Output of function step is not compatible with `sagemaker.clarify.ModelConfig()`

**Describe the bug**
When creating a pipeline combining steps defined using `@step` and `sagemaker.clarify.ModelConfig()` the compilation results in
`AttributeError: 'NoneType' object has no attribute 'sagemaker_session'`.
This make it hard to combine `@step` functions with Clarify steps.

**To reproduce**
execute this script
```
import sagemaker
from sagemaker.clarify import BiasConfig, DataConfig, ModelConfig
from sagemaker.workflow.check_job_config import CheckJobConfig
from sagemaker.workflow.clarify_check_step import (
ClarifyCheckStep,
ModelBiasCheckConfig,
ModelPredictedLabelConfig,
)
from sagemaker.workflow.function_step import step
from sagemaker.workflow.pipeline import Pipeline

sagemaker_session = sagemaker.Session()
role = sagemaker.get_execution_role()
bucket = sagemaker_session.default_bucket()
instance_type = "ml.c5"

@step(instance_type=instance_type)
def dummy_func():
return "single-text"

@step(instance_type=instance_type)
def generate_data():
return "data-uri"

check_job_config = CheckJobConfig(
role=role,
instance_count=1,
instance_type="ml.c5.xlarge",
volume_size_in_gb=120,
sagemaker_session=sagemaker_session,
)

bias_config = BiasConfig(
label_values_or_threshold=15.0,
facet_name=["facet"],
facet_values_or_threshold=None,
)

model_bias_data_config = DataConfig(
s3_data_input_path=generate_data(),
s3_output_path=f"s3://{bucket}/model-bias",
dataset_type="text/csv",
label="label",
predicted_label="prediction",
s3_analysis_config_output_path=f"s3://{bucket}/model-bias/analysis_cfg",
)

model_bias_check_config = ModelBiasCheckConfig(
data_config=model_bias_data_config,
data_bias_config=bias_config,
model_predicted_label_config=ModelPredictedLabelConfig(),
model_config=ModelConfig(
model_name=dummy_func(),
instance_count=1,
instance_type="ml.m5.xlarge",
),
)

model_bias_check_step = ClarifyCheckStep(
name="ModelBiasCheckStep",
clarify_check_config=model_bias_check_config,
check_job_config=check_job_config,
skip_check=True,
register_new_baseline=True,
model_package_group_name="ModelPackageName",
)
pipeline = Pipeline(name="TestPipeline", steps=[model_bias_check_step])
definition = pipeline.definition()
```

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: 2.199.0