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Dear cjerry, thank you for sharing your great work!
When I executed python train.py -c config_24k.json, I got:
Selected optimization level O1: Insert automatic casts around Pytorch functions and Tensor methods.
Defaults for this optimization level are:
enabled : True
opt_level : O1
cast_model_type : None
patch_torch_functions : True
keep_batchnorm_fp32 : None
master_weights : None
loss_scale : dynamic
Processing user overrides (additional kwargs that are not None)...
After processing overrides, optimization options are:
enabled : True
opt_level : O1
cast_model_type : None
patch_torch_functions : True
keep_batchnorm_fp32 : None
master_weights : None
loss_scale : dynamic
Warning: multi_tensor_applier fused unscale kernel is unavailable, possibly because apex was installed without --cuda_ext --cpp_ext. Using Python fallback. Original ImportError was: ModuleNotFoundError("No module named 'amp_C'",)
Traceback (most recent call last):
File "train.py", line 141, in <module>
train(**train_config)
File "train.py", line 74, in train
if rank == 0:
NameError: name 'rank' is not defined
Is it maybe possible that the argument rank is missing in the function train in train.py?
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