8b0fe06c89
Signed-off-by: luka <luka@neuralmagic.com> Signed-off-by: Luka Govedic <luka.govedic@gmail.com>
38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
from copy import deepcopy
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from typing import Callable, Union
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from torch import fx
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from vllm.compilation.inductor_pass import InductorPass
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class TestBackend:
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"""
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This class provides a simple Inductor backend that can be used for testing.
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It takes a list of custom passes and runs them after Inductor's passes.
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It also saves the graph before and after the custom passes for inspection.
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"""
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def __init__(self, *passes: Union[InductorPass, Callable[[fx.Graph],
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None]]):
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self.custom_passes = list(passes)
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from torch._inductor import config
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self.current_config = config.shallow_copy_dict()
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self.current_config['force_disable_caches'] = True
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self.current_config['post_grad_custom_post_pass'] = self.post_pass
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def __call__(self, graph: fx.GraphModule, example_inputs):
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from torch._inductor.compile_fx import compile_fx
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return compile_fx(graph,
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example_inputs,
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config_patches=self.current_config)
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def post_pass(self, graph: fx.Graph):
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self.graph_pre_pass = deepcopy(graph)
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for pass_ in self.custom_passes:
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pass_(graph)
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self.graph_post_pass = deepcopy(graph)
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# assign by reference, will reflect the final state of the graph
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self.final_graph = graph
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