code: def get_tflops(device, num_ctas, num_warps, dtype):
      capability = torch.cuda.get_device_capability(device)
      if capability[0] < 8 and dtype == torch.float32:
          return get_simd_tflops(device, num_ctas, num_warps, dtype)
      return get_tensorcore_tflops(device, num_ctas, num_warps, dtype)
  
file_path: triton/python/triton/ops/matmul_perf_model.py
imports: import heapq
  import torch
  from ..None import cdiv
  from ..runtime import driver
  from ..testing import get_dram_gbps, get_max_simd_tflops, get_max_tensorcore_tflops, nvsmi
label_desc: Use image node_id 3 for calling a global function with example usage: get_tflops(device, num_ctas, num_warps, dtype) and returns: get_tensorcore_tflops, get_simd_tflops