Removed unnecessary lines
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1 changed files with 0 additions and 16 deletions
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@ -35,28 +35,12 @@ def split(data, k):
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train_samples.extend(samples[j*bucketsize:(j+1)*bucketsize])
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train_samples.extend(samples[j*bucketsize:(j+1)*bucketsize])
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# Create new dictionaries in the eval lists
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# Create new dictionaries in the eval lists
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#X_eval.append({'dc': eval_samples[:-1]})
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#y_eval.append({'dc': eval_samples[-1]})
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X_eval.append({'dc': [x for s in eval_samples for c, x in enumerate(s, 1) if c % 337 != 0]})
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X_eval.append({'dc': [x for s in eval_samples for c, x in enumerate(s, 1) if c % 337 != 0]})
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y_eval.append({'dc': [x for s in eval_samples for c, x in enumerate(s, 1) if c % 337 == 0]})
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y_eval.append({'dc': [x for s in eval_samples for c, x in enumerate(s, 1) if c % 337 == 0]})
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#X_train.append({'dc': train_samples[:-1]})
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#y_train.append({'dc': train_samples[-1]})
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X_train.append({'dc': [x for s in train_samples for c, x in enumerate(s, 1) if c % 337 != 0]})
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X_train.append({'dc': [x for s in train_samples for c, x in enumerate(s, 1) if c % 337 != 0]})
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y_train.append({'dc': [x for s in train_samples for c, x in enumerate(s, 1) if c % 337 == 0]})
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y_train.append({'dc': [x for s in train_samples for c, x in enumerate(s, 1) if c % 337 == 0]})
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#print(len(X_eval))
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#print(len(y_eval))
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#print(len(X_train))
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#print(len(y_train))
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#print(len(X_train[0]['dc']))
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#print(len(y_train[0]['dc']))
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#print(len(X_eval[0]['dc']))
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#print(len(y_eval[0]['dc']))
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#print(X_train)
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#print(y_train)
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#exit(0)
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return X_train, y_train, X_eval, y_eval
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return X_train, y_train, X_eval, y_eval
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