CONDA small refactoring
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6
deepl.py
6
deepl.py
@ -14,6 +14,8 @@ import sys
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import mlflow
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import mlflow
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from mlflow.models import infer_signature
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from mlflow.models import infer_signature
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from urllib.parse import urlparse
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from urllib.parse import urlparse
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import zipfile
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mlflow.set_experiment("s444463x")
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mlflow.set_experiment("s444463x")
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def convert_text_to_model_form(text):
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def convert_text_to_model_form(text):
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@ -28,6 +30,8 @@ def train(epochs):
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# print(sys.argv[1])
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# print(sys.argv[1])
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# epochs = int(sys.argv[1])
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# epochs = int(sys.argv[1])
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# epochs=10
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# epochs=10
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with zipfile.ZipFile('stare_zadania/real-or-fake-fake-jobposting-prediction.zip', 'r') as zip_ref:
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zip_ref.extractall('')
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mlflow.log_param("epochs", epochs)
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mlflow.log_param("epochs", epochs)
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# kaggle.api.authenticate()
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# kaggle.api.authenticate()
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@ -183,7 +187,7 @@ def train(epochs):
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torch.save(model, 'model')
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torch.save(model, 'model')
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input_example = data_train[:5]
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input_example = data_train[:5]
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siganture = infer_signature(input_example, np.array(['company_profile']))
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# siganture = infer_signature(input_example, np.array(['company_profile']))
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# path = urlparse(mlflow.get_tracking_uri()).scheme
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# path = urlparse(mlflow.get_tracking_uri()).scheme
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