هو اي حل المشكله دي GatewayRuntimeError في بايثون؟

لديك مشكلة في عدم تطابق طول البيانات عند إنشاء إطار البيانات النهائي، بسبب استخدام متغير غير معرف data_test_copy بدلاً من استخدام نفس إطار البيانات الذي يحتوي على الميزات أي استخدم df أو test لاستخراج date_id وليس data_test_copy.

أيضًا الدالة حددت لها بأن تُعيد float لكن النتيجة هي pd.DataFrame، يجب تصحيح ذلك إلى pd.DataFrame

import pandas as pd
import tensorflow as tf
import kaggle_evaluation
import os

col = ['D1','D2','D3','D4','D5','D6','D7','D8','D9','E1','E10','E11','E12','E13','E14',
       'E15','E16','E17','E18','E19','E2','E20','E3','E4','E5','E6','E7','E8','E9','I1',
       'I2','I3','I4','I5','I6','I7','I8','I9','M1','M10','M11','M12','M13','M14','M15',
       'M16','M17','M18','M2','M3','M4','M5','M6','M7','M8','M9','P1','P10','P11','P12',
       'P13','P2','P3','P4','P5','P6','P7','P8','P9','S1','S10','S11','S12','S2','S3',
       'S4','S5','S6','S7','S8','S9','V1','V10','V11','V12','V13','V2','V3','V4','V5',
       'V6','V7','V8','V9','is_scored','lagged_risk_free_rate',
       'lagged_market_forward_excess_returns']

model_path = 'AlphaPulse.keras'
if not os.path.exists(model_path):
    model_path = '/kaggle/working/AlphaPulse.keras'
model = tf.keras.models.load_model(model_path)

def predict(test: pd.DataFrame) -> pd.DataFrame:
    df = test.copy()
    missing_cols = set(col) - set(df.columns)
    if missing_cols:
        raise ValueError(f"missing columns: {missing_cols}")
    x_test = df[col]
    preds = model.predict(x_test, verbose=0)
    allocation = preds.clip(0, 2).reshape(-1)
    if len(allocation) != len(df):
        raise ValueError(f"prediction length ({len(allocation)})  doesn't match data length ({len(df)})")
    return pd.DataFrame({
        "date_id": df["date_id"].values,
        "prediction": allocation
    })

inference_server = kaggle_evaluation.default_inference_server.DefaultInferenceServer(predict)

if os.getenv('KAGGLE_IS_COMPETITION_RERUN'):
    inference_server.serve()
else:
    inference_server.run_local_gateway(('/kaggle/input/hull-tactical-market-prediction/',))

بتاريخ 2 ساعة قال Mustafa Suleiman:

لديك مشكلة في عدم تطابق طول البيانات عند إنشاء إطار البيانات النهائي، بسبب استخدام متغير غير معرف data_test_copy بدلاً من استخدام نفس إطار البيانات الذي يحتوي على الميزات أي استخدم df أو test لاستخراج date_id وليس data_test_copy.

 

ايوه بس اطار البيانات ده انا مسح منو العمود ده في بيانات التدريب وكمان الاختبار عشان كده عملت copy البيانات ؟

حذفت date_id من test نفسه؟ إذن يجب تمرير إطار بيانات يحتوي على date_id.

import pandas as pd
import tensorflow as tf
import kaggle_evaluation
import os

col = ['D1','D2','D3','D4','D5','D6','D7','D8','D9','E1','E10','E11','E12','E13','E14',
       'E15','E16','E17','E18','E19','E2','E20','E3','E4','E5','E6','E7','E8','E9','I1',
       'I2','I3','I4','I5','I6','I7','I8','I9','M1','M10','M11','M12','M13','M14','M15',
       'M16','M17','M18','M2','M3','M4','M5','M6','M7','M8','M9','P1','P10','P11','P12',
       'P13','P2','P3','P4','P5','P6','P7','P8','P9','S1','S10','S11','S12','S2','S3',
       'S4','S5','S6','S7','S8','S9','V1','V10','V11','V12','V13','V2','V3','V4','V5',
       'V6','V7','V8','V9','is_scored','lagged_risk_free_rate',
       'lagged_market_forward_excess_returns']

model_path = 'AlphaPulse.keras'
if not os.path.exists(model_path):
    model_path = '/kaggle/working/AlphaPulse.keras'
model = tf.keras.models.load_model(model_path)

def predict(test: pd.DataFrame, test_with_dates: pd.DataFrame) -> pd.DataFrame:
    df = test.copy()
    x_test = df[col]
    preds = model.predict(x_test, verbose=0)
    allocation = preds.clip(0, 2).reshape(-1)
    return pd.DataFrame({
        "date_id": test_with_dates["date_id"].values,
        "prediction": allocation
    })

inference_server = kaggle_evaluation.default_inference_server.DefaultInferenceServer(predict)

if os.getenv('KAGGLE_IS_COMPETITION_RERUN'):
    inference_server.serve()
else:
    inference_server.run_local_gateway(('/kaggle/input/hull-tactical-market-prediction/',))

بس بتحصل بقا المشكله دي 

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/templates.py:95: RuntimeWarning: 1889 seconds elapsed before server startup.
                This exceeds the startup time limit of 900 seconds that the gateway will enforce
                during the rerun on the hidden test set. Start the server before performing any time consuming steps.
  warnings.warn(
---------------------------------------------------------------------------
GatewayRuntimeError                       Traceback (most recent call last)
/tmp/ipykernel_39/2380296845.py in <cell line: 0>()
     38     inference_server.serve()
     39 else:
---> 40     inference_server.run_local_gateway(('/kaggle/input/hull-tactical-market-prediction/',))

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/templates.py in run_local_gateway(self, data_paths, file_share_dir, *args, **kwargs)
    106             self.gateway.run()
    107         except Exception as err:
--> 108             raise err from None
    109         finally:
    110             self.server.stop(0)

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/templates.py in run_local_gateway(self, data_paths, file_share_dir, *args, **kwargs)
    104         try:
    105             self.gateway = self._get_gateway_for_test(data_paths, file_share_dir, *args, **kwargs)
--> 106             self.gateway.run()
    107         except Exception as err:
    108             raise err from None

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/base_gateway.py in run(self)
    149         elif error:
    150             # For local testing
--> 151             raise error
    152 
    153     @final

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/base_gateway.py in run(self)
    130         try:
    131             self.unpack_data_paths()
--> 132             predictions, row_ids = self.get_all_predictions()
    133             self.write_submission(predictions, row_ids)
    134         except GatewayRuntimeError as gre:

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/base_gateway.py in get_all_predictions(self)
    106         self.data_batch_counter = 0
    107         for data_batch, row_ids in self.generate_data_batches():
--> 108             predictions = self.predict(*data_batch)
    109             self.competition_agnostic_validation(predictions, row_ids)
    110             self.competition_specific_validation(predictions, row_ids, data_batch)

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/base_gateway.py in predict(self, *args, **kwargs)
    124             return self.client.send('predict', *args, **kwargs)
    125         except Exception as e:
--> 126             self.handle_server_error(e, 'predict')
    127 
    128     def run(self) -> None:

/kaggle/input/hull-tactical-market-prediction/kaggle_evaluation/core/base_gateway.py in handle_server_error(self, exception, endpoint)
    429             message_match = re.search('"Exception calling application: (.*)"', exception_str, re.IGNORECASE)
    430             message = message_match.group(1) if message_match else exception_str
--> 431             raise GatewayRuntimeError(GatewayRuntimeErrorType.SERVER_RAISED_EXCEPTION, message) from None
    432         if isinstance(exception, grpc._channel._InactiveRpcError):
    433             raise GatewayRuntimeError(GatewayRuntimeErrorType.SERVER_CONNECTION_FAILED, exception_str) from None

GatewayRuntimeError: (<GatewayRuntimeErrorType.SERVER_RAISED_EXCEPTION: 3>, "predict() missing 1 required positional argument: 'test_with_dates'")