pretrained-model loading with errors

[Ao-Lee]

Hello,
I used single GPU env with python == 3.8, torch==1.8.1 and torchvision==0.9.1
I followed the github hint with the following command:

python3 infer.py --gpu --image demo_image/demo_2.jpg --model vitstr_small_patch16_224.pth

It returned an error with

AttributeError: 'collections.OrderedDict' object has no attribute 'to'

it seems that the function model = torch.load(checkpoint) in infer.py returns an ordered dict instead of the model object.
One way to solve the problem is:

ordered_dict = torch.load(checkpoint)
model.load(ordered_dict )

But I do not know the hyper params of vitstr_small_patch16_224.pth when it is training. so it is very hard form me to initialize the model object with correct hyper params.
I would like to ask would it possible to may the hyper params of the pretrained models public?

I also tried the pt models

python3 infer.py --gpu --image demo_image/demo_2.jpg --model vitstr_small_patch16_jit.pt

it gives the following error:

  File "E:\ProgramFiles\anaconda3\envs\vitstr\lib\site-packages\spyder_kernels\py3compat.py", line 356, in compat_exec
    exec(code, globals, locals)

  File "e:\projects\deep-text-recognition-benchmark-master\infer.py", line 147, in <module>
    data = infer(args)

  File "e:\projects\deep-text-recognition-benchmark-master\infer.py", line 121, in infer
    model = torch.load(checkpoint)

  File "E:\ProgramFiles\anaconda3\envs\vitstr\lib\site-packages\torch\serialization.py", line 591, in load
    return torch.jit.load(opened_file)

  File "E:\ProgramFiles\anaconda3\envs\vitstr\lib\site-packages\torch\jit\_serialization.py", line 163, in load
    cpp_module = torch._C.import_ir_module_from_buffer(

RuntimeError: 
Unknown type name 'NoneType':
Serialized   File "code/__torch__/modules/vitstr.py", line 12
  embed_dim : int
  num_tokens : int
  dist_token : NoneType
               ~~~~~~~~ <--- HERE
  head_dist : NoneType
  patch_embed : __torch__.timm.models.layers.patch_embed.PatchEmbed

any way to load the model correctly please?
may thanks

[roatienza]

I just tried. Everything seems fine. Both on cpu and gpu inference.

(base) rowel@atienza-G190-G30:\~/github/roatienza/deep-text-recognition-benchmark$ python3 infer.py --image demo_image/demo_2.jpg --model https://github.com/roatienza/deep-text-recognition-benchmark/releases/download/v0.1.0/vitstr_small_patch16_jit.pt
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 82.1M/82.1M [00:01<00:00, 84.0MB/s]
/home/rowel/anaconda3/lib/python3.7/site-packages/torch/serialization.py:709: UserWarning: 'torch.load' received a zip file that looks like a TorchScript archive dispatching to 'torch.jit.load' (call 'torch.jit.load' directly to silence this warning)
  " silence this warning)", UserWarning)
demo_image/demo_2.jpg   :  SHAKESHACK
(base) rowel@atienza-G190-G30:\~/github/roatienza/deep-text-recognition-benchmark$ python3 infer.py --image demo_image/demo_2.jpg --model vitstr_small_patch16_jit.pt
/home/rowel/anaconda3/lib/python3.7/site-packages/torch/serialization.py:709: UserWarning: 'torch.load' received a zip file that looks like a TorchScript archive dispatching to 'torch.jit.load' (call 'torch.jit.load' directly to silence this warning)
  " silence this warning)", UserWarning)
demo_image/demo_2.jpg   :  SHAKESHACK
(base) rowel@atienza-G190-G30:\~/github/roatienza/deep-text-recognition-benchmark$ python3
Python 3.7.3 (default, Mar 27 2019, 22:11:17) 
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.__version__)
1.11.0+cu113
>>> 
(base) rowel@atienza-G190-G30:\~/github/roatienza/deep-text-recognition-benchmark$ python3 infer.py --image demo_image/demo_2.jpg --gpu --model vitstr_small_patch16_jit.pt
/home/rowel/anaconda3/lib/python3.7/site-packages/torch/serialization.py:709: UserWarning: 'torch.load' received a zip file that looks like a TorchScript archive dispatching to 'torch.jit.load' (call 'torch.jit.load' directly to silence this warning)
  " silence this warning)", UserWarning)
demo_image/demo_2.jpg   :  SHAKESHACK

[Ao-Lee]

thx. I can update torch from 1.8 to 1.11.0 and try again

[Ao-Lee]

would kindly like to ask if requirements.txt can be update to your current environment setting please?

[Ao-Lee]

all problems are solved with pytorch 1.11.0, many thanks, plz close this issue

[raisinbl]

@Ao-Lee

it seems that the function model = torch.load(checkpoint) in infer.py returns an ordered dict instead of the model object.
One way to solve the problem is:

ordered_dict = torch.load(checkpoint)  
model.load(ordered_dict )

How can you create model in infer.py. Can you show me how to that? I want to infer from my checkpoint but I was stuck there
Thank you so much.

[roatienza]

In test.py,

deep-text-recognition-benchmark/test.py

Line 237 in ea0d077

# https://pytorch.org/tutorials/beginner/saving_loading_models.html

It is triggered by --infer-model option. The pytorch doc for JIT is also indicated.

[raisinbl]

In test.py,

deep-text-recognition-benchmark/test.py

Line 237 in ea0d077

# https://pytorch.org/tutorials/beginner/saving_loading_models.html

It is triggered by --infer-model option. The pytorch doc for JIT is also indicated.

Thank you so much! My problem is solved

[siddagra]

Should probably update requirements.txt to torch=1.1.0