def __init__(self):
self.dataset = ProcessData(train_ratio=0.8,process_raw_data=False,do_augment=False, image_type='OA',
get_scale_center=False, single_sample=True,
do_blur=False, do_crop=False, do_deform=False, do_flip=True)
self.model = cnn_skipC_OA_model.cnn_skipC_OA_model(
criterion=nn.MSELoss(),
optimizer= torch.optim.Adam,
learning_rate=0.001,
weight_decay=0
)
def GenerateModel(dictionary, id):
demand = ProcessData.ProcessData(dictionary)
Prediction.GenerateModel(dictionary, demand)
latestPrediction = Prediction.GetPrediction(dictionary, demand)
loadDict[id] = latestPrediction
with open("savedPredictions.txt", "a+") as outfile:
json.dump({"id": id, "predictions": latestPrediction}, outfile)
outfile.write("\n")
print("latestPrediction type: ", type(latestPrediction),
"\n latestPrediction: ", latestPrediction)
return "Model Generation completed."
