try
Browse files
dronescapes_reader/multitask_dataset.py
CHANGED
@@ -13,7 +13,7 @@ from lovely_tensors import monkey_patch
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monkey_patch()
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BuildDatasetTuple = tuple[dict[str, list[Path]], list[str]]
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-
MultiTaskItem = tuple[dict[str, tr.Tensor], str, list[str]]
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class NpzRepresentation:
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"""Generic Task with data read from/saved to npz files. Tries to read data as-is from disk and store it as well"""
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@@ -24,7 +24,7 @@ class NpzRepresentation:
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"""Reads the npz data from the disk and transforms it properly"""
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data = np.load(path, allow_pickle=False)
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data = data if isinstance(data, np.ndarray) else data["arr_0"] # in case on npz, we need this as well
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return tr.from_numpy(data)
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def save_to_disk(self, data: tr.Tensor, path: Path):
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"""stores this item to the disk which can then be loaded via `load_from_disk`"""
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@@ -114,7 +114,7 @@ class MultiTaskDataset(Dataset):
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"""
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assert all(item[2] == self.task_names for item in items), ((item[2] for item in items), self.task_names)
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items_name = [item[1] for item in items]
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res = {k: tr.zeros(len(items), *self.data_shape[k]) for k in self.task_names}
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for i in range(len(items)):
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for k in self.task_names:
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res[k][i] = items[i][0][k] if items[i][0][k] is not None else 0
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monkey_patch()
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BuildDatasetTuple = tuple[dict[str, list[Path]], list[str]]
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+
MultiTaskItem = tuple[dict[str, tr.Tensor], str, list[str]] # [{task: data}, stem(name) | list[stem(name)], [tasks]]
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class NpzRepresentation:
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"""Generic Task with data read from/saved to npz files. Tries to read data as-is from disk and store it as well"""
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"""Reads the npz data from the disk and transforms it properly"""
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data = np.load(path, allow_pickle=False)
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data = data if isinstance(data, np.ndarray) else data["arr_0"] # in case on npz, we need this as well
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return tr.from_numpy(data) # can be uint8, float16, float32 etc.
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def save_to_disk(self, data: tr.Tensor, path: Path):
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"""stores this item to the disk which can then be loaded via `load_from_disk`"""
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"""
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assert all(item[2] == self.task_names for item in items), ((item[2] for item in items), self.task_names)
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items_name = [item[1] for item in items]
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res = {k: tr.zeros(len(items), *self.data_shape[k]).float() for k in self.task_names} # float32 always
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for i in range(len(items)):
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for k in self.task_names:
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res[k][i] = items[i][0][k] if items[i][0][k] is not None else 0
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