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Homework sacred

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This commit is contained in:
Mikołaj Pokrywka 2022-05-07 14:23:09 +02:00
parent b553894099
commit 2a439a88b2
3 changed files with 20 additions and 9 deletions
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3
.gitignore vendored
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@ -13,4 +13,5 @@ venv
model_resutls.txt model_resutls.txt
model model
metrics.txt metrics.txt
metrics.png metrics.png
my_runs

2
Jenkinsfile vendored
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@ -21,7 +21,7 @@ pipeline {
withEnv(["EPOCH=${params.EPOCH}"]) { withEnv(["EPOCH=${params.EPOCH}"]) {
copyArtifacts filter: '*', projectName: 's444463-create-dataset' copyArtifacts filter: '*', projectName: 's444463-create-dataset'
sh 'python3 ./deepl.py $EPOCH' sh 'python3 ./deepl.py $EPOCH'
archiveArtifacts artifacts: "model" archiveArtifacts artifacts: "model, my_runs"
build job: "s444463-evaluation/master" build job: "s444463-evaluation/master"
} }
} }

24
deepl.py
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@ -10,7 +10,17 @@ from torch import nn
from torch import optim from torch import optim
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import sys import sys
from sacred import Experiment
from sacred.observers import FileStorageObserver
ex = Experiment()
ex.observers.append(FileStorageObserver('my_runs'))
vectorizer = TfidfVectorizer()
@ex.config
def my_config():
epochs = 10
def convert_text_to_model_form(text): def convert_text_to_model_form(text):
@ -18,12 +28,12 @@ def convert_text_to_model_form(text):
b = torch.tensor(scipy.sparse.csr_matrix.todense(a)).float() b = torch.tensor(scipy.sparse.csr_matrix.todense(a)).float()
return b return b
@ex.automain
if __name__ == "__main__": def my_main(epochs, _run):
print(sys.argv[1]) # print(sys.argv[1])
print(type(sys.argv[1])) # print(type(sys.argv[1]))
print(sys.argv[1]) # print(sys.argv[1])
epochs = int(sys.argv[1]) # epochs = int(sys.argv[1])
# epochs=10 # epochs=10
# kaggle.api.authenticate() # kaggle.api.authenticate()
@ -59,7 +69,6 @@ if __name__ == "__main__":
y_dev = np.array(y_dev) y_dev = np.array(y_dev)
y_test = np.array(y_test) y_test = np.array(y_test)
vectorizer = TfidfVectorizer()
company_profile = vectorizer.fit_transform(company_profile) company_profile = vectorizer.fit_transform(company_profile)
x_train = vectorizer.transform(x_train) x_train = vectorizer.transform(x_train)
@ -172,6 +181,7 @@ if __name__ == "__main__":
f.close() f.close()
torch.save(model, 'model') torch.save(model, 'model')
ex.add_artifact("model")
# plt.figure(figsize=(12, 5)) # plt.figure(figsize=(12, 5))