code: def floating_dtypes(
      *,
      endianness: str = "?",
      sizes: Sequence[Literal[16, 32, 64, 96, 128]] = (16, 32, 64),
  ) -> st.SearchStrategy[np.dtype]:
      """Return a strategy for floating-point dtypes.
  
      sizes is the size in bits of floating-point number.  Some machines support
      96- or 128-bit floats, but these are not generated by default.
  
      Larger floats (96 and 128 bit real parts) are not supported on all
      platforms and therefore disabled by default.  To generate these dtypes,
      include these values in the sizes argument.
      """
      return dtype_factory(
          "f", sizes, (16, 32, 64, 96, 128), endianness
      )
  
imports: import importlib
  import math
  from typing import TYPE_CHECKING, Any, Literal, Mapping, Optional, Sequence, Tuple, Type, TypeVar, Union
  import numpy
  from hypothesis import strategies
  from hypothesis._settings import note_deprecation
  from hypothesis.errors import HypothesisException, InvalidArgument
  from hypothesis.extra._array_helpers import NDIM_MAX, BasicIndex, BasicIndexStrategy, BroadcastableShapes, Shape, array_shapes, broadcastable_shapes, check_argument, check_valid_dims, mutually_broadcastable_shapes, order_check, valid_tuple_axes
  from hypothesis.internal.conjecture import utils
  from hypothesis.internal.coverage import check_function
  from hypothesis.internal.reflection import proxies
  from hypothesis.internal.validation import check_type
  from hypothesis.strategies._internal.numbers import Real
  from hypothesis.strategies._internal.strategies import Ex, T, check_strategy
  from hypothesis.strategies._internal.utils import defines_strategy
label_desc: Use image node_id 11 for calling a global function with example usage: floating_dtypes() and returns: dtype_factory