syxin_old/train_run.log

nohup: ignoring input

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Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
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Set TORCH_CUDA_ARCH_LIST to 9.0
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
Set TORCH_CUDA_ARCH_LIST to 9.0
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
Set TORCH_CUDA_ARCH_LIST to 9.0
Set TORCH_CUDA_ARCH_LIST to 9.0
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
Set TORCH_CUDA_ARCH_LIST to 9.0
Set TORCH_CUDA_ARCH_LIST to 9.0
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
Set TORCH_CUDA_ARCH_LIST to 9.0
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
Set TORCH_CUDA_ARCH_LIST to 9.0
/workspace/hanrui/syxin_old/Specforge/specforge/modeling/draft/llama3_eagle.py:29: UserWarning: flash_attn is not found, falling back to flex_attention. Please install flash_attn if you want to use the flash attention backend.
  warnings.warn(
`torch_dtype` is deprecated! Use `dtype` instead!
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]`torch_dtype` is deprecated! Use `dtype` instead!
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]`torch_dtype` is deprecated! Use `dtype` instead!
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
`torch_dtype` is deprecated! Use `dtype` instead!
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
The following generation flags are not valid and may be ignored: ['output_hidden_states']. Set `TRANSFORMERS_VERBOSITY=info` for more details.

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trainable params: 30,670,848 || all params: 8,221,406,208 || trainable%: 0.3731

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trainable params: 30,670,848 || all params: 8,221,406,208 || trainable%: 0.3731
trainable params: 30,670,848 || all params: 8,221,406,208 || trainable%: 0.3731
trainable params: 30,670,848 || all params: 8,221,406,208 || trainable%: 0.3731

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dataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkl

Map (num_proc=16):   0%|          | 0/818627 [00:00<?, ? examples/s]/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(
/workspace/hanrui/syxin_old/Specforge/specforge/data/parse.py:84: UserWarning: The first message is from system, we will use the system prompt from the data and ignore the system prompt from the template
  warnings.warn(

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/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/distributed_c10d.py:4876: UserWarning: barrier(): using the device under current context. You can specify `device_id` in `init_process_group` to mute this warning.
  warnings.warn(  # warn only once
[rank0]:[W323 13:02:24.876799111 ProcessGroupNCCL.cpp:5072] Guessing device ID based on global rank. This can cause a hang if rank to GPU mapping is heterogeneous. You can specify device_id in init_process_group()

Filter:   0%|          | 0/818627 [00:00<?, ? examples/s]dataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkldataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkl

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dataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkldataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkl

dataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkl
dataset is cached at /tmp/specforge_cache/processed_dataset/b2b7bdc9eb8a4170c0d33f03d2bf640b.pkl

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Epoch 0:   0%|          | 19/12384 [02:25<24:58:58,  7.27s/it, loss=25.3883, acc=0.0011, iter_time=8.41s]
Epoch 0:   0%|          | 20/12384 [02:25<24:57:11,  7.27s/it, loss=25.3883, acc=0.0011, iter_time=8.41s]
Epoch 0:   0%|          | 20/12384 [02:33<24:57:11,  7.27s/it, loss=25.3092, acc=0.0002, iter_time=7.33s]
Epoch 0:   0%|          | 21/12384 [02:33<25:19:33,  7.37s/it, loss=25.3092, acc=0.0002, iter_time=7.33s]
Epoch 0:   0%|          | 21/12384 [02:40<25:19:33,  7.37s/it, loss=25.6943, acc=0.0011, iter_time=7.56s]
Epoch 0:   0%|          | 22/12384 [02:40<25:11:45,  7.34s/it, loss=25.6943, acc=0.0011, iter_time=7.56s]
Epoch 0:   0%|          | 22/12384 [02:47<25:11:45,  7.34s/it, loss=26.9137, acc=0.0004, iter_time=7.25s]
Epoch 0:   0%|          | 23/12384 [02:47<25:06:06,  7.31s/it, loss=26.9137, acc=0.0004, iter_time=7.25s]
Epoch 0:   0%|          | 23/12384 [02:55<25:06:06,  7.31s/it, loss=25.6135, acc=0.0014, iter_time=7.64s]
Epoch 0:   0%|          | 24/12384 [02:55<25:02:34,  7.29s/it, loss=25.6135, acc=0.0014, iter_time=7.64s]
Epoch 0:   0%|          | 24/12384 [03:02<25:02:34,  7.29s/it, loss=26.1792, acc=0.0009, iter_time=6.87s]
Epoch 0:   0%|          | 25/12384 [03:02<25:01:00,  7.29s/it, loss=26.1792, acc=0.0009, iter_time=6.87s]
Epoch 0:   0%|          | 25/12384 [03:09<25:01:00,  7.29s/it, loss=25.4236, acc=0.0010, iter_time=7.25s]
Epoch 0:   0%|          | 26/12384 [03:09<24:59:08,  7.28s/it, loss=25.4236, acc=0.0010, iter_time=7.25s]
Epoch 0:   0%|          | 26/12384 [03:16<24:59:08,  7.28s/it, loss=25.8779, acc=0.0008, iter_time=7.27s]
Epoch 0:   0%|          | 27/12384 [03:16<24:57:22,  7.27s/it, loss=25.8779, acc=0.0008, iter_time=7.27s]
Epoch 0:   0%|          | 27/12384 [03:24<24:57:22,  7.27s/it, loss=25.2761, acc=0.0002, iter_time=4.21s]
Epoch 0:   0%|          | 28/12384 [03:24<24:55:54,  7.26s/it, loss=25.2761, acc=0.0002, iter_time=4.21s]
Epoch 0:   0%|          | 28/12384 [03:31<24:55:54,  7.26s/it, loss=24.7261, acc=0.0006, iter_time=10.28s]
Epoch 0:   0%|          | 29/12384 [03:31<24:55:29,  7.26s/it, loss=24.7261, acc=0.0006, iter_time=10.28s]
Epoch 0:   0%|          | 29/12384 [03:38<24:55:29,  7.26s/it, loss=26.0604, acc=0.0012, iter_time=6.71s] 
Epoch 0:   0%|          | 30/12384 [03:38<24:53:52,  7.26s/it, loss=26.0604, acc=0.0012, iter_time=6.71s]
Epoch 0:   0%|          | 30/12384 [03:45<24:53:52,  7.26s/it, loss=25.6512, acc=0.0013, iter_time=7.79s]
Epoch 0:   0%|          | 31/12384 [03:45<24:53:34,  7.25s/it, loss=25.6512, acc=0.0013, iter_time=7.79s]
Epoch 0:   0%|          | 31/12384 [03:53<24:53:34,  7.25s/it, loss=25.4752, acc=0.0010, iter_time=7.65s]
Epoch 0:   0%|          | 32/12384 [03:53<24:53:27,  7.25s/it, loss=25.4752, acc=0.0010, iter_time=7.65s]
Epoch 0:   0%|          | 32/12384 [04:00<24:53:27,  7.25s/it, loss=26.0732, acc=0.0004, iter_time=6.86s]
Epoch 0:   0%|          | 33/12384 [04:00<24:53:16,  7.25s/it, loss=26.0732, acc=0.0004, iter_time=6.86s]
Epoch 0:   0%|          | 33/12384 [04:07<24:53:16,  7.25s/it, loss=26.2147, acc=0.0006, iter_time=7.27s]
Epoch 0:   0%|          | 34/12384 [04:07<24:53:29,  7.26s/it, loss=26.2147, acc=0.0006, iter_time=7.27s]
Epoch 0:   0%|          | 34/12384 [04:14<24:53:29,  7.26s/it, loss=25.3158, acc=0.0018, iter_time=5.68s]
Epoch 0:   0%|          | 35/12384 [04:14<24:51:20,  7.25s/it, loss=25.3158, acc=0.0018, iter_time=5.68s]
Epoch 0:   0%|          | 35/12384 [04:22<24:51:20,  7.25s/it, loss=25.3095, acc=0.0006, iter_time=8.80s]
Epoch 0:   0%|          | 36/12384 [04:22<24:52:17,  7.25s/it, loss=25.3095, acc=0.0006, iter_time=8.80s]
Epoch 0:   0%|          | 36/12384 [04:29<24:52:17,  7.25s/it, loss=26.7242, acc=0.0006, iter_time=7.26s]
Epoch 0:   0%|          | 37/12384 [04:29<24:52:10,  7.25s/it, loss=26.7242, acc=0.0006, iter_time=7.26s]
Epoch 0:   0%|          | 37/12384 [04:36<24:52:10,  7.25s/it, loss=24.7830, acc=0.0007, iter_time=3.49s]
Epoch 0:   0%|          | 38/12384 [04:36<24:52:14,  7.25s/it, loss=24.7830, acc=0.0007, iter_time=3.49s]
Epoch 0:   0%|          | 38/12384 [04:43<24:52:14,  7.25s/it, loss=26.1911, acc=0.0006, iter_time=11.00s]
Epoch 0:   0%|          | 39/12384 [04:43<24:51:17,  7.25s/it, loss=26.1911, acc=0.0006, iter_time=11.00s]
Epoch 0:   0%|          | 39/12384 [04:51<24:51:17,  7.25s/it, loss=26.6228, acc=0.0004, iter_time=7.63s] 
Epoch 0:   0%|          | 40/12384 [04:51<24:50:52,  7.25s/it, loss=26.6228, acc=0.0004, iter_time=7.63s]
Epoch 0:   0%|          | 40/12384 [04:58<24:50:52,  7.25s/it, loss=26.3213, acc=0.0003, iter_time=6.85s]
Epoch 0:   0%|          | 41/12384 [04:58<24:50:44,  7.25s/it, loss=26.3213, acc=0.0003, iter_time=6.85s]
Epoch 0:   0%|          | 41/12384 [05:05<24:50:44,  7.25s/it, loss=25.6779, acc=0.0007, iter_time=7.24s]
Epoch 0:   0%|          | 42/12384 [05:05<24:50:51,  7.25s/it, loss=25.6779, acc=0.0007, iter_time=7.24s]
Epoch 0:   0%|          | 42/12384 [05:12<24:50:51,  7.25s/it, loss=25.1938, acc=0.0003, iter_time=6.75s]
Epoch 0:   0%|          | 43/12384 [05:12<24:50:51,  7.25s/it, loss=25.1938, acc=0.0003, iter_time=6.75s]
Epoch 0:   0%|          | 43/12384 [05:20<24:50:51,  7.25s/it, loss=26.5261, acc=0.0019, iter_time=7.76s]
Epoch 0:   0%|          | 44/12384 [05:20<24:50:08,  7.25s/it, loss=26.5261, acc=0.0019, iter_time=7.76s]
Epoch 0:   0%|          | 44/12384 [05:27<24:50:08,  7.25s/it, loss=24.9753, acc=0.0005, iter_time=7.24s]
Epoch 0:   0%|          | 45/12384 [05:27<24:49:44,  7.24s/it, loss=24.9753, acc=0.0005, iter_time=7.24s]
Epoch 0:   0%|          | 45/12384 [05:34<24:49:44,  7.24s/it, loss=25.4438, acc=0.0005, iter_time=4.87s]
Epoch 0:   0%|          | 46/12384 [05:34<24:46:59,  7.23s/it, loss=25.4438, acc=0.0005, iter_time=4.87s]
Epoch 0:   0%|          | 46/12384 [05:41<24:46:59,  7.23s/it, loss=24.4372, acc=0.0011, iter_time=9.57s]
Epoch 0:   0%|          | 47/12384 [05:41<24:47:22,  7.23s/it, loss=24.4372, acc=0.0011, iter_time=9.57s]
Epoch 0:   0%|          | 47/12384 [05:49<24:47:22,  7.23s/it, loss=24.4923, acc=0.0013, iter_time=7.65s]
Epoch 0:   0%|          | 48/12384 [05:49<24:48:55,  7.24s/it, loss=24.4923, acc=0.0013, iter_time=7.65s]
Epoch 0:   0%|          | 48/12384 [05:56<24:48:55,  7.24s/it, loss=25.7376, acc=0.0007, iter_time=5.25s]
Epoch 0:   0%|          | 49/12384 [05:56<24:53:36,  7.27s/it, loss=25.7376, acc=0.0007, iter_time=5.25s]
Epoch 0:   0%|          | 49/12384 [06:03<24:53:36,  7.27s/it, loss=25.5508, acc=0.0010, iter_time=9.31s]
Epoch 0:   0%|          | 50/12384 [06:03<24:51:52,  7.26s/it, loss=25.5508, acc=0.0010, iter_time=9.31s]
Epoch 0:   0%|          | 50/12384 [06:10<24:51:52,  7.26s/it, loss=24.6517, acc=0.0011, iter_time=4.49s]
Epoch 0:   0%|          | 51/12384 [06:10<24:50:53,  7.25s/it, loss=24.6517, acc=0.0011, iter_time=4.49s]
Epoch 0:   0%|          | 51/12384 [06:18<24:50:53,  7.25s/it, loss=26.7249, acc=0.0002, iter_time=9.02s]
Epoch 0:   0%|          | 52/12384 [06:18<24:48:17,  7.24s/it, loss=26.7249, acc=0.0002, iter_time=9.02s]
Epoch 0:   0%|          | 52/12384 [06:25<24:48:17,  7.24s/it, loss=25.1032, acc=0.0008, iter_time=7.81s]
Epoch 0:   0%|          | 53/12384 [06:25<24:49:07,  7.25s/it, loss=25.1032, acc=0.0008, iter_time=7.81s]
Epoch 0:   0%|          | 53/12384 [06:32<24:49:07,  7.25s/it, loss=25.9677, acc=0.0010, iter_time=4.72s]
Epoch 0:   0%|          | 54/12384 [06:32<24:49:54,  7.25s/it, loss=25.9677, acc=0.0010, iter_time=4.72s]
Epoch 0:   0%|          | 54/12384 [06:39<24:49:54,  7.25s/it, loss=24.8746, acc=0.0004, iter_time=9.83s]
Epoch 0:   0%|          | 55/12384 [06:39<24:52:17,  7.26s/it, loss=24.8746, acc=0.0004, iter_time=9.83s]
Epoch 0:   0%|          | 55/12384 [06:47<24:52:17,  7.26s/it, loss=25.2453, acc=0.0004, iter_time=7.64s]
Epoch 0:   0%|          | 56/12384 [06:47<24:51:22,  7.26s/it, loss=25.2453, acc=0.0004, iter_time=7.64s]
Epoch 0:   0%|          | 56/12384 [06:54<24:51:22,  7.26s/it, loss=24.1171, acc=0.0013, iter_time=6.07s]
Epoch 0:   0%|          | 57/12384 [06:54<24:46:43,  7.24s/it, loss=24.1171, acc=0.0013, iter_time=6.07s]
Epoch 0:   0%|          | 57/12384 [07:01<24:46:43,  7.24s/it, loss=25.7877, acc=0.0010, iter_time=4.90s]
Epoch 0:   0%|          | 58/12384 [07:01<24:47:18,  7.24s/it, loss=25.7877, acc=0.0010, iter_time=4.90s]
Epoch 0:   0%|          | 58/12384 [07:08<24:47:18,  7.24s/it, loss=24.9161, acc=0.0011, iter_time=10.32s]
Epoch 0:   0%|          | 59/12384 [07:08<24:47:08,  7.24s/it, loss=24.9161, acc=0.0011, iter_time=10.32s]
Epoch 0:   0%|          | 59/12384 [07:16<24:47:08,  7.24s/it, loss=24.8615, acc=0.0005, iter_time=7.25s] 
Epoch 0:   0%|          | 60/12384 [07:16<24:47:53,  7.24s/it, loss=24.8615, acc=0.0005, iter_time=7.25s]
Epoch 0:   0%|          | 60/12384 [07:23<24:47:53,  7.24s/it, loss=25.7963, acc=0.0004, iter_time=6.39s]
Epoch 0:   0%|          | 61/12384 [07:23<24:47:46,  7.24s/it, loss=25.7963, acc=0.0004, iter_time=6.39s]
Epoch 0:   0%|          | 61/12384 [07:30<24:47:46,  7.24s/it, loss=25.4569, acc=0.0008, iter_time=6.48s]
Epoch 0:   1%|          | 62/12384 [07:30<24:47:13,  7.24s/it, loss=25.4569, acc=0.0008, iter_time=6.48s]
Epoch 0:   1%|          | 62/12384 [07:37<24:47:13,  7.24s/it, loss=23.8285, acc=0.0003, iter_time=8.86s]
Epoch 0:   1%|          | 63/12384 [07:37<24:47:50,  7.25s/it, loss=23.8285, acc=0.0003, iter_time=8.86s]
Epoch 0:   1%|          | 63/12384 [07:45<24:47:50,  7.25s/it, loss=24.9708, acc=0.0014, iter_time=7.34s]
Epoch 0:   1%|          | 64/12384 [07:45<24:46:58,  7.24s/it, loss=24.9708, acc=0.0014, iter_time=7.34s]
Epoch 0:   1%|          | 64/12384 [07:52<24:46:58,  7.24s/it, loss=26.5769, acc=0.0011, iter_time=6.65s]
Epoch 0:   1%|          | 65/12384 [07:52<24:46:22,  7.24s/it, loss=26.5769, acc=0.0011, iter_time=6.65s]
Epoch 0:   1%|          | 65/12384 [07:59<24:46:22,  7.24s/it, loss=26.3202, acc=0.0011, iter_time=7.73s]
Epoch 0:   1%|          | 66/12384 [07:59<24:46:34,  7.24s/it, loss=26.3202, acc=0.0011, iter_time=7.73s]
Epoch 0:   1%|          | 66/12384 [08:06<24:46:34,  7.24s/it, loss=26.4568, acc=0.0007, iter_time=7.25s]
Epoch 0:   1%|          | 67/12384 [08:06<24:47:17,  7.25s/it, loss=26.4568, acc=0.0007, iter_time=7.25s]
Epoch 0:   1%|          | 67/12384 [08:14<24:47:17,  7.25s/it, loss=24.0713, acc=0.0008, iter_time=7.25s]
Epoch 0:   1%|          | 68/12384 [08:14<24:47:27,  7.25s/it, loss=24.0713, acc=0.0008, iter_time=7.25s]
Epoch 0:   1%|          | 68/12384 [08:21<24:47:27,  7.25s/it, loss=26.1297, acc=0.0008, iter_time=6.17s]
Epoch 0:   1%|          | 69/12384 [08:21<24:46:04,  7.24s/it, loss=26.1297, acc=0.0008, iter_time=6.17s]
Epoch 0:   1%|          | 69/12384 [08:28<24:46:04,  7.24s/it, loss=25.1814, acc=0.0004, iter_time=8.30s]
Epoch 0:   1%|          | 70/12384 [08:28<24:46:18,  7.24s/it, loss=25.1814, acc=0.0004, iter_time=8.30s]
Epoch 0:   1%|          | 70/12384 [08:35<24:46:18,  7.24s/it, loss=25.3554, acc=0.0012, iter_time=7.24s]
Epoch 0:   1%|          | 71/12384 [08:35<24:46:09,  7.24s/it, loss=25.3554, acc=0.0012, iter_time=7.24s]
Epoch 0:   1%|          | 71/12384 [08:43<24:46:09,  7.24s/it, loss=26.4846, acc=0.0008, iter_time=7.64s]
Epoch 0:   1%|          | 72/12384 [08:43<24:46:47,  7.25s/it, loss=26.4846, acc=0.0008, iter_time=7.64s]
Epoch 0:   1%|          | 72/12384 [08:50<24:46:47,  7.25s/it, loss=25.3087, acc=0.0013, iter_time=4.99s]
Epoch 0:   1%|          | 73/12384 [08:50<24:48:08,  7.25s/it, loss=25.3087, acc=0.0013, iter_time=4.99s]
Epoch 0:   1%|          | 73/12384 [08:57<24:48:08,  7.25s/it, loss=25.8696, acc=0.0007, iter_time=9.14s]
Epoch 0:   1%|          | 74/12384 [08:57<24:47:27,  7.25s/it, loss=25.8696, acc=0.0007, iter_time=9.14s]
Epoch 0:   1%|          | 74/12384 [09:04<24:47:27,  7.25s/it, loss=25.4730, acc=0.0010, iter_time=7.26s]
Epoch 0:   1%|          | 75/12384 [09:04<24:47:57,  7.25s/it, loss=25.4730, acc=0.0010, iter_time=7.26s]
Epoch 0:   1%|          | 75/12384 [09:12<24:47:57,  7.25s/it, loss=25.9954, acc=0.0000, iter_time=6.67s]
Epoch 0:   1%|          | 76/12384 [09:12<24:46:05,  7.24s/it, loss=25.9954, acc=0.0000, iter_time=6.67s]
Epoch 0:   1%|          | 76/12384 [09:19<24:46:05,  7.24s/it, loss=25.1234, acc=0.0011, iter_time=6.97s]
Epoch 0:   1%|          | 77/12384 [09:19<24:47:05,  7.25s/it, loss=25.1234, acc=0.0011, iter_time=6.97s]
Epoch 0:   1%|          | 77/12384 [09:26<24:47:05,  7.25s/it, loss=24.7491, acc=0.0007, iter_time=8.08s]
Epoch 0:   1%|          | 78/12384 [09:26<24:45:33,  7.24s/it, loss=24.7491, acc=0.0007, iter_time=8.08s]
Epoch 0:   1%|          | 78/12384 [09:33<24:45:33,  7.24s/it, loss=25.9329, acc=0.0006, iter_time=7.24s]
Epoch 0:   1%|          | 79/12384 [09:33<24:45:19,  7.24s/it, loss=25.9329, acc=0.0006, iter_time=7.24s]
Epoch 0:   1%|          | 79/12384 [09:41<24:45:19,  7.24s/it, loss=24.6874, acc=0.0018, iter_time=7.10s]
Epoch 0:   1%|          | 80/12384 [09:41<24:44:59,  7.24s/it, loss=24.6874, acc=0.0018, iter_time=7.10s]
Epoch 0:   1%|          | 80/12384 [09:48<24:44:59,  7.24s/it, loss=25.7239, acc=0.0006, iter_time=4.80s]
Epoch 0:   1%|          | 81/12384 [09:48<24:45:03,  7.24s/it, loss=25.7239, acc=0.0006, iter_time=4.80s]
Epoch 0:   1%|          | 81/12384 [09:55<24:45:03,  7.24s/it, loss=25.8323, acc=0.0006, iter_time=9.80s]
Epoch 0:   1%|          | 82/12384 [09:55<24:45:41,  7.25s/it, loss=25.8323, acc=0.0006, iter_time=9.80s]
Epoch 0:   1%|          | 82/12384 [10:02<24:45:41,  7.25s/it, loss=24.6073, acc=0.0011, iter_time=7.29s]
Epoch 0:   1%|          | 83/12384 [10:02<24:46:03,  7.25s/it, loss=24.6073, acc=0.0011, iter_time=7.29s]
Epoch 0:   1%|          | 83/12384 [10:09<24:46:03,  7.25s/it, loss=25.9912, acc=0.0005, iter_time=6.97s]
Epoch 0:   1%|          | 84/12384 [10:09<24:44:38,  7.24s/it, loss=25.9912, acc=0.0005, iter_time=6.97s]
Epoch 0:   1%|          | 84/12384 [10:17<24:44:38,  7.24s/it, loss=25.8104, acc=0.0005, iter_time=7.49s]
Epoch 0:   1%|          | 85/12384 [10:17<24:43:46,  7.24s/it, loss=25.8104, acc=0.0005, iter_time=7.49s]
Epoch 0:   1%|          | 85/12384 [10:24<24:43:46,  7.24s/it, loss=25.5907, acc=0.0000, iter_time=7.23s]
Epoch 0:   1%|          | 86/12384 [10:24<24:43:26,  7.24s/it, loss=25.5907, acc=0.0000, iter_time=7.23s]
Epoch 0:   1%|          | 86/12384 [10:31<24:43:26,  7.24s/it, loss=26.5948, acc=0.0009, iter_time=7.24s]
Epoch 0:   1%|          | 87/12384 [10:31<24:47:26,  7.26s/it, loss=26.5948, acc=0.0009, iter_time=7.24s]
Epoch 0:   1%|          | 87/12384 [10:39<24:47:26,  7.26s/it, loss=25.5724, acc=0.0004, iter_time=7.70s]
Epoch 0:   1%|          | 88/12384 [10:39<24:47:41,  7.26s/it, loss=25.5724, acc=0.0004, iter_time=7.70s]
Epoch 0:   1%|          | 88/12384 [10:46<24:47:41,  7.26s/it, loss=24.6367, acc=0.0009, iter_time=5.27s]
Epoch 0:   1%|          | 89/12384 [10:46<24:47:03,  7.26s/it, loss=24.6367, acc=0.0009, iter_time=5.27s]
Epoch 0:   1%|          | 89/12384 [10:53<24:47:03,  7.26s/it, loss=24.2505, acc=0.0012, iter_time=8.85s]
Epoch 0:   1%|          | 90/12384 [10:53<24:45:40,  7.25s/it, loss=24.2505, acc=0.0012, iter_time=8.85s]
Epoch 0:   1%|          | 90/12384 [11:00<24:45:40,  7.25s/it, loss=26.7861, acc=0.0012, iter_time=7.27s]
Epoch 0:   1%|          | 91/12384 [11:00<24:46:49,  7.26s/it, loss=26.7861, acc=0.0012, iter_time=7.27s]
Epoch 0:   1%|          | 91/12384 [11:08<24:46:49,  7.26s/it, loss=24.3304, acc=0.0012, iter_time=7.25s]
Epoch 0:   1%|          | 92/12384 [11:08<24:46:38,  7.26s/it, loss=24.3304, acc=0.0012, iter_time=7.25s]
Epoch 0:   1%|          | 92/12384 [11:15<24:46:38,  7.26s/it, loss=26.2561, acc=0.0007, iter_time=5.69s]
Epoch 0:   1%|          | 93/12384 [11:15<24:45:51,  7.25s/it, loss=26.2561, acc=0.0007, iter_time=5.69s]
Epoch 0:   1%|          | 93/12384 [11:22<24:45:51,  7.25s/it, loss=25.0205, acc=0.0013, iter_time=8.80s]
Epoch 0:   1%|          | 94/12384 [11:22<24:44:52,  7.25s/it, loss=25.0205, acc=0.0013, iter_time=8.80s]
Epoch 0:   1%|          | 94/12384 [11:29<24:44:52,  7.25s/it, loss=26.0604, acc=0.0012, iter_time=5.94s]
Epoch 0:   1%|          | 95/12384 [11:29<24:43:22,  7.24s/it, loss=26.0604, acc=0.0012, iter_time=5.94s]
Epoch 0:   1%|          | 95/12384 [11:37<24:43:22,  7.24s/it, loss=25.8327, acc=0.0003, iter_time=8.40s]
Epoch 0:   1%|          | 96/12384 [11:37<24:44:01,  7.25s/it, loss=25.8327, acc=0.0003, iter_time=8.40s]
Epoch 0:   1%|          | 96/12384 [11:44<24:44:01,  7.25s/it, loss=25.7407, acc=0.0004, iter_time=4.80s]
Epoch 0:   1%|          | 97/12384 [11:44<24:44:23,  7.25s/it, loss=25.7407, acc=0.0004, iter_time=4.80s]
Epoch 0:   1%|          | 97/12384 [11:51<24:44:23,  7.25s/it, loss=24.6398, acc=0.0008, iter_time=9.83s]
Epoch 0:   1%|          | 98/12384 [11:51<24:43:52,  7.25s/it, loss=24.6398, acc=0.0008, iter_time=9.83s]
Epoch 0:   1%|          | 98/12384 [11:59<24:43:52,  7.25s/it, loss=25.8374, acc=0.0004, iter_time=7.30s]
Epoch 0:   1%|          | 99/12384 [11:59<25:00:21,  7.33s/it, loss=25.8374, acc=0.0004, iter_time=7.30s]
Epoch 0:   1%|          | 99/12384 [12:06<25:00:21,  7.33s/it, loss=24.4787, acc=0.0002, iter_time=7.85s]
Epoch 0:   1%|          | 100/12384 [12:06<24:55:01,  7.30s/it, loss=24.4787, acc=0.0002, iter_time=7.85s]
Epoch 0:   1%|          | 100/12384 [12:13<24:55:01,  7.30s/it, loss=26.2808, acc=0.0007, iter_time=6.86s]
Epoch 0:   1%|          | 101/12384 [12:13<24:51:55,  7.29s/it, loss=26.2808, acc=0.0007, iter_time=6.86s]
Epoch 0:   1%|          | 101/12384 [12:20<24:51:55,  7.29s/it, loss=25.5292, acc=0.0003, iter_time=7.25s]
Epoch 0:   1%|          | 102/12384 [12:20<24:49:11,  7.27s/it, loss=25.5292, acc=0.0003, iter_time=7.25s]
Epoch 0:   1%|          | 102/12384 [12:28<24:49:11,  7.27s/it, loss=24.7556, acc=0.0012, iter_time=7.25s]
Epoch 0:   1%|          | 103/12384 [12:28<24:47:47,  7.27s/it, loss=24.7556, acc=0.0012, iter_time=7.25s]
Epoch 0:   1%|          | 103/12384 [12:35<24:47:47,  7.27s/it, loss=24.5222, acc=0.0009, iter_time=7.65s]
Epoch 0:   1%|          | 104/12384 [12:35<24:47:23,  7.27s/it, loss=24.5222, acc=0.0009, iter_time=7.65s]
Epoch 0:   1%|          | 104/12384 [12:42<24:47:23,  7.27s/it, loss=25.7881, acc=0.0008, iter_time=4.75s]
Epoch 0:   1%|          | 105/12384 [12:42<24:44:57,  7.26s/it, loss=25.7881, acc=0.0008, iter_time=4.75s]
Epoch 0:   1%|          | 105/12384 [12:49<24:44:57,  7.26s/it, loss=24.2179, acc=0.0007, iter_time=8.55s]
Epoch 0:   1%|          | 106/12384 [12:49<24:46:52,  7.27s/it, loss=24.2179, acc=0.0007, iter_time=8.55s]
Epoch 0:   1%|          | 106/12384 [12:57<24:46:52,  7.27s/it, loss=25.2753, acc=0.0006, iter_time=8.08s]
Epoch 0:   1%|          | 107/12384 [12:57<24:45:38,  7.26s/it, loss=25.2753, acc=0.0006, iter_time=8.08s]
Epoch 0:   1%|          | 107/12384 [13:04<24:45:38,  7.26s/it, loss=23.8982, acc=0.0015, iter_time=7.26s]
Epoch 0:   1%|          | 108/12384 [13:04<24:45:00,  7.26s/it, loss=23.8982, acc=0.0015, iter_time=7.26s]
Epoch 0:   1%|          | 108/12384 [13:11<24:45:00,  7.26s/it, loss=24.9451, acc=0.0011, iter_time=7.25s]
Epoch 0:   1%|          | 109/12384 [13:11<24:44:08,  7.25s/it, loss=24.9451, acc=0.0011, iter_time=7.25s]
Epoch 0:   1%|          | 109/12384 [13:18<24:44:08,  7.25s/it, loss=24.2399, acc=0.0012, iter_time=7.25s]
Epoch 0:   1%|          | 110/12384 [13:18<24:43:46,  7.25s/it, loss=24.2399, acc=0.0012, iter_time=7.25s]
Epoch 0:   1%|          | 110/12384 [13:26<24:43:46,  7.25s/it, loss=24.5482, acc=0.0006, iter_time=7.32s]
Epoch 0:   1%|          | 111/12384 [13:26<24:48:37,  7.28s/it, loss=24.5482, acc=0.0006, iter_time=7.32s]
Epoch 0:   1%|          | 111/12384 [13:33<24:48:37,  7.28s/it, loss=24.6159, acc=0.0011, iter_time=7.64s]
Epoch 0:   1%|          | 112/12384 [13:33<24:46:39,  7.27s/it, loss=24.6159, acc=0.0011, iter_time=7.64s]
Epoch 0:   1%|          | 112/12384 [13:40<24:46:39,  7.27s/it, loss=24.9661, acc=0.0007, iter_time=4.96s]
Epoch 0:   1%|          | 113/12384 [13:40<24:45:09,  7.26s/it, loss=24.9661, acc=0.0007, iter_time=4.96s]
Epoch 0:   1%|          | 113/12384 [13:47<24:45:09,  7.26s/it, loss=23.9603, acc=0.0010, iter_time=5.83s]
Epoch 0:   1%|          | 114/12384 [13:47<24:44:07,  7.26s/it, loss=23.9603, acc=0.0010, iter_time=5.83s]
Epoch 0:   1%|          | 114/12384 [13:55<24:44:07,  7.26s/it, loss=25.1833, acc=0.0010, iter_time=7.48s]
Epoch 0:   1%|          | 115/12384 [13:55<24:42:44,  7.25s/it, loss=25.1833, acc=0.0010, iter_time=7.48s]
Epoch 0:   1%|          | 115/12384 [14:02<24:42:44,  7.25s/it, loss=24.7678, acc=0.0012, iter_time=10.03s]
Epoch 0:   1%|          | 116/12384 [14:02<24:41:41,  7.25s/it, loss=24.7678, acc=0.0012, iter_time=10.03s]
Epoch 0:   1%|          | 116/12384 [14:09<24:41:41,  7.25s/it, loss=25.1418, acc=0.0007, iter_time=7.53s] 
Epoch 0:   1%|          | 117/12384 [14:09<24:42:13,  7.25s/it, loss=25.1418, acc=0.0007, iter_time=7.53s]
Epoch 0:   1%|          | 117/12384 [14:16<24:42:13,  7.25s/it, loss=25.1265, acc=0.0002, iter_time=7.23s]
Epoch 0:   1%|          | 118/12384 [14:16<24:40:32,  7.24s/it, loss=25.1265, acc=0.0002, iter_time=7.23s]
Epoch 0:   1%|          | 118/12384 [14:24<24:40:32,  7.24s/it, loss=25.7655, acc=0.0009, iter_time=6.15s]
Epoch 0:   1%|          | 119/12384 [14:24<24:39:52,  7.24s/it, loss=25.7655, acc=0.0009, iter_time=6.15s]
Epoch 0:   1%|          | 119/12384 [14:31<24:39:52,  7.24s/it, loss=24.9375, acc=0.0007, iter_time=8.69s]
Epoch 0:   1%|          | 120/12384 [14:31<24:39:07,  7.24s/it, loss=24.9375, acc=0.0007, iter_time=8.69s]
Epoch 0:   1%|          | 120/12384 [14:38<24:39:07,  7.24s/it, loss=24.9806, acc=0.0010, iter_time=6.84s]
Epoch 0:   1%|          | 121/12384 [14:38<24:38:55,  7.24s/it, loss=24.9806, acc=0.0010, iter_time=6.84s]
Epoch 0:   1%|          | 121/12384 [14:45<24:38:55,  7.24s/it, loss=25.6743, acc=0.0008, iter_time=7.25s]
Epoch 0:   1%|          | 122/12384 [14:45<24:38:58,  7.24s/it, loss=25.6743, acc=0.0008, iter_time=7.25s]
Epoch 0:   1%|          | 122/12384 [14:52<24:38:58,  7.24s/it, loss=26.0748, acc=0.0005, iter_time=3.88s]
Epoch 0:   1%|          | 123/12384 [14:52<24:38:40,  7.24s/it, loss=26.0748, acc=0.0005, iter_time=3.88s]
Epoch 0:   1%|          | 123/12384 [15:00<24:38:40,  7.24s/it, loss=25.7487, acc=0.0014, iter_time=10.82s]
Epoch 0:   1%|          | 124/12384 [15:00<24:52:38,  7.30s/it, loss=25.7487, acc=0.0014, iter_time=10.82s]
Epoch 0:   1%|          | 124/12384 [15:07<24:52:38,  7.30s/it, loss=26.6740, acc=0.0005, iter_time=7.25s] 
Epoch 0:   1%|          | 125/12384 [15:07<24:49:50,  7.29s/it, loss=26.6740, acc=0.0005, iter_time=7.25s]
Epoch 0:   1%|          | 125/12384 [15:14<24:49:50,  7.29s/it, loss=26.0283, acc=0.0007, iter_time=3.85s]
Epoch 0:   1%|          | 126/12384 [15:14<24:46:25,  7.28s/it, loss=26.0283, acc=0.0007, iter_time=3.85s]
Epoch 0:   1%|          | 126/12384 [15:22<24:46:25,  7.28s/it, loss=24.9161, acc=0.0009, iter_time=10.65s]
Epoch 0:   1%|          | 127/12384 [15:22<24:44:47,  7.27s/it, loss=24.9161, acc=0.0009, iter_time=10.65s]
Epoch 0:   1%|          | 127/12384 [15:29<24:44:47,  7.27s/it, loss=26.3718, acc=0.0008, iter_time=7.63s] 
Epoch 0:   1%|          | 128/12384 [15:29<24:43:48,  7.26s/it, loss=26.3718, acc=0.0008, iter_time=7.63s]
Epoch 0:   1%|          | 128/12384 [15:36<24:43:48,  7.26s/it, loss=25.1223, acc=0.0010, iter_time=6.88s]
Epoch 0:   1%|          | 129/12384 [15:36<24:43:19,  7.26s/it, loss=25.1223, acc=0.0010, iter_time=6.88s]
Epoch 0:   1%|          | 129/12384 [15:43<24:43:19,  7.26s/it, loss=25.4832, acc=0.0003, iter_time=3.89s]
Epoch 0:   1%|          | 130/12384 [15:43<24:41:40,  7.25s/it, loss=25.4832, acc=0.0003, iter_time=3.89s]
Epoch 0:   1%|          | 130/12384 [15:51<24:41:40,  7.25s/it, loss=24.9629, acc=0.0021, iter_time=10.59s]
Epoch 0:   1%|          | 131/12384 [15:51<24:41:27,  7.25s/it, loss=24.9629, acc=0.0021, iter_time=10.59s]
Epoch 0:   1%|          | 131/12384 [15:58<24:41:27,  7.25s/it, loss=24.9183, acc=0.0016, iter_time=7.26s] 
Epoch 0:   1%|          | 132/12384 [15:58<24:40:23,  7.25s/it, loss=24.9183, acc=0.0016, iter_time=7.26s]
Epoch 0:   1%|          | 132/12384 [16:05<24:40:23,  7.25s/it, loss=26.3849, acc=0.0005, iter_time=7.25s]
Epoch 0:   1%|          | 133/12384 [16:05<24:40:42,  7.25s/it, loss=26.3849, acc=0.0005, iter_time=7.25s]
Epoch 0:   1%|          | 133/12384 [16:12<24:40:42,  7.25s/it, loss=25.2442, acc=0.0001, iter_time=7.26s]
Epoch 0:   1%|          | 134/12384 [16:12<24:41:10,  7.25s/it, loss=25.2442, acc=0.0001, iter_time=7.26s]
Epoch 0:   1%|          | 134/12384 [16:20<24:41:10,  7.25s/it, loss=25.4194, acc=0.0010, iter_time=7.25s]
Epoch 0:   1%|          | 135/12384 [16:20<24:40:07,  7.25s/it, loss=25.4194, acc=0.0010, iter_time=7.25s]W0323 13:19:51.617000 11145 site-packages/torch/distributed/elastic/agent/server/api.py:725] Received 15 death signal, shutting down workers
W0323 13:19:51.635000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11250 closing signal SIGTERM
W0323 13:19:51.635000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11251 closing signal SIGTERM
W0323 13:19:51.636000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11252 closing signal SIGTERM
W0323 13:19:51.636000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11253 closing signal SIGTERM
W0323 13:19:51.636000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11254 closing signal SIGTERM
W0323 13:19:51.636000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11255 closing signal SIGTERM
W0323 13:19:51.636000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11256 closing signal SIGTERM
W0323 13:19:51.637000 11145 site-packages/torch/distributed/elastic/multiprocessing/api.py:908] Sending process 11257 closing signal SIGTERM
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/run.py", line 940, in <module>
    main()
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 357, in wrapper
    return f(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/run.py", line 936, in main
    run(args)
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/run.py", line 927, in run
    elastic_launch(
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 156, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 284, in launch_agent
    result = agent.run()
             ^^^^^^^^^^^
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/elastic/metrics/api.py", line 138, in wrapper
    result = f(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/elastic/agent/server/api.py", line 717, in run
    result = self._invoke_run(role)
             ^^^^^^^^^^^^^^^^^^^^^^
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/elastic/agent/server/api.py", line 881, in _invoke_run
    time.sleep(monitor_interval)
  File "/workspace/miniconda3/envs/spec/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 85, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 11145 got signal: 15