Neprox commited on
Commit
756495b
1 Parent(s): 95247b7

Increment model version

Browse files
Files changed (1) hide show
  1. app.py +9 -5
app.py CHANGED
@@ -6,8 +6,12 @@ import seaborn as sns
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  import matplotlib.pyplot as plt
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  from warnings import warn
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- from dotenv import load_dotenv
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- load_dotenv()
 
 
 
 
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  @st.experimental_memo
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  def load_data():
@@ -23,13 +27,13 @@ def load_data():
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  subreddits_fg.select(features=["subreddit_id", "snapshot_time"]), on=["subreddit_id", "snapshot_time"])
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  df = full_join.read()
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  except Exception as e:
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- warn("Could not load data from feature store (most likely due to Port issues with Hopsworks). Trying to load same data that is stored with the model. Full exception:")
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  warn(str(e))
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  df = None
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  # Load model including the generated images and evaluation scores
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  mr = project.get_model_registry()
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- model_hsfs = mr.get_model("reddit_predict", version=18)
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  model_dir = model_hsfs.download()
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  print("Model directory: {}".format(model_dir))
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@@ -62,7 +66,7 @@ def load_data():
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  df, plots, df_metrics = load_data()
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  if df is None:
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- st.error("Could not load data from feature store or model directory. Please upload the data to the model directory manually as Huggingface has compatibility issues with reading data from Hopsworks.")
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  st.stop()
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  # create a distribution plot of the number of likes using seaborn
 
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  import matplotlib.pyplot as plt
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  from warnings import warn
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+ is_local=False
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+ if is_local:
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+ from dotenv import load_dotenv
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+ load_dotenv()
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+
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+ MODEL_VERSION=22
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  @st.experimental_memo
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  def load_data():
 
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  subreddits_fg.select(features=["subreddit_id", "snapshot_time"]), on=["subreddit_id", "snapshot_time"])
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  df = full_join.read()
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  except Exception as e:
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+ warn("Could not load data from feature store (most likely due to Port issues with Hopsworks). Trying to load the data from the model registry instead. Full exception:")
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  warn(str(e))
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  df = None
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  # Load model including the generated images and evaluation scores
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  mr = project.get_model_registry()
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+ model_hsfs = mr.get_model("reddit_predict", version=MODEL_VERSION)
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  model_dir = model_hsfs.download()
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  print("Model directory: {}".format(model_dir))
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  df, plots, df_metrics = load_data()
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  if df is None:
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+ st.error("Could not load data from feature store or model directory as Huggingface has compatibility issues with parts of the data read API from Hopsworks.")
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  st.stop()
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  # create a distribution plot of the number of likes using seaborn