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import torch |
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from safetensors.torch import load_model, save_model |
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import logging |
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") |
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class CharmModel: |
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"""Handles loading and saving advanced safetensors models for Charm 15.""" |
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def __init__(self, model_path: str): |
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self.model_path = model_path |
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self.model = None |
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def load(self): |
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"""Loads Model 2 of 10 safely with optimized memory handling.""" |
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try: |
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logging.info(f"Loading model from {self.model_path}...") |
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self.model = load_model(torch.nn.Module(), self.model_path) |
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logging.info("Model loaded successfully.") |
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except Exception as e: |
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logging.error(f"Error loading model: {e}") |
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def save(self, save_path: str): |
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"""Saves the model safely in safetensors format.""" |
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if self.model: |
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try: |
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logging.info(f"Saving model to {save_path}...") |
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save_model(self.model, save_path) |
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logging.info("Model saved successfully.") |
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except Exception as e: |
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logging.error(f"Error saving model: {e}") |
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else: |
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logging.warning("No model loaded. Cannot save.") |
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def infer(self, input_data): |
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"""Runs inference on the loaded model (Placeholder for actual logic).""" |
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if self.model: |
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logging.info("Running inference...") |
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return "Inference result" |
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else: |
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logging.warning("No model loaded. Cannot perform inference.") |
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return None |