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Fix Codacy Warnings (#477)

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Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-10 15:38:45 +01:00
committed by Nicola Demo
parent e3790e049a
commit 4177bfbb50
157 changed files with 3473 additions and 3839 deletions
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36
tests/test_data/test_graph_dataset.py
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@@ -78,20 +78,12 @@ def test_getitem(conditions_dict, max_conditions_lengths):
data = dataset[50]
assert isinstance(data, dict)
assert all([isinstance(d["input"], Data) for d in data.values()])
assert all([isinstance(d["target"], torch.Tensor) for d in data.values()])
assert all(
[isinstance(d["target"], torch.Tensor) for d in data.values()]
[d["input"].x.shape == torch.Size((20, 10)) for d in data.values()]
)
assert all(
[
d["input"].x.shape == torch.Size((20, 10))
for d in data.values()
]
)
assert all(
[
d["target"].shape == torch.Size((20, 10))
for d in data.values()
]
[d["target"].shape == torch.Size((20, 10)) for d in data.values()]
)
assert all(
[
@@ -99,27 +91,17 @@ def test_getitem(conditions_dict, max_conditions_lengths):
for d in data.values()
]
)
assert all(
[d["input"].edge_attr.shape[0] == 60 for d in data.values()]
)
assert all([d["input"].edge_attr.shape[0] == 60 for d in data.values()])
data = dataset.fetch_from_idx_list([i for i in range(20)])
assert isinstance(data, dict)
assert all([isinstance(d["input"], Data) for d in data.values()])
assert all([isinstance(d["target"], torch.Tensor) for d in data.values()])
assert all(
[isinstance(d["target"], torch.Tensor) for d in data.values()]
[d["input"].x.shape == torch.Size((400, 10)) for d in data.values()]
)
assert all(
[
d["input"].x.shape == torch.Size((400, 10))
for d in data.values()
]
)
assert all(
[
d["target"].shape == torch.Size((400, 10))
for d in data.values()
]
[d["target"].shape == torch.Size((400, 10)) for d in data.values()]
)
assert all(
[
@@ -127,6 +109,4 @@ def test_getitem(conditions_dict, max_conditions_lengths):
for d in data.values()
]
)
assert all(
[d["input"].edge_attr.shape[0] == 1200 for d in data.values()]
)
assert all([d["input"].edge_attr.shape[0] == 1200 for d in data.values()])