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maybe lab6
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Szymon Parafiński 2022-06-05 23:45:15 +02:00
parent 2fab1c8ac0
commit 0196c8c5a3
4 changed files with 6 additions and 6 deletions
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4
Dockerfile
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@ -27,8 +27,8 @@ ENV KAGGLE_KEY=${KAGGLE_KEY}
WORKDIR /app
COPY lab2/download.sh .
COPY lab7/biblioteka_DL/dllib.py .
COPY lab7/biblioteka_DL/evaluate.py .
COPY lab6/biblioteka_DL/dllib.py .
COPY lab6/biblioteka_DL/evaluate.py .
COPY biblioteka_DL/imdb_top_1000.csv .
COPY predict.py .
COPY registry.py .

4
dvc.yaml
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@ -1,9 +1,9 @@
stages:
train:
cmd: python3 ./lab7/biblioteka_DL/dllib.py 100
cmd: python3 ./lab6/biblioteka_DL/dllib.py 100
deps:
- data/imdb_top_1000.csv
evaluate:
cmd: python3 ./lab7/biblioteka_DL/evaluate.py
cmd: python3 ./lab6/biblioteka_DL/evaluate.py
deps:
- data/imdb_top_1000.csv

2
lab6/biblioteka_DL/dllib.py
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@ -56,7 +56,7 @@ def normalize_gross(imbd_data):
def prepare_dataset():
df = pd.read_csv('biblioteka_DL/imdb_top_1000.csv')
df = pd.read_csv('data/imdb_top_1000.csv')
df = drop_relevant_columns(df)
df_lowercase = lowercase_columns_names(df)
df = data_to_numeric(df_lowercase)

2
lab6/biblioteka_DL/evaluate.py
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@ -56,7 +56,7 @@ def normalize_gross(imbd_data):
def prepare_dataset():
df = pd.read_csv('biblioteka_DL/imdb_top_1000.csv')
df = pd.read_csv('data/imdb_top_1000.csv')
df = drop_relevant_columns(df)
df_lowercase = lowercase_columns_names(df)
df = data_to_numeric(df_lowercase)