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54 lines
2.3 KiB
Python
54 lines
2.3 KiB
Python
from typing import List
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from extra.models.resnet import ResNet50
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from tinygrad import Tensor, nn
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from tinygrad.helpers import Profiling, Timing, getenv, BEAM, NOOPT, DEBUG, Context, ansilen
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from tinygrad.uop.ops import Ops
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from tinygrad.codegen.kernel import Kernel
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from tinygrad.codegen.heuristic import hand_coded_optimizations
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from tinygrad.codegen import get_rewrites_for_renderer, apply_rewrites
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from tinygrad.engine.search import beam_search, bufs_from_lin
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if __name__ == "__main__":
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mdl = ResNet50()
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for p in nn.state.get_parameters(mdl): p.replace(Tensor.empty(p.shape))
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img = Tensor.empty(64, 3, 224, 224)
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PROFILE = getenv("PYPROFILE", 0)
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FORWARD_ONLY = getenv("FORWARD_ONLY", 0)
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SCHEDULE_ONLY = getenv("SCHEDULE_ONLY", 0)
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LINEARIZE = bool(getenv("LINEARIZE", 1))
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with Timing("all "):
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with Timing("***** model tensor in "):
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out = mdl(img)
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if not FORWARD_ONLY:
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with Timing("***** model schedule in "):
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sched = out.schedule()
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if not SCHEDULE_ONLY:
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asts = list({x.ast.key:x.ast for x in sched if x.ast.op is Ops.SINK}.values())
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if (restrict_kernel := getenv("RESTRICT_KERNEL", -1)) != -1: asts = asts[restrict_kernel:restrict_kernel+1]
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kernels: List[Kernel] = []
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with Timing(f"***** model opts({len(asts):2d}) in "):
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with Profiling(PROFILE >= 3):
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for ast in asts:
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k = Kernel(ast)
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if BEAM:
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with Context(DEBUG=max(2, DEBUG.value)): k = beam_search(k, bufs_from_lin(k), BEAM.value)
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elif NOOPT: pass
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else: k.apply_opts(hand_coded_optimizations(k))
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kernels.append(k)
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with Timing("***** model prep in "):
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kernels = [(k, k.get_optimized_ast(), get_rewrites_for_renderer(k.opts, linearizer=LINEARIZE)) for k in kernels]
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with Profiling(PROFILE, fn="/tmp/rewrite.prof"):
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with Timing("***** model rewrite in "):
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rewritten_uops = []
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for i,(k,u,rewrites) in enumerate(kernels):
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with Timing(f"rewrite {i:2d} {k.name}{' '*(50-ansilen(k.name))}", enabled=getenv("VERBOSE", 0)):
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rewritten_uops.append(apply_rewrites(u, rewrites))
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uops = rewritten_uops
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if LINEARIZE: print(sum(len(u.arg.lst) for u in uops))
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