def test_show_examples_supervised(self, _): with testing.mock_data(num_examples=20): ds, ds_info = load.load('imagenet2012', split='train', with_info=True, as_supervised=True) visualization.show_examples(ds, ds_info)
def _as_df(ds_name: str, **kwargs) -> pandas.DataFrame: """Loads the dataset as `pandas.DataFrame`.""" with testing.mock_data(num_examples=3): ds, ds_info = load.load(ds_name, split='train', with_info=True, **kwargs) df = as_dataframe.as_dataframe(ds, ds_info) return df
def test_show_examples_graph_with_colors_and_labels(self, _): with testing.mock_data(num_examples=20): ds, ds_info = load.load('ogbg_molpcba', split='train', with_info=True) # Dictionaries used to map nodes and edges to colors. atomic_numbers_to_elements = { 6: 'C', 7: 'N', 8: 'O', 9: 'F', 14: 'Si', 15: 'P', 16: 'S', 17: 'Cl', 35: 'Br,' } elements_to_colors = { element: f'C{index}' for index, element in enumerate( atomic_numbers_to_elements.values()) } bond_types_to_colors = {num: f'C{num}' for num in range(4)} # Node colors are atomic numbers. def node_color_fn(graph): atomic_numbers = 1 + graph['node_feat'][:, 0].numpy() return { index: elements_to_colors[atomic_numbers_to_elements[atomic_number]] for index, atomic_number in enumerate(atomic_numbers) } # Node labels are element names. def node_label_fn(graph): atomic_numbers = 1 + graph['node_feat'][:, 0].numpy() return { index: atomic_numbers_to_elements[atomic_number] for index, atomic_number in enumerate(atomic_numbers) } # Edge colors are bond types. def edge_color_fn(graph): bonds = graph['edge_index'].numpy() bond_types = graph['edge_feat'][:, 0].numpy() return { tuple(bond): bond_types_to_colors[bond_type] for bond, bond_type in zip(bonds, bond_types) } visualization.show_examples(ds, ds_info, node_color_fn=node_color_fn, node_label_fn=node_label_fn, edge_color_fn=edge_color_fn)
def test_show_examples(self, mock_fig): with testing.mock_data(num_examples=20): ds, ds_info = registered.load('imagenet2012', split='train', with_info=True) visualization.show_examples(ds_info, ds) ds, ds_info = registered.load('crema_d', split='validation', with_info=True) visualization.show_examples(ds_info, ds)
def test_show_examples(self): with testing.mock_data(): builder = registered.builder('imagenet2012') visualization.show_statistics(builder.info)
def test_show_examples_missing_sample(self, _): with testing.mock_data(num_examples=3): ds, ds_info = load.load('imagenet2012', split='train', with_info=True) visualization.show_examples(ds.take(3), ds_info)
def test_show_examples_graph(self, _): with testing.mock_data(num_examples=20): ds, ds_info = load.load('ogbg_molpcba', split='train', with_info=True) visualization.show_examples(ds, ds_info)