Merge branch 'main' into use-correct-docstrfmt-version

datasets/e2e/pytorch/pyproject.toml

@@ -9,7 +9,7 @@ description = "Flower Datasets with PyTorch"
 authors = ["The Flower Authors <[email protected]>"]
 
 [tool.poetry.dependencies]
-python = "^3.8"
+python = "^3.9"
 flwr-datasets = { path = "./../../", extras = ["vision"] }
 torch = "^1.12.0"
 torchvision = "^0.14.1"

datasets/e2e/scikit-learn/pyproject.toml

@@ -9,7 +9,7 @@ description = "Flower Datasets with scikit-learn"
 authors = ["The Flower Authors <[email protected]>"]
 
 [tool.poetry.dependencies]
-python = "^3.8"
+python = "^3.9"
 flwr-datasets = { path = "./../../", extras = ["vision"] }
 scikit-learn = "^1.2.0"
 parameterized = "==0.9.0"

datasets/e2e/tensorflow/pyproject.toml

@@ -9,7 +9,7 @@ description = "Flower Datasets with TensorFlow"
 authors = ["The Flower Authors <[email protected]>"]
 
 [tool.poetry.dependencies]
-python = ">=3.8,<3.11"
+python = ">=3.9,<3.11"
 flwr-datasets = { path = "./../../", extras = ["vision"] }
 tensorflow-cpu = "^2.9.1, !=2.11.1"
 tensorflow-io-gcs-filesystem = "<0.35.0"

datasets/flwr_datasets/mock_utils_test.py

@@ -409,7 +409,11 @@ def _load_mocked_dataset_by_partial_download(
         The dataset with the requested samples.
     """
     dataset = datasets.load_dataset(
-        dataset_name, name=subset_name, split=split_name, streaming=True
+        dataset_name,
+        name=subset_name,
+        split=split_name,
+        streaming=True,
+        trust_remote_code=True,
     )
     dataset_list = []
     # It's a list of dict such that each dict represent a single sample of the dataset

datasets/flwr_datasets/visualization/bar_plot.py

@@ -22,6 +22,7 @@
 from matplotlib import colors as mcolors
 from matplotlib import pyplot as plt
 from matplotlib.axes import Axes
+from matplotlib.figure import Figure
 
 
 # pylint: disable=too-many-arguments,too-many-locals,too-many-branches
@@ -82,10 +83,11 @@ def _plot_bar(
     if "stacked" not in plot_kwargs:
         plot_kwargs["stacked"] = True
 
-    axis = dataframe.plot(
+    axis_df: Axes = dataframe.plot(
         ax=axis,
         **plot_kwargs,
     )
+    assert axis_df is not None, "axis is None after plotting using DataFrame.plot()"
 
     if legend:
         if legend_kwargs is None:
@@ -104,20 +106,22 @@ def _plot_bar(
             shift = min(0.05 + max_len_label_str / 100, 0.15)
             legend_kwargs["bbox_to_anchor"] = (1.0 + shift, 0.5)
 
-        handles, legend_labels = axis.get_legend_handles_labels()
-        _ = axis.figure.legend(
+        handles, legend_labels = axis_df.get_legend_handles_labels()
+        figure = axis_df.figure
+        assert isinstance(figure, Figure), "figure extraction from axes is not a Figure"
+        _ = figure.legend(
             handles=handles[::-1], labels=legend_labels[::-1], **legend_kwargs
         )
 
     # Heuristic to make the partition id on xticks non-overlapping
     if partition_id_axis == "x":
-        xticklabels = axis.get_xticklabels()
+        xticklabels = axis_df.get_xticklabels()
         if len(xticklabels) > 20:
             # Make every other xtick label not visible
             for i, label in enumerate(xticklabels):
                 if i % 2 == 1:
                     label.set_visible(False)
-    return axis
+    return axis_df
 
 
 def _initialize_figsize(

datasets/flwr_datasets/visualization/comparison_label_distribution.py

@@ -30,6 +30,7 @@
 
 
 # pylint: disable=too-many-arguments,too-many-locals
+# mypy: disable-error-code="call-overload"
 def plot_comparison_label_distribution(
     partitioner_list: list[Partitioner],
     label_name: Union[str, list[str]],
@@ -153,7 +154,11 @@ def plot_comparison_label_distribution(
     figsize = _initialize_comparison_figsize(figsize, num_partitioners)
     axes_sharing = _initialize_axis_sharing(size_unit, plot_type, partition_id_axis)
     fig, axes = plt.subplots(
-        1, num_partitioners, layout="constrained", figsize=figsize, **axes_sharing
+        nrows=1,
+        ncols=num_partitioners,
+        figsize=figsize,
+        layout="constrained",
+        **axes_sharing,
     )
 
     if titles is None:

datasets/flwr_datasets/visualization/label_distribution.py

@@ -245,5 +245,7 @@ def plot_label_distributions(
             plot_kwargs,
             legend_kwargs,
         )
-    assert axis is not None
-    return axis.figure, axis, dataframe
+    assert axis is not None, "axis is None after plotting"
+    figure = axis.figure
+    assert isinstance(figure, Figure), "figure extraction from axes is not a Figure"
+    return figure, axis, dataframe

datasets/pyproject.toml

@@ -51,9 +51,9 @@ exclude = [
 ]
 
 [tool.poetry.dependencies]
-python = "^3.8"
+python = "^3.9"
 numpy = "^1.21.0"
-datasets = ">=2.14.6 <2.20.0"
+datasets = ">=2.14.6 <=3.1.0"
 pillow = { version = ">=6.2.1", optional = true }
 soundfile = { version = ">=0.12.1", optional = true }
 librosa = { version = ">=0.10.0.post2", optional = true }