MLFlow inprogress

This commit is contained in:
Mikołaj Pokrywka 2022-05-22 21:37:36 +02:00
parent 0c67053401
commit 8b99b7e9e9
131 changed files with 60 additions and 302 deletions

4
.gitignore vendored
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@ -14,4 +14,6 @@ model_resutls.txt
model model
metrics.txt metrics.txt
metrics.png metrics.png
my_runs my_runs
mlruns
modelML

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@ -14,4 +14,4 @@ WORKDIR /app
COPY ./deepl.py . COPY ./deepl.py .
COPY ./MLProject . COPY ./MLProject .
# CMD python3 deepl.py # CMD python3 deepl.py 10

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@ -1,4 +1,4 @@
name: s444463 name: s444463x
docker_env: docker_env:
image: ium_444463 image: ium_444463

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@ -14,9 +14,8 @@ import sys
import mlflow import mlflow
from mlflow.models import infer_signature from mlflow.models import infer_signature
mlflow.set_tracking_uri("http://172.17.0.1:5000")
mlflow.set_experiment("s444463")
mlflow.set_experiment("s444463x")
def convert_text_to_model_form(text): def convert_text_to_model_form(text):
a = vectorizer.transform([text]) a = vectorizer.transform([text])
b = torch.tensor(scipy.sparse.csr_matrix.todense(a)).float() b = torch.tensor(scipy.sparse.csr_matrix.todense(a)).float()
@ -183,8 +182,10 @@ def train(epochs):
f.close() f.close()
torch.save(model, 'model') torch.save(model, 'model')
mlflow.pytorch.log_model(model, "model", signature=siganture, input_example=input_example) input_example = data_train[:5]
mlflow.pytorch.save_model(model, "model", signature=siganture, input_example=input_example) siganture = infer_signature(input_example, np.array(['company_profile']))
mlflow.pytorch.log_model(model, "modelML", signature=siganture, input_example=input_example)
mlflow.pytorch.save_model(model, "modelML", signature=siganture, input_example=input_example)
print(sys.argv[1]) print(sys.argv[1])
@ -193,6 +194,15 @@ print(sys.argv[1])
epochs = int(sys.argv[1]) epochs = int(sys.argv[1])
if __name__ == "__main__": if __name__ == "__main__":
# mlflow.set_tracking_uri("http://172.17.0.1:5000")
# with mlflow.start_run() as run:
# mlflow.set_tracking_uri("http://172.17.0.1:5000")
# mlflow.set_experiment("s444463")
mlflow.log_param("TEST", 'TEST')
train(epochs) train(epochs)
# plt.figure(figsize=(12, 5)) # plt.figure(figsize=(12, 5))

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