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Commit 3b063700 authored by Yandi's avatar Yandi
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modified create submission to make it work with job batches

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...@@ -30,7 +30,7 @@ def dummy_model(X): ...@@ -30,7 +30,7 @@ def dummy_model(X):
# Divided by a magic number # Divided by a magic number
return X[:, :, 4:].mean(dim=2) / 26 # This is (B, T) return X[:, :, 4:].mean(dim=2) / 26 # This is (B, T)
def create_submission(model, transform, device): def create_submission(model, transform, device, rootDir):
step_days = 10 step_days = 10
batch_size = 1024 batch_size = 1024
# We make chunks of num_days consecutive samples; As our dummy predictor # We make chunks of num_days consecutive samples; As our dummy predictor
...@@ -57,7 +57,7 @@ def create_submission(model, transform, device): ...@@ -57,7 +57,7 @@ def create_submission(model, transform, device):
num_days_test = test_loader.dataset.ntimes num_days_test = test_loader.dataset.ntimes
logging.info("= Filling in the submission file") logging.info("= Filling in the submission file")
with open("submission.csv", "w") as fh_submission: with open(rootDir + "submission.csv", "w") as fh_submission:
fh_submission.write("Id,Predicted\n") fh_submission.write("Id,Predicted\n")
submission_offset = 0 submission_offset = 0
......
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...@@ -132,4 +132,4 @@ if __name__ == "__main__": ...@@ -132,4 +132,4 @@ if __name__ == "__main__":
wandb.log({"val_loss": val_loss}) wandb.log({"val_loss": val_loss})
create_submission.create_submission(network, dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_min_max_scaling(MIN, MAX)), device) create_submission.create_submission(network, dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_min_max_scaling(MIN, MAX)), device, rootDir)
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