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Update torchdynamo backend for torchbench #1091

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Update torchdynamo backend for torchbench #1091

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2 changes: 1 addition & 1 deletion configs/torchdynamo/nvfuser-aot-speedup.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -7,4 +7,4 @@ args:
# empty argument means the default pytorch eager mode
- ""
- "--torchdynamo nvfuser"
- "--torchdynamo aot_autograd_speedup_strategy"
- "--torchdynamo aot_nvfuser"
10 changes: 1 addition & 9 deletions torchbenchmark/util/backends/torchdynamo.py
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Expand Up @@ -5,16 +5,10 @@
import functools
from typing import List
import torchdynamo
from torchdynamo.optimizations.training import aot_autograd_speedup_strategy

EXTRA_BACKENDS = {
"aot_autograd_speedup_strategy": aot_autograd_speedup_strategy,
}

def parse_torchdynamo_args(model: 'torchbenchmark.util.model.BenchmarkModel', dyamo_args: List[str]) -> argparse.Namespace:
parser = argparse.ArgumentParser()
available_backends = torchdynamo.list_backends()
available_backends.extend(EXTRA_BACKENDS.keys())
parser.add_argument(
"--torchdynamo", choices=available_backends, help="Specify torchdynamo backends"
)
Expand All @@ -23,9 +17,7 @@ def parse_torchdynamo_args(model: 'torchbenchmark.util.model.BenchmarkModel', dy


def apply_torchdynamo_args(model: 'torchbenchmark.util.model.BenchmarkModel', args: argparse.Namespace, precision: str):
if args.torchdynamo in EXTRA_BACKENDS:
model.add_context(functools.partial(torchdynamo.optimize, EXTRA_BACKENDS[args.torchdynamo]))
elif args.torchdynamo == "fx2trt" and precision == "fp16":
if args.torchdynamo == "fx2trt" and precision == "fp16":
model.add_context(functools.partial(torchdynamo.optimize, torchdynamo.optimizations.backends.fx2trt_compiler_fp16))
else:
model.add_context(functools.partial(torchdynamo.optimize, args.torchdynamo))
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