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"""
helper function to benchmark eager pytorch
"""
# pylint: disable=C0415
[docs]def benchmark_torch_function(iters: int, function, *args, **kwargs) -> float:
"""
function for benchmarking a pytorch function.
Parameters
----------
iters: int
Number of iterations.
function: lambda function
function to benchmark.
args: Any type
Args to function.
Returns
-------
float
Runtime per iteration in ms.
"""
import torch
# Warm up
for _ in range(5):
function(*args, **kwargs)
# Start benchmark.
torch.cuda.synchronize()
start_event = torch.cuda.Event(enable_timing=True)
end_event = torch.cuda.Event(enable_timing=True)
start_event.record()
for _ in range(iters):
function(*args, **kwargs)
end_event.record()
torch.cuda.synchronize()
# in ms
return (start_event.elapsed_time(end_event)) / iters