[generator] remove use of deprecated arguments

bob/learn/tensorflow/data/generator.py

@@ -37,7 +37,7 @@ class Generator:
         reader,
         multiple_samples=False,
         shuffle_on_epoch_end=False,
-        **kwargs
+        **kwargs,
     ):
         super().__init__(**kwargs)
         self.reader = reader
@@ -65,6 +65,7 @@ class Generator:
         dataset = tf.data.Dataset.from_tensors(dlk)
         self._output_types = tf.compat.v1.data.get_output_types(dataset)
         self._output_shapes = tf.compat.v1.data.get_output_shapes(dataset)
+        self._element_spec = dataset.element_spec
 
         logger.info(
             "Initializing a dataset with %d %s and %s types and %s shapes",
@@ -84,6 +85,11 @@ class Generator:
         "The shapes of the returned samples"
         return self._output_shapes
 
+    @property
+    def element_spec(self):
+        "The type specification of an element of the dataset"
+        return self._element_spec
+
     def __call__(self):
         """A generator function that when called will yield the samples.
 
@@ -106,7 +112,13 @@ class Generator:
             random.shuffle(self.samples)
 
 
-def dataset_using_generator(samples, reader, **kwargs):
+def dataset_using_generator(
+    samples,
+    reader,
+    multiple_samples=False,
+    shuffle_on_epoch_end=False,
+    **kwargs,
+):
     """
     A generator class which wraps samples so that they can
     be used with tf.data.Dataset.from_generator
@@ -128,8 +140,14 @@ def dataset_using_generator(samples, reader, **kwargs):
         A tf.data.Dataset
     """
 
-    generator = Generator(samples, reader, **kwargs)
+    generator = Generator(
+        samples,
+        reader,
+        multiple_samples=multiple_samples,
+        shuffle_on_epoch_end=shuffle_on_epoch_end,
+        **kwargs,
+    )
     dataset = tf.data.Dataset.from_generator(
-        generator, generator.output_types, generator.output_shapes
+        generator, output_signature=generator.element_spec
     )
     return dataset