carrot/tinygrad_repo/test/external/external_benchmark_schedule.py

from typing import List
from extra.models.resnet import ResNet50
from tinygrad import Tensor, nn
from tinygrad.helpers import Profiling, Timing, getenv, BEAM, NOOPT, DEBUG, Context, ansilen
from tinygrad.uop.ops import Ops
from tinygrad.codegen.kernel import Kernel
from tinygrad.codegen.heuristic import hand_coded_optimizations
from tinygrad.codegen import get_rewrites_for_renderer, apply_rewrites, rewrites_for_linearizer
from tinygrad.engine.search import beam_search, bufs_from_lin

if __name__ == "__main__":
  mdl = ResNet50()
  for p in nn.state.get_parameters(mdl): p.replace(Tensor.empty(p.shape))
  img = Tensor.empty(64, 3, 224, 224)

  PROFILE = getenv("PYPROFILE", 0)
  FORWARD_ONLY = getenv("FORWARD_ONLY", 0)
  SCHEDULE_ONLY = getenv("SCHEDULE_ONLY", 0)
  LINEARIZE = bool(getenv("LINEARIZE", 1))

  with Timing("all "):
    with Timing("***** model tensor in    "):
      out = mdl(img)

    if not FORWARD_ONLY:
      with Timing("***** model schedule in  "):
        with Profiling(PROFILE >= 3):
          sched = out.schedule()

      if not SCHEDULE_ONLY:
        asts = list({x.ast.key:x.ast for x in sched if x.ast.op is Ops.SINK}.values())
        if (restrict_kernel := getenv("RESTRICT_KERNEL", -1)) != -1: asts = asts[restrict_kernel:restrict_kernel+1]
        kernels: List[Kernel] = []
        with Timing(f"***** model opts({len(asts):2d}) in  "):
          with Profiling(PROFILE >= 3):
            for ast in asts:
              k = Kernel(ast)
              if BEAM:
                with Context(DEBUG=max(2, DEBUG.value)): k = beam_search(k, bufs_from_lin(k), BEAM.value)
              elif NOOPT: pass
              else: k.apply_opts(hand_coded_optimizations(k))
              kernels.append(k)

        with Timing("***** model prep in      "):
          kernels = [(k, k.get_optimized_ast(), get_rewrites_for_renderer(k.opts, linearizer=False)) for k in kernels]

        with Profiling(PROFILE, fn="/tmp/rewrite.prof"):
          with Timing("***** model rewrite in   "):
            rewritten_uops = []
            for i,(k,u,rewrites) in enumerate(kernels):
              with Timing(f"rewrite {i:2d} {k.name}{' '*(50-ansilen(k.name))}", enabled=getenv("VERBOSE", 0)):
                rewritten_uops.append(apply_rewrites(u, rewrites))

        if LINEARIZE:
          with Timing("***** model linearize in "):
            uops_line = []
            for u in rewritten_uops:
              uops_line.append(apply_rewrites(u, rewrites_for_linearizer))
          print(sum(len(u.arg.lst) for u in uops_line))