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Fix serialization of ListConfig in checkpoint state dictionary #1534

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merged 1 commit into from
Oct 16, 2023
Merged

Fix serialization of ListConfig in checkpoint state dictionary #1534

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16 changes: 8 additions & 8 deletions src/super_gradients/training/processing/processing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -139,7 +139,7 @@ class ImagePermute(Processing):
"""

def __init__(self, permutation: Tuple[int, int, int] = (2, 0, 1)):
self.permutation = permutation
self.permutation = tuple(permutation)

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, None]:
processed_image = np.ascontiguousarray(image.transpose(*self.permutation))
Expand Down Expand Up @@ -187,7 +187,7 @@ class StandardizeImage(Processing):

def __init__(self, max_value: float = 255.0):
super().__init__()
self.max_value = max_value
self.max_value = float(max_value)

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, None]:
"""Reverse the channel order of an image.
Expand Down Expand Up @@ -246,7 +246,7 @@ class _DetectionPadding(Processing, ABC):
"""

def __init__(self, output_shape: Tuple[int, int], pad_value: int):
self.output_shape = output_shape
self.output_shape = tuple(output_shape)
self.pad_value = pad_value

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, DetectionPadToSizeMetadata]:
Expand Down Expand Up @@ -288,7 +288,7 @@ class _KeypointsPadding(Processing, ABC):
"""

def __init__(self, output_shape: Tuple[int, int], pad_value: int):
self.output_shape = output_shape
self.output_shape = tuple(output_shape)
self.pad_value = pad_value

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, DetectionPadToSizeMetadata]:
Expand Down Expand Up @@ -351,7 +351,7 @@ class _Rescale(Processing, ABC):
"""

def __init__(self, output_shape: Tuple[int, int]):
self.output_shape = output_shape
self.output_shape = tuple(output_shape)

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, RescaleMetadata]:
scale_factor_h, scale_factor_w = self.output_shape[0] / image.shape[0], self.output_shape[1] / image.shape[1]
Expand All @@ -378,7 +378,7 @@ class _LongestMaxSizeRescale(Processing, ABC):
"""

def __init__(self, output_shape: Tuple[int, int]):
self.output_shape = output_shape
self.output_shape = tuple(output_shape)

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, RescaleMetadata]:
height, width = image.shape[:2]
Expand Down Expand Up @@ -443,7 +443,7 @@ def postprocess_predictions(self, predictions: Prediction, metadata: None) -> Pr
class Resize(ClassificationProcess):
def __init__(self, size: int = 224):
super().__init__()
self.size = size
self.size = int(size)

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, None]:
"""Resize an image.
Expand Down Expand Up @@ -477,7 +477,7 @@ class CenterCrop(ClassificationProcess):

def __init__(self, size: int = 224):
super().__init__()
self.size = size
self.size = int(size)

def preprocess_image(self, image: np.ndarray) -> Tuple[np.ndarray, None]:
"""Crops the given image at the center.
Expand Down