Duplicated space runtime error

#72
by ikolomiets - opened

Hi there,

Excellent quality of the tool! Unfortunately, as I'm trying to run a duplicate space, I get this error:

Screenshot 2024-06-21 at 13.03.12.png

Can somebody please advise on how to fix it?
Thank you!

Full stack trace:

===== Application Startup at 2024-06-21 07:05:58 =====

The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.


0it [00:00, ?it/s]
0it [00:00, ?it/s]
Traceback (most recent call last):
  File "/home/user/app/app.py", line 24, in <module>
    from controlnet_aux import OpenposeDetector
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/__init__.py", line 7, in <module>
    from .midas import MidasDetector
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/__init__.py", line 11, in <module>
    from .api import MiDaSInference
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/api.py", line 9, in <module>
    from .midas.dpt_depth import DPTDepthModel
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/midas/dpt_depth.py", line 6, in <module>
    from .blocks import (
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/midas/blocks.py", line 4, in <module>
    from .vit import (
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/midas/vit.py", line 3, in <module>
    import timm
  File "/usr/local/lib/python3.10/site-packages/timm/__init__.py", line 2, in <module>
    from .models import create_model, list_models, is_model, list_modules, model_entrypoint, \
  File "/usr/local/lib/python3.10/site-packages/timm/models/__init__.py", line 1, in <module>
    from .beit import *
  File "/usr/local/lib/python3.10/site-packages/timm/models/beit.py", line 30, in <module>
    from .helpers import build_model_with_cfg
  File "/usr/local/lib/python3.10/site-packages/timm/models/helpers.py", line 21, in <module>
    from .fx_features import FeatureGraphNet
  File "/usr/local/lib/python3.10/site-packages/timm/models/fx_features.py", line 18, in <module>
    from .layers import Conv2dSame, ScaledStdConv2dSame, CondConv2d, StdConv2dSame
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/__init__.py", line 10, in <module>
    from .conv_bn_act import ConvNormAct, ConvNormActAa, ConvBnAct
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/conv_bn_act.py", line 9, in <module>
    from .create_norm_act import get_norm_act_layer
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/create_norm_act.py", line 12, in <module>
    from .evo_norm import *
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/evo_norm.py", line 32, in <module>
    from .create_act import create_act_layer
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/create_act.py", line 8, in <module>
    from .activations_me import *
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/activations_me.py", line 105, in <module>
    def hard_sigmoid_jit_bwd(x, grad_output):
  File "/usr/local/lib/python3.10/site-packages/torch/jit/_script.py", line 1341, in script
    fn = torch._C._jit_script_compile(
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 71, in get_signature
    signature = try_real_annotations(fn, loc)
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 278, in try_real_annotations
    arg_types = [ann_to_type(p.annotation, loc)
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 278, in <listcomp>
    arg_types = [ann_to_type(p.annotation, loc)
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 422, in ann_to_type
    raise ValueError(f"Unknown type annotation: '{ann}' at {loc.highlight()}")
ValueError: Unknown type annotation: 'Any' at   File "/usr/local/lib/python3.10/site-packages/timm/models/layers/activations_me.py", line 106


@torch
	.jit.script
def hard_sigmoid_jit_bwd(x, grad_output):
    m = torch.ones_like(x) * ((x >= -3.) & (x <= 3.)) / 6.
        ~~~~~~~~~~~~~~~ <--- HERE
    return grad_output * m

The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.


0it [00:00, ?it/s]
0it [00:00, ?it/s]
Traceback (most recent call last):
  File "/home/user/app/app.py", line 24, in <module>
    from controlnet_aux import OpenposeDetector
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/__init__.py", line 7, in <module>
    from .midas import MidasDetector
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/__init__.py", line 11, in <module>
    from .api import MiDaSInference
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/api.py", line 9, in <module>
    from .midas.dpt_depth import DPTDepthModel
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/midas/dpt_depth.py", line 6, in <module>
    from .blocks import (
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/midas/blocks.py", line 4, in <module>
    from .vit import (
  File "/usr/local/lib/python3.10/site-packages/controlnet_aux/midas/midas/vit.py", line 3, in <module>
    import timm
  File "/usr/local/lib/python3.10/site-packages/timm/__init__.py", line 2, in <module>
    from .models import create_model, list_models, is_model, list_modules, model_entrypoint, \
  File "/usr/local/lib/python3.10/site-packages/timm/models/__init__.py", line 1, in <module>
    from .beit import *
  File "/usr/local/lib/python3.10/site-packages/timm/models/beit.py", line 30, in <module>
    from .helpers import build_model_with_cfg
  File "/usr/local/lib/python3.10/site-packages/timm/models/helpers.py", line 21, in <module>
    from .fx_features import FeatureGraphNet
  File "/usr/local/lib/python3.10/site-packages/timm/models/fx_features.py", line 18, in <module>
    from .layers import Conv2dSame, ScaledStdConv2dSame, CondConv2d, StdConv2dSame
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/__init__.py", line 10, in <module>
    from .conv_bn_act import ConvNormAct, ConvNormActAa, ConvBnAct
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/conv_bn_act.py", line 9, in <module>
    from .create_norm_act import get_norm_act_layer
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/create_norm_act.py", line 12, in <module>
    from .evo_norm import *
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/evo_norm.py", line 32, in <module>
    from .create_act import create_act_layer
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/create_act.py", line 8, in <module>
    from .activations_me import *
  File "/usr/local/lib/python3.10/site-packages/timm/models/layers/activations_me.py", line 105, in <module>
    def hard_sigmoid_jit_bwd(x, grad_output):
  File "/usr/local/lib/python3.10/site-packages/torch/jit/_script.py", line 1341, in script
    fn = torch._C._jit_script_compile(
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 71, in get_signature
    signature = try_real_annotations(fn, loc)
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 278, in try_real_annotations
    arg_types = [ann_to_type(p.annotation, loc)
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 278, in <listcomp>
    arg_types = [ann_to_type(p.annotation, loc)
  File "/usr/local/lib/python3.10/site-packages/torch/jit/annotations.py", line 422, in ann_to_type
    raise ValueError(f"Unknown type annotation: '{ann}' at {loc.highlight()}")
ValueError: Unknown type annotation: 'Any' at   File "/usr/local/lib/python3.10/site-packages/timm/models/layers/activations_me.py", line 106


@torch
	.jit.script
def hard_sigmoid_jit_bwd(x, grad_output):
    m = torch.ones_like(x) * ((x >= -3.) & (x <= 3.)) / 6.
        ~~~~~~~~~~~~~~~ <--- HERE
    return grad_output * m

Same error

Same error

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