code: def test_unsupported_arguments(requests_mock: Mocker):
      url = "http://fake_url2"
  
      path_to_mock_features = os.path.join(
          os.path.dirname(os.path.realpath(__file__)),
          "test_data/binary/mock_features.parquet",
      )
      mock_default_requests(requests_mock, url)
      search_task_id = mock_initial_search(requests_mock, url)
      validation_search_task_id = mock_validation_search(
          requests_mock, url, search_task_id
      )
      mock_initial_progress(requests_mock, url, search_task_id)
      mock_validation_progress(
          requests_mock, url, validation_search_task_id
      )
      ads_search_task_id = mock_initial_and_validation_summary(
          requests_mock,
          url,
          search_task_id,
          validation_search_task_id,
      )
      mock_get_metadata(requests_mock, url, search_task_id)
      mock_get_task_metadata_v2(
          requests_mock,
          url,
          ads_search_task_id,
          ProviderTaskMetadataV2(
              features=[
                  FeaturesMetadataV2(
                      name="feature",
                      type="NUMERIC",
                      source="ads",
                      hit_rate=99.0,
                      shap_value=10.1,
                  )
              ],
              hit_rate_metrics=HitRateMetrics(
                  etalon_row_count=10000,
                  max_hit_count=9990,
                  hit_rate=0.999,
                  hit_rate_percent=99.9,
              ),
              eval_set_metrics=[
                  ModelEvalSet(
                      eval_set_index=1,
                      hit_rate=1.0,
                      hit_rate_metrics=HitRateMetrics(
                          etalon_row_count=1000,
                          max_hit_count=1000,
                          hit_rate=1.0,
                          hit_rate_percent=100.0,
                      ),
                  ),
                  ModelEvalSet(
                      eval_set_index=2,
                      hit_rate=0.99,
                      hit_rate_metrics=HitRateMetrics(
                          etalon_row_count=1000,
                          max_hit_count=990,
                          hit_rate=0.99,
                          hit_rate_percent=99.0,
                      ),
                  ),
              ],
          ),
      )
      mock_raw_features(
          requests_mock, url, search_task_id, path_to_mock_features
      )
      mock_validation_raw_features(
          requests_mock,
          url,
          validation_search_task_id,
          path_to_mock_features,
      )
  
      enricher = FeaturesEnricher(
          search_keys={"date": SearchKey.DATE},
          endpoint=url,
          api_key="fake_api_key",
          logs_enabled=False,
          unsupported_argument="some_value",
      )
  
      df = pd.DataFrame(
          {
              "date": [
                  "2021-01-01",
                  "2021-01-02",
                  "2023-01-01",
                  "2023-01-02",
              ],
              "feature": [11, 10, 12, 13],
              "target": [0, 1, 0, 1],
          }
      )
  
      original_min_rows = Dataset.MIN_ROWS_COUNT
      Dataset.MIN_ROWS_COUNT = 3
      try:
          # with pytest.raises(NoMockAddress):
          enricher.fit(
              df.drop(columns="target"),
              df["target"],
              [(df.drop(columns="target"), df["target"])],
              "unsupported_positional_argument",
              unsupported_key_argument=False,
          )
  
          # with pytest.raises(NoMockAddress):
          enricher.fit_transform(
              df.drop(columns="target"),
              df["target"],
              [(df.drop(columns="target"), df["target"])],
              "unsupported_positional_argument",
              unsupported_key_argument=False,
          )
  
          enricher.transform(
              df.drop(columns="target"),
              "unsupported_positional_argument",
              unsupported_key_argument=False,
          )
  
          enricher.calculate_metrics(
              df.drop(columns="target"),
              df["target"],
              [(df.drop(columns="target"), df["target"])],
              "unsupported_positional_argument",
              unsupported_key_argument=False,
          )
      finally:
          Dataset.MIN_ROWS_COUNT = original_min_rows
  
imports: import os
  from datetime import date
  from typing import List, Optional
  import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from requests_mock.mocker import Mocker
  from upgini import FeaturesEnricher, SearchKey
  from upgini.dataset import Dataset
  from upgini.errors import ValidationError
  from upgini.http import _RestClient
  from upgini.metadata import CVType, FeaturesMetadataV2, HitRateMetrics, ModelEvalSet, ModelTaskType, ProviderTaskMetadataV2, RuntimeParameters
  from upgini.resource_bundle import bundle
  from upgini.search_task import SearchTask
  from upgini.utils.datetime_utils import DateTimeSearchKeyConverter
  from .utils import mock_default_requests, mock_get_metadata, mock_get_task_metadata_v2, mock_initial_and_validation_summary, mock_initial_progress, mock_initial_search, mock_initial_summary, mock_raw_features, mock_validation_progress, mock_validation_raw_features, mock_validation_search, mock_validation_summary
label_desc: Use image node_id 31 for calling a global function with example usage: test_unsupported_arguments(requests_mock) without return types