mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-18 21:21:17 +00:00
67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
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import argparse
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import numpy as np
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import os
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import csv
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parser = argparse.ArgumentParser()
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parser.add_argument('--input', type=str)
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args = parser.parse_args()
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def get_gpu_lines(path):
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lines = []
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with open(path, newline='') as f:
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reader = csv.reader(f, delimiter=',')
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for row in reader:
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if row[2].find('TotalDurationNs') < 0 :
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lines.append(row)
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return lines
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activities = [
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('nccl', lambda x : x.find('nccl') >= 0),
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('gemm', lambda x : x.find('Cijk_') >= 0),
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('memcpy', lambda x : x.find('CUDA mem') >= 0),
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('adam', lambda x : x.lower().find('adam') >= 0),
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('lamb', lambda x : x.lower().find('lamb') >= 0 or x.lower().find('multi_tensor_apply') >= 0),
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('dropout', lambda x : x.lower().find('dropout') >= 0 or x.find('curand') >= 0),
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('layernorm', lambda x : x.find('LayerNorm') >= 0 or x.find('cuCompute') >= 0),
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('reduce', lambda x : x.find('reduce') >= 0),
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('softmax', lambda x : x.lower().find('softmax') >= 0),
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('transpose', lambda x : x.lower().find('transpose') >= 0),
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('element-wise', lambda x : x.lower().find('elementwise') >= 0 or x.find('DivGrad') >= 0),
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('jit', lambda x : x.startswith('kernel_')),
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('misc', lambda x : True),
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]
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def group_gpu_activity(lines):
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groups = { name : [] for name,_ in activities }
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for line in lines:
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for name, check in activities:
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if check(line[0]):
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groups[name].append(line)
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break
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return groups
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def get_seconds(time):
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return float(time.replace('us','')) / (1000.0 * 1000.0 * 1000.0)
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def gpu_percent_time(activities):
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return sum([float(a[4].replace('%','')) for a in activities])
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def gpu_absolute_time(activities):
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return sum([get_seconds(a[2]) for a in activities])
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def gpu_kernel_calls(activities):
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return sum([int(a[1]) for a in activities])
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lines = get_gpu_lines(args.input)
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groups = group_gpu_activity(lines)
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for name in groups:
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activities = groups[name]
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print('{}: N={}, calls={}, absolute={:.3f}s, percent={:.2f}%'.format(name, len(activities), gpu_kernel_calls(activities), gpu_absolute_time(activities), gpu_percent_time(activities)))
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total = [item for name in groups for item in groups[name]]
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print('Total: N={}, calls={}, absolute={:.3f}s, percent={:.2f}%'.format(len(total), gpu_kernel_calls(total), gpu_absolute_time(total), gpu_percent_time(total)))
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