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import torch
def validate_sequence(sequence):
valid_amino_acids = set("ACDEFGHIKLMNPQRSTVWY") # 20 standard amino acids
return all(aa in valid_amino_acids for aa in sequence) and len(sequence) <= 200
def load_model():
# Assuming the model is a simple PyTorch model, adjust the path as needed
model = torch.load('model.pth', map_location=torch.device('cpu'))
model.eval()
return model
def predict(model, sequence):
# Dummy tensor conversion, replace with your actual model's input handling
tensor = torch.tensor([ord(char) for char in sequence], dtype=torch.float32)
output = model(tensor)
return output.item()
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