Update deprecated Python 3.8 typing (#13971)
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@@ -5,7 +5,8 @@ import copy
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import itertools
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import pickle as pkl
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import time
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from typing import Callable, Iterable, List, Tuple
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from collections.abc import Iterable
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from typing import Callable
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import torch
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import torch.utils.benchmark as TBenchmark
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@@ -228,7 +229,7 @@ def print_timers(timers: Iterable[TMeasurement]):
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def run(dtype: torch.dtype,
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MKNs: Iterable[Tuple[int, int, int]]) -> Iterable[TMeasurement]:
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MKNs: Iterable[tuple[int, int, int]]) -> Iterable[TMeasurement]:
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results = []
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for m, k, n in MKNs:
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timers = bench(dtype, m, k, n, f"scaled-{dtype}-gemm",
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@@ -241,7 +242,7 @@ def run(dtype: torch.dtype,
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# output makers
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def make_output(data: Iterable[TMeasurement],
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MKNs: Iterable[Tuple[int, int, int]],
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MKNs: Iterable[tuple[int, int, int]],
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base_description: str,
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timestamp=None):
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print(f"== All Results {base_description} ====")
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@@ -282,7 +283,7 @@ def run_model_bench(args):
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for i, model in enumerate(args.models):
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print(f"[{i}] {model}")
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def model_shapes(model_name: str, tp_size: int) -> List[Tuple[int, int]]:
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def model_shapes(model_name: str, tp_size: int) -> list[tuple[int, int]]:
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KNs = []
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for KN, tp_split_dim in copy.deepcopy(WEIGHT_SHAPES[model_name]):
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KN[tp_split_dim] = KN[tp_split_dim] // tp_size
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