我一直很难将我本地训练的SKlearn模型（自定义代码+逻辑模型的管道）部署到Sagemaker Endpoint。我的管道如下：

所有这些自定义代码（RecodeCategorias）所做的就是规范化并将一些类别列重新编码为“其他”值，用于某些功能：

class RecodeCategorias(BaseEstimator, TransformerMixin):

def __init__(self, feature, categs, exclude=True):
    self.feature = feature
    self.categs = categs
    self.exclude = exclude

def fit(self, X, y=None):
    return self

def transform(self, X, y=None):
    X[self.feature] = X[self.feature].str.lower().str.strip()
    if self.exclude is True:
        X[self.feature] = np.where(
            (X[self.feature].isin(self.categs)) & (~X[self.feature].isna()),
            "outro",
            X[self.feature],
        )
    elif self.exclude is False:
        X[self.feature] = np.where(
            (X[self.feature].isin(self.categs)) | (X[self.feature].isna()),
            X[self.feature],
            "outro",
        )
    else:
        raise ValueError(
            """PLease set exclude the categs to True (to change the categs to 'others')
            or False (to keep the categs and change the remaning to 'others')"""
        )
    return X

我的模型数据保存在tar.gz文件中的S3存储桶中，该文件包含：inference.py、model.joblib和pipeline.joblib。我的部署脚本是：

modelo = SKLearnModel(
model_data='s3://'+s3_bucket+"/"+prefix+"/"+model_path,
role=role,
entry_point="inference.py",
framework_version="1.0-1",
py_version="py3",
sagemaker_session=sagemaker_session,
name="testesdk3",
source_dir='custom_transformers',
dependencies=['custom_transformers/recodefeat.py']
)
try:
    r = modelo.deploy(
             endpoint_name="testesdkendpoint3",
             serverless_inference_config=ServerlessInferenceConfig(
             memory_size_in_mb=4096, max_concurrency=100),
             )
    print(f"Model deploy with name: {modelo.name} and endpoint {modelo.endpoint_name}")
except Exception as e:
   print(e)

重点是我试过了

• 将类定义添加到model.tar.gz的根目录下的文件中，并将其传递给依赖项（由于相同的文件夹，因此也应该从本地文件中获取相同的文件）
• 添加到“custom_transformers”到与www.example.com相同目录下的文件夹中inference.py，并将其传递到dependencies或source_dir。

我尝试过AWS Sagemaker SKlearn entry point allow multiple script、AWS Sagemaker SKlearn entry point allow multiple script和https://github.com/aws/amazon-sagemaker-examples/issues/725的解决方案，但似乎都不起作用，总是给予我一个

sagemaker_containers._errors.ClientError: Can't get attribute 'RecodeCategorias' on <module '__main__' from '/miniconda3/bin/gunicorn'>

我到底应该如何传递我的类依赖关系才能正确加载它？
谢谢