deepgeek/CosyVoice
2
0
Fork 0
mirror of https://github.com/FunAudioLLM/CosyVoice.git synced 2026-02-05 18:09:24 +08:00
Code Issues Packages Projects Releases Wiki Activity

fix lint

Browse Source
This commit is contained in:
yuekaiz
2025-10-09 15:13:43 +08:00
parent 8811e9f33a
commit 33aee03ed5
14 changed files with 100 additions and 72 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
runtime/triton_trtllm/client_grpc.py
View File

@@ -122,7 +122,10 @@ def write_triton_stats(stats, summary_file):
total_input_time_s = int(model_inference_stats["compute_input"]["ns"]) / 1e9
total_output_time_s = int(model_inference_stats["compute_output"]["ns"]) / 1e9
summary_f.write(
f"queue time {total_queue_time_s:<5.2f} s, compute infer time {total_infer_time_s:<5.2f} s, compute input time {total_input_time_s:<5.2f} s, compute output time {total_output_time_s:<5.2f} s \n"
f"queue time {total_queue_time_s:<5.2f} s, "
f"compute infer time {total_infer_time_s:<5.2f} s, "
f"compute input time {total_input_time_s:<5.2f} s, "
f"compute output time {total_output_time_s:<5.2f} s \n"
)
model_batch_stats = model_state["batch_stats"]
for batch in model_batch_stats:
@@ -136,7 +139,12 @@ def write_triton_stats(stats, summary_file):
compute_input_time_ms = int(compute_input["ns"]) / 1e6
compute_output_time_ms = int(compute_output["ns"]) / 1e6
summary_f.write(
f"execuate inference with batch_size {batch_size:<2} total {batch_count:<5} times, total_infer_time {compute_infer_time_ms:<9.2f} ms, avg_infer_time {compute_infer_time_ms:<9.2f}/{batch_count:<5}={compute_infer_time_ms / batch_count:.2f} ms, avg_infer_time_per_sample {compute_infer_time_ms:<9.2f}/{batch_count:<5}/{batch_size}={compute_infer_time_ms / batch_count / batch_size:.2f} ms \n"
f"execuate inference with batch_size {batch_size:<2} total {batch_count:<5} times, "
f"total_infer_time {compute_infer_time_ms:<9.2f} ms, "
f"avg_infer_time {compute_infer_time_ms:<9.2f}/{batch_count:<5}="
f"{compute_infer_time_ms / batch_count:.2f} ms, "
f"avg_infer_time_per_sample {compute_infer_time_ms:<9.2f}/{batch_count:<5}/{batch_size}="
f"{compute_infer_time_ms / batch_count / batch_size:.2f} ms \n"
)
summary_f.write(
f"input {compute_input_time_ms:<9.2f} ms, avg {compute_input_time_ms / batch_count:.2f} ms, "