Sanket45 commited on
Commit
dbfefc3
1 Parent(s): 5658340

model path changed update

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Files changed (1) hide show
  1. src/model.py +4 -6
src/model.py CHANGED
@@ -8,7 +8,7 @@ import torch
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  from prophet.serialize import model_to_json, model_from_json
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  from pytorch_forecasting import Baseline, TemporalFusionTransformer, TimeSeriesDataSet
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  from pytorch_forecasting.models.temporal_fusion_transformer.tuning import optimize_hyperparameters
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-
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  # at beginning of the script
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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@@ -38,11 +38,9 @@ class Model_Load:
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  def store_model_load(self,model_option):
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  if model_option=='TFT':
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  # best_model_path="models/store_item_10_lead_1_v2/lightning_logs/lightning_logs/version_2/checkpoints/epoch=7-step=4472.ckpt"
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- best_model_path="models/store_item_10_lead_1_v3/lightning_logs/lightning_logs/version_0/checkpoints/epoch=7-step=4472.ckpt"
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- best_tft = TemporalFusionTransformer.load_from_checkpoint(best_model_path)
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- # best_tft = TemporalFusionTransformer()
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- # best_tft.load_state_dict(torch.load(best_model_path,map_location=torch.device('cpu')))
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- # best_tft.to('cpu')
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  print('Model Load Sucessfully.')
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  return best_tft
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  elif model_option=='Prophet':
 
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  from prophet.serialize import model_to_json, model_from_json
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  from pytorch_forecasting import Baseline, TemporalFusionTransformer, TimeSeriesDataSet
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  from pytorch_forecasting.models.temporal_fusion_transformer.tuning import optimize_hyperparameters
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+ import pickle
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  # at beginning of the script
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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  def store_model_load(self,model_option):
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  if model_option=='TFT':
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  # best_model_path="models/store_item_10_lead_1_v2/lightning_logs/lightning_logs/version_2/checkpoints/epoch=7-step=4472.ckpt"
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+ # best_model_path="models/store_item_10_lead_1_v3/lightning_logs/lightning_logs/version_0/checkpoints/epoch=7-step=4472.ckpt"
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+ # best_tft = TemporalFusionTransformer.load_from_checkpoint(best_model_path)
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+ best_tft=pickle.load(open("models/cpu_finalized_model_v1.sav", 'rb'))
 
 
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  print('Model Load Sucessfully.')
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  return best_tft
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  elif model_option=='Prophet':