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firestar5683
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
# opt opinionatedly transforms an ast into an optimized ast using either heuristics or beam search
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from tinygrad.opt.kernel import Kernel
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from tinygrad.opt.heuristic import hand_coded_optimizations
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from tinygrad.uop.ops import UOp
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from tinygrad.helpers import NOOPT, BEAM, USE_TC, getenv
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from tinygrad.renderer import Renderer
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def get_optimized_ast(ast:UOp, renderer:Renderer) -> UOp:
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"""
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Optimize an AST based on heuristics or BEAM search.
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Args:
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ast: The Ops.SINK rooted AST
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renderer: The renderer used to generate the code
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Returns:
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The Ops.SINK rooted AST transformed to apply the opts and with a KernelInfo in the arg.
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"""
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k = Kernel(ast, opts=renderer)
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if ast.arg is not None and ast.arg.opts_to_apply is not None: k.apply_opts(ast.arg.opts_to_apply)
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elif not NOOPT:
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if not k.apply_tensor_cores(USE_TC.value): k.apply_opts(hand_coded_optimizations(k))
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if BEAM >= 1:
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from tinygrad.opt.search import beam_search, bufs_from_lin
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kb = Kernel(ast, opts=renderer)
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rawbufs = bufs_from_lin(kb, allocate=False)
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k = beam_search(kb, rawbufs, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))
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return k.get_optimized_ast()
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