Skip to content

[Benchmarks] fix: lcm benchmarking reporting #6198

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Dec 17, 2023
Merged

[Benchmarks] fix: lcm benchmarking reporting #6198

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
17e2ead
fix: lcm benchmarking reporting
sayakpaul Dec 17, 2023
6695d7a
fix generate_csv_dict call.
sayakpaul Dec 17, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
19 changes: 19 additions & 0 deletions benchmarks/base_classes.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -162,6 +162,25 @@ def run_inference(self, pipe, args):
guidance_scale=1.0,
)

def benchmark(self, args):
Copy link
Member Author

@sayakpaul sayakpaul Dec 17, 2023 •
edited
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

This ensures that the overridden get_result_filepath() in the LCMLoRATextToImageBenchmark class gets called properly.

flush()

print(f"[INFO] {self.pipe.__class__.__name__}: Running benchmark with: {vars(args)}\n")

time = benchmark_fn(self.run_inference, self.pipe, args) # in seconds.
memory = bytes_to_giga_bytes(torch.cuda.max_memory_allocated()) # in GBs.
benchmark_info = BenchmarkInfo(time=time, memory=memory)

pipeline_class_name = str(self.pipe.__class__.__name__)
flush()
csv_dict = generate_csv_dict(
pipeline_cls=pipeline_class_name, ckpt=self.lora_id, args=args, benchmark_info=benchmark_info
)
filepath = self.get_result_filepath(args)
write_to_csv(filepath, csv_dict)
print(f"Logs written to: {filepath}")
flush()


class ImageToImageBenchmark(TextToImageBenchmark):
pipeline_class = AutoPipelineForImage2Image
Expand Down