From 1448e021accfdb03a381651cb5a8be6d1a6e8adf Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 19 二月 2024 14:59:26 +0800
Subject: [PATCH] aishell example
---
funasr/train_utils/trainer.py | 41 +++++++++++++++++++++++++----------------
1 files changed, 25 insertions(+), 16 deletions(-)
diff --git a/funasr/train_utils/trainer.py b/funasr/train_utils/trainer.py
index d144019..3cd61a1 100644
--- a/funasr/train_utils/trainer.py
+++ b/funasr/train_utils/trainer.py
@@ -204,25 +204,25 @@
my_context = self.model.no_sync if batch_idx % accum_grad != 0 else nullcontext
with my_context():
time2 = time.perf_counter()
- print("before, GPU, memory: {:.1} MB, "
- "{:.1} MB, "
- "{:.1} MB, "
- "{:.1} MB".format(torch.cuda.memory_allocated()/1024/1024/1024,
- torch.cuda.max_memory_allocated()/1024/1024/1024,
- torch.cuda.memory_reserved()/1024/1024/1024,
- torch.cuda.max_memory_reserved()/1024/1024/1024,
- ))
+ # print("before, GPU, memory: {:.3f} GB, "
+ # "{:.3f} GB, "
+ # "{:.3f} GB, "
+ # "{:.3f} GB".format(torch.cuda.memory_allocated()/1024/1024/1024,
+ # torch.cuda.max_memory_allocated()/1024/1024/1024,
+ # torch.cuda.memory_reserved()/1024/1024/1024,
+ # torch.cuda.max_memory_reserved()/1024/1024/1024,
+ # ))
retval = self.model(**batch)
torch.cuda.empty_cache()
- print("after, GPU, memory: {:.1} MB, "
- "{:.1} MB, "
- "{:.1} MB, "
- "{:.1} MB".format(torch.cuda.memory_allocated()/1024/1024/1024,
- torch.cuda.max_memory_allocated()/1024/1024/1024,
- torch.cuda.memory_reserved()/1024/1024/1024,
- torch.cuda.max_memory_reserved()/1024/1024/1024,
- ))
+ # print("after, GPU, memory: {:.3f} GB, "
+ # "{:.3f} GB, "
+ # "{:.3f} GB, "
+ # "{:.3f} GB".format(torch.cuda.memory_allocated()/1024/1024/1024,
+ # torch.cuda.max_memory_allocated()/1024/1024/1024,
+ # torch.cuda.memory_reserved()/1024/1024/1024,
+ # torch.cuda.max_memory_reserved()/1024/1024/1024,
+ # ))
time3 = time.perf_counter()
speed_stats["forward_time"] = f"{time3 - time2:0.3f}"
loss, stats, weight = retval
@@ -275,12 +275,21 @@
pbar.update(1)
if self.local_rank == 0:
+ gpu_info = "GPU, memory: {:.3f} GB, " \
+ "{:.3f} GB, "\
+ "{:.3f} GB, "\
+ "{:.3f} GB".format(torch.cuda.memory_allocated()/1024/1024/1024,
+ torch.cuda.max_memory_allocated()/1024/1024/1024,
+ torch.cuda.memory_reserved()/1024/1024/1024,
+ torch.cuda.max_memory_reserved()/1024/1024/1024,
+ )
description = (
f"Train epoch: {epoch}/{self.max_epoch}, "
f"step {batch_idx}/{len(self.dataloader_train)}, "
f"{speed_stats}, "
f"(loss: {loss.detach().cpu().item():.3f}), "
f"{[(k, round(v.cpu().item(), 3)) for k, v in stats.items()]}"
+ f"{gpu_info}"
)
pbar.set_description(description)
if self.writer:
--
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