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Zero
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from inference.core.env import AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, LAMBDA
from inference.core.models.classification_base import (
ClassificationBaseOnnxRoboflowInferenceModel,
)
class VitClassification(ClassificationBaseOnnxRoboflowInferenceModel):
"""VitClassification handles classification inference
for Vision Transformer (ViT) models using ONNX.
Inherits:
ClassificationBaseOnnxRoboflowInferenceModel: Base class for ONNX Roboflow Inference.
ClassificationMixin: Mixin class providing classification-specific methods.
Attributes:
multiclass (bool): A flag that specifies if the model should handle multiclass classification.
"""
def __init__(self, *args, **kwargs):
"""Initializes the VitClassification instance.
Args:
*args: Variable length argument list.
**kwargs: Arbitrary keyword arguments.
"""
super().__init__(*args, **kwargs)
self.multiclass = self.environment.get("MULTICLASS", False)
@property
def weights_file(self) -> str:
"""Determines the weights file to be used based on the availability of AWS keys.
If AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are set, it returns the path to 'weights.onnx'.
Otherwise, it returns the path to 'best.onnx'.
Returns:
str: Path to the weights file.
"""
if AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY and LAMBDA:
return "weights.onnx"
else:
return "best.onnx"
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