code: def test_typeconvert_downcast(
      src_dtype, dst_dtype, rounding, max_repr
  ):
      if src_dtype != "float32" and torch.cuda.get_device_capability(
          0
      ) < (9, 0):
          pytest.skip(
              "non-float32 downcast tests only supported on compute capability 9.0+"
          )
  
      if (
          dst_dtype.startswith("float8")
          and rounding == "rtne"
          and torch.cuda.get_device_capability(0) < (9, 0)
      ):
          pytest.skip(
              "float8 downcast with RTNE rounding tests only supported on compute capability 9.0+"
          )
  
      # dtype : (exponent_bits, mantissa_bits, exponent_bias)
      stuff = {
          "float16": (5, 10, 15),
          "bfloat16": (8, 7, 127),
          "float8e5": (5, 2, 15),
          "float8e4b15": (4, 3, 15),
          "float8e4nv": (4, 3, 7),
      }[dst_dtype]
  
      for i in range(256):
          downcast_test(
              getattr(tl, src_dtype),
              getattr(tl, dst_dtype),
              rounding,
              *stuff,
              max_repr,
              i,
          )
  
file_path: triton/python/test/unit/language/test_conversions.py
imports: import numpy
  import torch
  import pytest
  import triton
  import triton.language
label_desc: Use image node_id 14 for calling a global function with example usage: test_typeconvert_downcast(src_dtype, dst_dtype, rounding, max_repr) without return types