Bug got an unexpected keyword argument 'strides

[ternaus]

Affects most of the network architectures.

In [1]: import segmentation_models_pytorch_3d as smp

In [2]: model = smp.Unet(
   ...:             encoder_name="timm-skresnet34",
   ...:             encoder_weights=None,
   ...:             in_channels=1,
   ...:             classes=3,
   ...:             activation=None,
   ...:         ),
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[2], line 1
----> 1 model = smp.Unet(
      2             encoder_name="timm-skresnet34",
      3             encoder_weights=None,
      4             in_channels=1,
      5             classes=3,
      6             activation=None,
      7         ),

File ~/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/decoders/unet/model.py:72, in Unet.__init__(self, encoder_name, encoder_depth, encoder_weights, decoder_use_batchnorm, decoder_channels, decoder_attention_type, in_channels, classes, activation, aux_params, strides)
     56 def __init__(
     57     self,
     58     encoder_name: str = "resnet34",
   (...)
     68     strides=((2, 2, 2), (2, 2, 2), (2, 2, 2), (2, 2, 2), (2, 2, 2))
     69 ):
     70     super().__init__()
---> 72     self.encoder = get_encoder(
     73         encoder_name,
     74         in_channels=in_channels,
     75         depth=encoder_depth,
     76         weights=encoder_weights,
     77         strides=strides,
     78     )
     80     self.decoder = UnetDecoder(
     81         encoder_channels=self.encoder.out_channels,
     82         decoder_channels=decoder_channels,
   (...)
     87         strides=strides,
     88     )
     90     self.segmentation_head = SegmentationHead(
     91         in_channels=decoder_channels[-1],
     92         out_channels=classes,
     93         activation=activation,
     94         kernel_size=3,
     95     )

File ~/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/__init__.py:73, in get_encoder(name, in_channels, depth, weights, output_stride, strides, **kwargs)
     71 params.update(depth=depth)
     72 params.update(strides=strides)
---> 73 encoder = Encoder(**params)
     75 if weights is not None:
     76     try:

File ~/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/timm_sknet.py:9, in SkNetEncoder.__init__(self, out_channels, depth, **kwargs)
      8 def __init__(self, out_channels, depth=5, **kwargs):
----> 9     super().__init__(**kwargs)
     10     self._depth = depth
     11     self._out_channels = out_channels

TypeError: ResNet.__init__() got an unexpected keyword argument 'strides'

[ternaus]

Testing encoder: senet154
❌ Failed: SENet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: se_resnet50
❌ Failed: SENet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: se_resnet101
❌ Failed: SENet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: se_resnet152
❌ Failed: SENet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: se_resnext50_32x4d
❌ Failed: SENet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: se_resnext101_32x4d
❌ Failed: SENet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: inceptionresnetv2
❌ Failed: InceptionResNetV2.__init__() got an unexpected keyword argument 'strides'

Testing encoder: inceptionv4
❌ Failed: InceptionV4.__init__() got an unexpected keyword argument 'strides'

Testing encoder: mobilenet_v2
❌ Failed: MobileNetV2.__init__() got an unexpected keyword argument 'strides'

Testing encoder: xception
❌ Failed: Xception.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b0
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b1
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b2
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b3
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b4
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b5
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b6
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b7
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-b8
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-efficientnet-l2
❌ Failed: EfficientNetEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-tf_efficientnet_lite0
❌ Failed: EfficientNetLiteEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-tf_efficientnet_lite1
❌ Failed: EfficientNetLiteEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-tf_efficientnet_lite2
❌ Failed: EfficientNetLiteEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-tf_efficientnet_lite3
❌ Failed: EfficientNetLiteEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-tf_efficientnet_lite4
❌ Failed: EfficientNetLiteEncoder.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest14d
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest26d
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest50d
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest101e
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest200e
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest269e
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest50d_4s2x40d
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-resnest50d_1s4x24d
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2net50_26w_4s
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2net101_26w_4s
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2net50_26w_6s
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2net50_26w_8s
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2net50_48w_2s
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2net50_14w_8s
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-res2next50
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_002
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_004
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_006
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_008
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_016
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_032
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_040
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_064
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_080
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_120
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_160
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnetx_320
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_002
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_004
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_006
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_008
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_016
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_032
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_040
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_064
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_080
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_120
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_160
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-regnety_320
❌ Failed: RegNetCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-skresnet18
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-skresnet34
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-skresnext50_32x4d
❌ Failed: ResNet.__init__() got an unexpected keyword argument 'strides'


Testing encoder: timm-gernet_s
❌ Failed: ByoModelCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-gernet_m
❌ Failed: ByoModelCfg.__init__() got an unexpected keyword argument 'strides'

Testing encoder: timm-gernet_l
❌ Failed: ByoModelCfg.__init__() got an unexpected keyword argument 'strides'

[ZFTurbo]

It's expected. There is note in main readme file:
Note: Strides currently supported by resnet-family and densenet models with Unet decoder only.

[ternaus]

I am initializing as:

model = smp.Unet(
    encoder_name=encoder_name,
    encoder_weights=None,
    in_channels=1,
    classes=3,
    activation=None,
)

not passing strides as input

[ternaus]

I tried to figure out what Unet's could be torchscripted with this script:

import time
from pathlib import Path

import segmentation_models_pytorch_3d as smp
import torch
from torch import nn
from tqdm import tqdm


class ModelWrapper(nn.Module):
    """Wrapper to return output directly"""

    def __init__(self, model):
        super().__init__()
        self.model = model

    def forward(self, x):
        return self.model(x)


def test_encoder(encoder_name: str, output_dir: Path) -> dict:
    """Test if an encoder can be TorchScripted"""
    print(f"\nTesting encoder: {encoder_name}")
    result = {
        "encoder": encoder_name,
        "success": False,
        "error": None,
        "model_size": {
            "mb": None,
            "bytes": None,
            "human_readable": None,
        },
        "trace_time": None,
    }

    try:
        # Create model
        model = smp.Unet(
            encoder_name=encoder_name,
            encoder_weights=None,
            in_channels=1,
            classes=3,
            activation=None,
        )

        # Wrap model
        wrapped_model = ModelWrapper(model)
        wrapped_model.eval()

        # Create example input with smaller dimensions for testing
        example_input = torch.randn(1, 1, 64, 64, 64, dtype=torch.float32)

        start_time = time.time()
        with torch.inference_mode():
            traced_model = torch.jit.trace(wrapped_model, example_input)
            traced_model(example_input)

            # Save the model
            output_path = output_dir / f"unet_{encoder_name}.pt"
            torch.jit.save(traced_model, output_path)

            # Get detailed size information
            size_bytes = output_path.stat().st_size
            size_mb = size_bytes / (1024 * 1024)

            # Human readable size
            def human_size(size_in_bytes):
                for unit in ["B", "KB", "MB", "GB"]:
                    if size_in_bytes < 1024.0:
                        return f"{size_in_bytes:.2f} {unit}"
                    size_in_bytes /= 1024.0
                return f"{size_in_bytes:.2f} GB"

        trace_time = time.time() - start_time

        result.update(
            {
                "success": True,
                "model_size": {
                    "mb": round(size_mb, 2),
                    "bytes": size_bytes,
                    "human_readable": human_size(size_bytes),
                },
                "trace_time": round(trace_time, 2),
            },
        )
        print(f"✅ Success! Size: {human_size(size_bytes)}, Trace time: {trace_time:.2f}s")

    except Exception as e:
        result["error"] = str(e)
        print(f"❌ Failed: {e!s}")

    return result


def main():
    # Create output directory
    output_dir = Path("encoder_tests")
    output_dir.mkdir(exist_ok=True)

    # Get all available encoders
    encoders = smp.encoders.get_encoder_names()
    print(f"Found {len(encoders)} encoders to test")

    # Test each encoder
    results = []
    for encoder in tqdm(encoders):
        result = test_encoder(encoder, output_dir)
        results.append(result)

    # Save results
    successful = [r for r in results if r["success"]]
    failed = [r for r in results if not r["success"]]

    print("\n=== Summary ===")
    print(f"Total encoders tested: {len(results)}")
    print(f"Successful: {len(successful)}")
    print(f"Failed: {len(failed)}")

    print(successful)

    if successful:
        print("\nSuccessful encoders:")
        for r in successful:
            print(f"- {r['encoder']}: {r['model_size']['mb']}MB")

    if failed:
        print("\nFailed encoders:")
        for r in failed:
            print(f"- {r['encoder']}: {r['error']}")

    # Save detailed results to file
    import json

    with (output_dir / "results.json").open("w") as f:
        json.dump(results, f, indent=2)


if __name__ == "__main__":
    main()

[ternaus]

Results:

[
  {
    "encoder": "resnet18",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 162.83,
      "bytes": 170741079,
      "human_readable": "162.83 MB"
    },
    "trace_time": 2.22
  },
  {
    "encoder": "resnet34",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 278.59,
      "bytes": 292121293,
      "human_readable": "278.59 MB"
    },
    "trace_time": 3.42
  },
  {
    "encoder": "resnet50",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 279.84,
      "bytes": 293428825,
      "human_readable": "279.84 MB"
    },
    "trace_time": 3.77
  },
  {
    "encoder": "resnet101",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 429.28,
      "bytes": 450133050,
      "human_readable": "429.28 MB"
    },
    "trace_time": 5.08
  },
  {
    "encoder": "resnet152",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 552.43,
      "bytes": 579260336,
      "human_readable": "552.43 MB"
    },
    "trace_time": 6.77
  },
  {
    "encoder": "resnext50_32x4d",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 202.34,
      "bytes": 212165462,
      "human_readable": "202.34 MB"
    },
    "trace_time": 2.6
  },
  {
    "encoder": "resnext101_32x4d",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 285.51,
      "bytes": 299381405,
      "human_readable": "285.51 MB"
    },
    "trace_time": 3.88
  },
  {
    "encoder": "resnext101_32x8d",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 517.01,
      "bytes": 542128861,
      "human_readable": "517.01 MB"
    },
    "trace_time": 4.82
  },
  {
    "encoder": "resnext101_32x16d",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 1163.22,
      "bytes": 1219723810,
      "human_readable": "1.14 GB"
    },
    "trace_time": 8.77
  },
  {
    "encoder": "resnext101_32x32d",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 3188.42,
      "bytes": 3343303266,
      "human_readable": "3.11 GB"
    },
    "trace_time": 19.21
  },
  {
    "encoder": "resnext101_32x48d",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 6190.71,
      "bytes": 6491431338,
      "human_readable": "6.05 GB"
    },
    "trace_time": 35.25
  },
  {
    "encoder": "dpn68",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 119.19,
      "bytes": 124978793,
      "human_readable": "119.19 MB"
    },
    "trace_time": 2.68
  },
  {
    "encoder": "dpn68b",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 119.23,
      "bytes": 125019869,
      "human_readable": "119.23 MB"
    },
    "trace_time": 3.83
  },
  {
    "encoder": "dpn92",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 282.29,
      "bytes": 296001491,
      "human_readable": "282.29 MB"
    },
    "trace_time": 4.18
  },
  {
    "encoder": "dpn98",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 392.47,
      "bytes": 411530659,
      "human_readable": "392.47 MB"
    },
    "trace_time": 5.68
  },
  {
    "encoder": "dpn107",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 519.85,
      "bytes": 545103273,
      "human_readable": "519.85 MB"
    },
    "trace_time": 6.73
  },
  {
    "encoder": "dpn131",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 474.25,
      "bytes": 497288537,
      "human_readable": "474.25 MB"
    },
    "trace_time": 6.42
  },
  {
    "encoder": "vgg11",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 209.02,
      "bytes": 219174240,
      "human_readable": "209.02 MB"
    },
    "trace_time": 2.64
  },
  {
    "encoder": "vgg11_bn",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 209.09,
      "bytes": 219243471,
      "human_readable": "209.09 MB"
    },
    "trace_time": 2.65
  },
  {
    "encoder": "vgg13",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 211.14,
      "bytes": 221394644,
      "human_readable": "211.14 MB"
    },
    "trace_time": 3.5
  },
  {
    "encoder": "vgg13_bn",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 211.21,
      "bytes": 221472347,
      "human_readable": "211.21 MB"
    },
    "trace_time": 3.28
  },
  {
    "encoder": "vgg16",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 271.9,
      "bytes": 285112060,
      "human_readable": "271.90 MB"
    },
    "trace_time": 3.48
  },
  {
    "encoder": "vgg16_bn",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 272.01,
      "bytes": 285219213,
      "human_readable": "272.01 MB"
    },
    "trace_time": 3.85
  },
  {
    "encoder": "vgg19",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 332.67,
      "bytes": 348829418,
      "human_readable": "332.67 MB"
    },
    "trace_time": 3.79
  },
  {
    "encoder": "vgg19_bn",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 332.8,
      "bytes": 348965759,
      "human_readable": "332.80 MB"
    },
    "trace_time": 4.09
  },
  {
    "encoder": "senet154",
    "success": false,
    "error": "SENet.__init__() got an unexpected keyword argument 'strides'",
    "model_size": {
      "mb": null,
      "bytes": null,
      "human_readable": null
    },
    "trace_time": null
  },
  {
    "encoder": "se_resnet50",
    "success": false,
    "error": "SENet.__init__() got an unexpected keyword argument 'strides'",
    "model_size": {
      "mb": null,
      "bytes": null,
      "human_readable": null
    },
    "trace_time": null
  },
  {
    "encoder": "se_resnet101",
    "success": false,
    "error": "SENet.__init__() got an unexpected keyword argument 'strides'",
    "model_size": {
      "mb": null,
      "bytes": null,
      "human_readable": null
    },
    "trace_time": null
  },
  {
    "encoder": "se_resnet152",
    "success": false,
    "error": "SENet.__init__() got an unexpected keyword argument 'strides'",
    "model_size": {
      "mb": null,
      "bytes": null,
      "human_readable": null
    },
    "trace_time": null
  },
  {
    "encoder": "se_resnext50_32x4d",
    "success": false,
    "error": "SENet.__init__() got an unexpected keyword argument 'strides'",
    "model_size": {
      "mb": null,
      "bytes": null,
      "human_readable": null
    },
    "trace_time": null
  },
  {
    "encoder": "se_resnext101_32x4d",
    "success": false,
    "error": "SENet.__init__() got an unexpected keyword argument 'strides'",
    "model_size": {
      "mb": null,
      "bytes": null,
      "human_readable": null
    },
    "trace_time": null
  },
  {
    "encoder": "densenet121",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 120.34,
      "bytes": 126182659,
      "human_readable": "120.34 MB"
    },
    "trace_time": 3.59
  },
  {
    "encoder": "densenet169",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 172.45,
      "bytes": 180821998,
      "human_readable": "172.45 MB"
    },
    "trace_time": 4.74
  },
  {
    "encoder": "densenet201",
    "success": true,
    "error": null,
    "model_size": {
      "mb": 219.09,
      "bytes": 229734702,
      "human_readable": "219.09 MB"
    },
    "trace_time": 5.4
  },
  {
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    "encoder": "efficientnet-b0",
    "success": false,
    "error": "\nCould not export Python function call 'SwishImplementation'. Remove calls to Python functions before export. Did you forget to add @script or @script_method annotation? If this is a nn.ModuleList, add it to __constants__:\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/autograd/function.py(575): apply\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(112): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(734): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(1088): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/base/model.py(48): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(15): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1278): trace_module\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(698): _trace_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1002): trace\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(51): test_encoder\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(101): main\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(131): <module>\n",
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    "encoder": "efficientnet-b1",
    "success": false,
    "error": "\nCould not export Python function call 'SwishImplementation'. Remove calls to Python functions before export. Did you forget to add @script or @script_method annotation? If this is a nn.ModuleList, add it to __constants__:\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/autograd/function.py(575): apply\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(112): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(734): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(1088): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/base/model.py(48): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(15): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1278): trace_module\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(698): _trace_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1002): trace\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(51): test_encoder\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(101): main\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(131): <module>\n",
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    "encoder": "efficientnet-b2",
    "success": false,
    "error": "\nCould not export Python function call 'SwishImplementation'. Remove calls to Python functions before export. Did you forget to add @script or @script_method annotation? If this is a nn.ModuleList, add it to __constants__:\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/autograd/function.py(575): apply\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(112): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(734): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(1088): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/base/model.py(48): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(15): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1278): trace_module\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(698): _trace_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1002): trace\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(51): test_encoder\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(101): main\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(131): <module>\n",
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    "encoder": "efficientnet-b3",
    "success": false,
    "error": "\nCould not export Python function call 'SwishImplementation'. Remove calls to Python functions before export. Did you forget to add @script or @script_method annotation? If this is a nn.ModuleList, add it to __constants__:\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/autograd/function.py(575): apply\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(112): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(734): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(1088): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/base/model.py(48): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(15): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1278): trace_module\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(698): _trace_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1002): trace\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(51): test_encoder\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(101): main\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(131): <module>\n",
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    "encoder": "efficientnet-b4",
    "success": false,
    "error": "\nCould not export Python function call 'SwishImplementation'. Remove calls to Python functions before export. Did you forget to add @script or @script_method annotation? If this is a nn.ModuleList, add it to __constants__:\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/autograd/function.py(575): apply\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(112): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(734): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/encoders/efficientnet.py(1088): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/segmentation_models_pytorch_3d/base/model.py(48): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(15): forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1726): _slow_forward\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1747): _call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/nn/modules/module.py(1736): _wrapped_call_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1278): trace_module\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(698): _trace_impl\n/home/vladimir/anaconda3/envs/czii_2024/lib/python3.12/site-packages/torch/jit/_trace.py(1002): trace\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(51): test_encoder\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(101): main\n/mnt/evo850/workspace/czii_2024/src/find_encoders.py(131): <module>\n",
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