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add more config params
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2 changed files with 18 additions and 9 deletions
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@ -28,8 +28,11 @@ def num_cols(matrix: list[list[int]]) -> int:
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class ManipulateMatrixConfig:
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"""Configuration for Manipulate Matrix dataset generation"""
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min_rows: int = 1 # Minimum number of rows
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min_cols: int = 1 # Minimum number of columns
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max_rows: int = 10 # Maximum number of rows
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max_cols: int = 10 # Maximum number of columns
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max_transforms: int = 5 # Maximum number of transformations to apply
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p_rotate: float = 0.2 # Probability of rotating the matrix
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p_hmirror: float = 0.2 # Probability of horizontally mirroring the matrix
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p_vmirror: float = 0.2 # Probability of vertically mirroring the matrix
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@ -46,8 +49,11 @@ class ManipulateMatrixConfig:
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def validate(self):
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"""Validate configuration parameters"""
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assert 1 <= self.max_rows, "max_rows must be at least 1"
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assert 1 <= self.max_cols, "max_cols must be at least 1"
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assert 1 <= self.min_rows, "min_rows must be at least 1"
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assert 1 <= self.min_cols, "min_cols must be at least 1"
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assert self.min_rows <= self.max_rows, "max_rows must be at least min_rows"
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assert self.min_cols <= self.max_cols, "max_cols must be at least min_cols"
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assert 0 <= self.max_transforms, "max_transforms must be non-negative"
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assert 0 <= self.p_rotate <= 1, "p_rotate must be between 0 and 1"
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assert 0 <= self.p_hmirror <= 1, "p_hmirror must be between 0 and 1"
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assert 0 <= self.p_vmirror <= 1, "p_vmirror must be between 0 and 1"
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@ -86,8 +92,8 @@ class ManipulateMatrixDataset(ProceduralDataset):
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def _get_matrix(self, rng: Random) -> list[list[int]]:
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"""Generate a random matrix"""
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rows = rng.randint(1, self.config.max_rows)
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cols = rng.randint(1, self.config.max_cols)
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rows = rng.randint(self.config.min_rows, self.config.max_rows)
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cols = rng.randint(self.config.min_cols, self.config.max_cols)
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numbers = [rng.randint(0, 9) for _ in range(rows * cols)]
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matrix = [numbers[i * cols : (i + 1) * cols] for i in range(rows)]
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return matrix
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@ -157,14 +163,13 @@ class ManipulateMatrixDataset(ProceduralDataset):
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matrix = self._get_matrix(rng)
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matrix_str = self._matrix_to_str(matrix)
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# Shuffle the order of operations (make sure to copy the list to guarantee same order)
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all_transforms = deepcopy(self._all_transforms)
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rng.shuffle(all_transforms)
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num_transforms = rng.randint(0, self.config.max_transforms)
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transforms = rng.sample(self._all_transforms, num_transforms)
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operations = []
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answer = deepcopy(matrix)
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for transform in all_transforms:
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for transform in transforms:
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# Rotate
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if transform == "rotate" and rng.random() < self.config.p_rotate:
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rotation = rng.choice(list(self._rotations.keys()))
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