code: def test_infer_schema_from_pandas_instances(self):
      def func() -> pd.Series[int]:
          pass
  
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtype, np.int64)
      self.assertEqual(inferred.spark_type, LongType())
  
      def func() -> pd.Series[float]:
          pass
  
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtype, np.float64)
      self.assertEqual(inferred.spark_type, DoubleType())
  
      def func() -> "pd.DataFrame[np.float_, str]":
          pass
  
      expected = StructType(
          [
              StructField("c0", DoubleType()),
              StructField("c1", StringType()),
          ]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.float64, np.unicode_])
      self.assertEqual(inferred.spark_type, expected)
  
      def func() -> "pandas.DataFrame[float]":
          pass
  
      expected = StructType([StructField("c0", DoubleType())])
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.float64])
      self.assertEqual(inferred.spark_type, expected)
  
      def func() -> "pd.Series[int]":
          pass
  
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtype, np.int64)
      self.assertEqual(inferred.spark_type, LongType())
  
      def func() -> pd.DataFrame[np.float64, str]:
          pass
  
      expected = StructType(
          [
              StructField("c0", DoubleType()),
              StructField("c1", StringType()),
          ]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.float64, np.unicode_])
      self.assertEqual(inferred.spark_type, expected)
  
      def func() -> pd.DataFrame[np.float_]:
          pass
  
      expected = StructType([StructField("c0", DoubleType())])
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.float64])
      self.assertEqual(inferred.spark_type, expected)
  
      pdf = pd.DataFrame({"a": [1, 2, 3], "b": [3, 4, 5]})
  
      def func() -> pd.DataFrame[pdf.dtypes]:
          pass
  
      expected = StructType(
          [StructField("c0", LongType()), StructField("c1", LongType())]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.int64, np.int64])
      self.assertEqual(inferred.spark_type, expected)
  
      pdf = pd.DataFrame(
          {"a": [1, 2, 3], "b": pd.Categorical(["a", "b", "c"])}
      )
  
      def func() -> pd.Series[pdf.b.dtype]:
          pass
  
      inferred = infer_return_type(func)
      self.assertEqual(
          inferred.dtype, CategoricalDtype(categories=["a", "b", "c"])
      )
      self.assertEqual(inferred.spark_type, LongType())
  
      def func() -> pd.DataFrame[pdf.dtypes]:
          pass
  
      expected = StructType(
          [StructField("c0", LongType()), StructField("c1", LongType())]
      )
      inferred = infer_return_type(func)
      self.assertEqual(
          inferred.dtypes,
          [np.int64, CategoricalDtype(categories=["a", "b", "c"])],
      )
      self.assertEqual(inferred.spark_type, expected)
  
imports: import sys
  import unittest
  import datetime
  import decimal
  from typing import List
  import pandas
  import pandas
  from pandas.api.types import CategoricalDtype
  import numpy
  from pyspark.loose_version import LooseVersion
  from pyspark.sql.types import ArrayType, BinaryType, BooleanType, FloatType, IntegerType, LongType, StringType, StructField, StructType, ByteType, ShortType, DateType, DecimalType, DoubleType, TimestampType
  from pyspark.pandas.typedef import as_spark_type, extension_dtypes_available, extension_float_dtypes_available, extension_object_dtypes_available, infer_return_type, pandas_on_spark_type
  from pyspark import pandas
label_desc: Use image node_id 2 for calling the TypeHintTestsMixin obj's underlying member method code with example usage: obj.test_infer_schema_from_pandas_instances() without return types