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import os | ||
import zipfile | ||
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MAX_SIZE_MB = 100 | ||
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def print_top_10_largest_files(zip_file): | ||
with zipfile.ZipFile(zip_file, 'r') as z: | ||
file_sizes = [(f, z.getinfo(f).file_size) for f in z.namelist()] | ||
file_sizes.sort(key=lambda x: x[1], reverse=True) | ||
for f, size in file_sizes[:10]: | ||
print(f"{f}: {size/(1024*1024)} MBs uncompressed.") | ||
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def check_wheel_size(directory): | ||
for root, _, files in os.walk(directory): | ||
for f in files: | ||
if f.endswith(".whl"): | ||
wheel_path = os.path.join(root, f) | ||
wheel_size = os.path.getsize(wheel_path) | ||
wheel_size_mb = wheel_size / (1024 * 1024) | ||
if wheel_size_mb > MAX_SIZE_MB: | ||
print( | ||
f"Wheel {wheel_path} is too large ({wheel_size_mb} MB) " | ||
f"compare to the allowed size ({MAX_SIZE_MB} MB).") | ||
print_top_10_largest_files(wheel_path) | ||
return 1 | ||
else: | ||
print(f"Wheel {wheel_path} is within the allowed size " | ||
f"({wheel_size_mb} MB).") | ||
return 0 | ||
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if __name__ == "__main__": | ||
import sys | ||
sys.exit(check_wheel_size(sys.argv[1])) |
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name: 💬 Request for comments (RFC). | ||
description: Ask for feedback on major architectural changes or design choices. | ||
title: "[RFC]: " | ||
labels: ["RFC"] | ||
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body: | ||
- type: markdown | ||
attributes: | ||
value: > | ||
#### Please take a look at previous [RFCs](https://github.com/vllm-project/vllm/issues?q=label%3ARFC+sort%3Aupdated-desc) for reference. | ||
- type: textarea | ||
attributes: | ||
label: Motivation. | ||
description: > | ||
The motivation of the RFC. | ||
validations: | ||
required: true | ||
- type: textarea | ||
attributes: | ||
label: Proposed Change. | ||
description: > | ||
The proposed change of the RFC. | ||
validations: | ||
required: true | ||
- type: textarea | ||
attributes: | ||
label: Feedback Period. | ||
description: > | ||
The feedback period of the RFC. Usually at least one week. | ||
validations: | ||
required: false | ||
- type: textarea | ||
attributes: | ||
label: CC List. | ||
description: > | ||
The list of people you want to CC. | ||
validations: | ||
required: false | ||
- type: textarea | ||
attributes: | ||
label: Any Other Things. | ||
description: > | ||
Any other things you would like to mention. | ||
validations: | ||
required: false | ||
- type: markdown | ||
attributes: | ||
value: > | ||
Thanks for contributing 🎉! |
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Original file line number | Diff line number | Diff line change |
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neuralmagic/benchmarks/configs/benchmark_serving.json | ||
neuralmagic/benchmarks/configs/benchmark_throughput.json | ||
neuralmagic/benchmarks/configs/benchmark_throughput_decode.json | ||
neuralmagic/benchmarks/configs/benchmark_throughput_prefill.json | ||
neuralmagic/benchmarks/configs/benchmark_remote_push.json |
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bigger_is_better
{"name": "request_throughput", "description": "VLLM Engine throughput - synthetic\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 1", "vllm_version": "0.2.0", "python_version": "3.10.12 (main, May 10 2024, 13:42:25) [GCC 9.4.0]", "torch_version": "2.3.0+cu121"}
3.8388254207613244
prompts/s3.8408865302828166
prompts/s1.00
{"name": "token_throughput", "description": "VLLM Engine throughput - synthetic\nmodel - NousResearch/Llama-2-7b-chat-hf\nmax_model_len - 4096\nbenchmark_throughput {\n \"use-all-available-gpus_\": \"\",\n \"input-len\": 256,\n \"output-len\": 128,\n \"num-prompts\": 1000\n}", "gpu_description": "NVIDIA A10G x 1", "vllm_version": "0.2.0", "python_version": "3.10.12 (main, May 10 2024, 13:42:25) [GCC 9.4.0]", "torch_version": "2.3.0+cu121"}
1474.1089615723486
tokens/s1474.9004276286016
tokens/s1.00
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