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- #!/usr/bin/env python
- import json
- import pandas as pd
- from eas_prediction import TFRequest
- if __name__ == '__main__':
- fg_config = {}
- with open("/Users/zhao/Downloads/feature_list_20260403.json", "r") as f:
- fg_config = json.load(f)
- df = pd.read_csv("/Users/zhao/Downloads/DataWorks_SQL查询_结果3_20260515170950_0.csv").sample(n=500, random_state=50)
- df['r_vid'] = df['vid'].copy()
- shape = df.shape[0]
- req = TFRequest('serving_default')
- for feature_info in fg_config['features']:
- feature_name = feature_info['feature_name']
- value_type = feature_info['value_type']
- if value_type == 'Double':
- df[feature_name] = pd.to_numeric(df[feature_name], errors='coerce').fillna(0).astype(float)
- content = df[feature_name].tolist()
- req.add_feed(feature_name, [shape], TFRequest.DT_DOUBLE, content)
- else:
- df[feature_name] = df[feature_name].astype(object).fillna('-1024').astype(str)
- content = [s.encode('utf-8') for s in df[feature_name].tolist()]
- req.add_feed(feature_name, [shape], TFRequest.DT_STRING, content)
- req.add_fetch('y_return_n_uv')
- req.add_fetch('probs_is_share')
- with open("/Users/zhao/Desktop/warm_up_20260413.bin", "wb") as fw:
- fw.write(req.to_string())
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