code: def _infer_schema_from_type_hint(type_hint, examples=None):
      has_examples = examples is not None
      if has_examples:
          _validate_is_list(examples)
          _validate_non_empty(examples)
  
      if type_hint == List[str]:
          if has_examples:
              _validate_is_all_string(examples)
          return Schema([ColSpec(type="string", name=None)])
      elif type_hint == List[Dict[str, str]]:
          if has_examples:
              _validate_dict_examples(examples)
              return Schema(
                  [
                      ColSpec(type="string", name=name)
                      for name in examples[0]
                  ]
              )
          else:
              _logger.warning(
                  f"Could not infer schema for {type_hint} because example is missing"
              )
              return Schema([ColSpec(type="string", name=None)])
      else:
          _logger.info(
              "Unsupported type hint: %s, skipping schema inference",
              type_hint,
          )
          return None
  
imports: import logging
  import warnings
  from collections import defaultdict
  from typing import Any, Dict, List, Optional, Union
  import numpy
  import pandas
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.types import DataType
  from mlflow.types.schema import Array, ColSpec, Object, ParamSchema, ParamSpec, Property, Schema, TensorSpec
label_desc: Use image node_id 26 for calling a global function with example usage: _infer_schema_from_type_hint(type_hint, examples) and returns: Schema, None, Schema, Schema