Update docstring empty output

Lightning-Universe · Jan 25, 2022 · be7214f · be7214f
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commit be7214f
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Showing 4 changed files with 18 additions and 9 deletions.
diff --git a/flash/image/classification/data.py b/flash/image/classification/data.py
@@ -849,7 +849,8 @@ def from_fiftyone(
             >>> train_dataset = fo.Dataset.from_images(
             ...     ["image_1.png", "image_2.png", "image_3.png"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> samples = [train_dataset[filepath] for filepath in train_dataset.values("filepath")]
             >>> for sample, label in zip(samples, ["cat", "dog", "cat"]):
             ...     sample["ground_truth"] = fo.Classification(label=label)
@@ -858,7 +859,8 @@ def from_fiftyone(
             >>> predict_dataset = fo.Dataset.from_images(
             ...     ["predict_image_1.png", "predict_image_2.png", "predict_image_3.png"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> datamodule = ImageClassificationData.from_fiftyone(
             ...     train_dataset=train_dataset,
             ...     predict_dataset=predict_dataset,

diff --git a/flash/image/detection/data.py b/flash/image/detection/data.py
@@ -655,7 +655,8 @@ def from_fiftyone(
             >>> train_dataset = fo.Dataset.from_images(
             ...     ["image_1.png", "image_2.png", "image_3.png"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> samples = [train_dataset[filepath] for filepath in train_dataset.values("filepath")]
             >>> for sample, label, bounding_box in zip(
             ...     samples,
@@ -670,14 +671,16 @@ def from_fiftyone(
             >>> predict_dataset = fo.Dataset.from_images(
             ...     ["predict_image_1.png", "predict_image_2.png", "predict_image_3.png"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> datamodule = ObjectDetectionData.from_fiftyone(
             ...     train_dataset=train_dataset,
             ...     predict_dataset=predict_dataset,
             ...     transform_kwargs=dict(image_size=(128, 128)),
             ...     batch_size=2,
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            Computing...
+            <BLANKLINE>
+            ...
             >>> datamodule.num_classes
             3
             >>> datamodule.labels

diff --git a/flash/image/segmentation/data.py b/flash/image/segmentation/data.py
@@ -584,7 +584,8 @@ def from_fiftyone(
             >>> train_dataset = fo.Dataset.from_images(
             ...     ["image_1.png", "image_2.png", "image_3.png"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> samples = [train_dataset[filepath] for filepath in train_dataset.values("filepath")]
             >>> for sample in samples:
             ...     sample["ground_truth"] = fo.Segmentation(mask=np.random.randint(0, 10, (64, 64), dtype="uint8"))
@@ -593,7 +594,8 @@ def from_fiftyone(
             >>> predict_dataset = fo.Dataset.from_images(
             ...     ["predict_image_1.png", "predict_image_2.png", "predict_image_3.png"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> datamodule = SemanticSegmentationData.from_fiftyone(
             ...     train_dataset=train_dataset,
             ...     predict_dataset=predict_dataset,

diff --git a/flash/video/classification/data.py b/flash/video/classification/data.py
@@ -818,7 +818,8 @@ def from_fiftyone(
             >>> train_dataset = fo.Dataset.from_videos(
             ...     ["video_1.mp4", "video_2.mp4", "video_3.mp4"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> samples = [train_dataset[filepath] for filepath in train_dataset.values("filepath")]
             >>> for sample, label in zip(samples, ["cat", "dog", "cat"]):
             ...     sample["ground_truth"] = fo.Classification(label=label)
@@ -827,7 +828,8 @@ def from_fiftyone(
             >>> predict_dataset = fo.Dataset.from_images(
             ...     ["predict_video_1.mp4", "predict_video_2.mp4", "predict_video_3.mp4"]
             ... )  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-            33%...
+            <BLANKLINE>
+            ...
             >>> datamodule = VideoClassificationData.from_fiftyone(
             ...     train_dataset=train_dataset,
             ...     predict_dataset=predict_dataset,