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3b54592050
To be used to evaluate performance of following improvements. Baseline numbers: https://gist.github.com/swolchok/c8bcb92be1dc6e67c4f7efad498becd5 Differential Revision: [D43919653](https://our.internmc.facebook.com/intern/diff/D43919653/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D43919653/)! Pull Request resolved: https://github.com/pytorch/pytorch/pull/96496 Approved by: https://github.com/Skylion007
24 lines
843 B
Python
24 lines
843 B
Python
import torch
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import torch.utils.benchmark as benchmark
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MEMO = {}
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def create_nested_dict_type(layers):
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if layers == 0:
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return torch._C.StringType.get()
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if layers not in MEMO:
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less_nested = create_nested_dict_type(layers - 1)
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result = torch._C.DictType(torch._C.StringType.get(), torch._C.TupleType([less_nested, less_nested]))
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MEMO[layers] = result
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return MEMO[layers]
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nesting_levels = (1, 3, 5, 10)
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types = (reasonable, medium, big, huge) = [create_nested_dict_type(x) for x in nesting_levels]
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timers = [benchmark.Timer(stmt='x.annotation_str', globals={'x': nested_type}) for nested_type in types]
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for nesting_level, typ, timer in zip(nesting_levels, types, timers):
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print("Nesting level:", nesting_level)
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print("output:", typ.annotation_str[:70])
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print(timer.blocked_autorange())
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