
-          raise TypeError("Invalid `datasets`. `datasets` is expected to be a "
+          raise TypeError(
-                          "(nested) structure of `tf.data.Dataset` objects. "
+              "Invalid input to `zip`. Inputs are expected to be (nested)"
-                          "Python `list` is not supported and you should use "
+              " structures of `tf.data.Dataset` objects. Python `list` is"
-                          "`tuple` instead.")
+              " not supported and you should use `tuple` instead."
+          )
         else:
-          raise TypeError(f"Invalid `datasets`. `datasets` is expected to be a "
+          raise TypeError(
-                          f"(nested) structure of `tf.data.Dataset` objects "
+              "Invalid input to `zip`. Inputs are expected to be (nested)"
-                          f"but encountered object of type {type(ds)}.")
+              " structures of `tf.data.Dataset` objects but"
+              f" encountered object of type {type(ds)}."
+          )
     self._datasets = datasets
     self._structure = nest.pack_sequence_as(
-        self._datasets,
+        self._datasets, [ds.element_spec for ds in nest.flatten(self._datasets)]
-        [ds.element_spec for ds in nest.flatten(self._datasets)])
+    )
     self._name = name
     variant_tensor = gen_dataset_ops.zip_dataset(
         [ds._variant_tensor for ds in nest.flatten(self._datasets)],
-        **self._common_args)
+        **self._common_args,
+    )
     super().__init__(variant_tensor)
 
   def _inputs(self):

tensorflow/tools/api/golden/v1/tensorflow.data.-dataset.pbtxt

@@ -229,6 +229,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v1/tensorflow.data.-fixed-length-record-dataset.pbtxt

@@ -231,6 +231,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v1/tensorflow.data.-t-f-record-dataset.pbtxt

@@ -231,6 +231,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v1/tensorflow.data.-text-line-dataset.pbtxt

@@ -231,6 +231,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-csv-dataset.pbtxt

@@ -231,6 +231,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-random-dataset.pbtxt

@@ -231,6 +231,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v1/tensorflow.data.experimental.-sql-dataset.pbtxt

@@ -231,6 +231,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.-dataset.pbtxt

@@ -196,6 +196,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.-fixed-length-record-dataset.pbtxt

@@ -198,6 +198,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.-t-f-record-dataset.pbtxt

@@ -197,6 +197,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.-text-line-dataset.pbtxt

@@ -198,6 +198,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-csv-dataset.pbtxt

@@ -198,6 +198,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-random-dataset.pbtxt

@@ -199,6 +199,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.data.experimental.-sql-dataset.pbtxt

@@ -198,6 +198,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }

tensorflow/tools/api/golden/v2/tensorflow.experimental.dtensor.-d-tensor-dataset.pbtxt

@@ -199,6 +199,6 @@ tf_class {
   }
   member_method {
     name: "zip"
-    argspec: "args=[\'datasets\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+    argspec: "args=[], varargs=args, keywords=None, defaults=None"
   }
 }