Core Compatibility Report: patient-swan/v0¤
| 🟡 | bioimageio format validation |
|---|---|
| status | valid-format |
| source | https://hypha.aicell.io/bioimage-io/artifacts/patient-swan/files/rdf.yaml?version=v0 |
| id | patient-swan |
| version | 1.0.7 |
| applied format | model 0.5.7 |
| bioimageio.spec | 0.5.7.4 |
| Location | Details | |
|---|---|---|
| ✔️ | Successfully created `ModelDescr` instance. | |
| ✔️ | bioimageio.spec format validation model 0.5.7 | |
| ⚠ | documentation |
No '# Validation' (sub)section found in README.md. |
| ⚠ | inputs.0.sample_tensor |
Needs to be filled for FAIR compliance |
| ⚠ | outputs.0.sample_tensor |
Needs to be filled for FAIR compliance |
| ✔️ | weights.pytorch_state_dict |
Created conda environment '03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520' |
| ❌ | weights.pytorch_state_dict |
Reproduce test outputs from test inputs (pytorch_state_dict) |
| ❌ | weights.pytorch_state_dict |
EOF when reading a line |
| See Traceback 1. | ||
weights.pytorch_state_dict |
recommended conda environment (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
| See Recommended Conda Environment 1. | ||
weights.pytorch_state_dict |
conda compare (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
Success. All the packages in the specification file are present in the environment with matching version and build string. |
Traceback 1
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 832 │ │ test_input = get_test_input_sample(model) │
│ 833 │ │ expected = get_test_output_sample(model) │
│ 834 │ │ │
│ ❱ 835 │ │ with create_prediction_pipeline( │
│ 836 │ │ │ bioimageio_model=model, devices=devices, weight_format=weight_format │
│ 837 │ │ ) as prediction_pipeline: │
│ 838 │ │ │ results = prediction_pipeline.predict_sample_without_blocking(test_input) │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 368 │ │ │ f"deprecated create_prediction_pipeline kwargs: {set(deprecated_kwargs)}" │
│ 369 │ │ ) │
│ 370 │ │
│ ❱ 371 │ model_adapter = model_adapter or create_model_adapter( │
│ 372 │ │ model_description=bioimageio_model, │
│ 373 │ │ devices=devices, │
│ 374 │ │ weight_format_priority_order=weights_format and (weights_format,), │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 166 │ │ assert errors │
│ 167 │ │ if len(weight_format_priority_order) == 1: │
│ 168 │ │ │ assert len(errors) == 1 │
│ ❱ 169 │ │ │ raise errors[0] │
│ 170 │ │ │
│ 171 │ │ else: │
│ 172 │ │ │ msg = ( │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 109 │ │ │ │ try: │
│ 110 │ │ │ │ │ from .pytorch_backend import PytorchModelAdapter │
│ 111 │ │ │ │ │ │
│ ❱ 112 │ │ │ │ │ return PytorchModelAdapter( │
│ 113 │ │ │ │ │ │ model_description=model_description, devices=devices │
│ 114 │ │ │ │ │ ) │
│ 115 │ │ │ │ except Exception as e: │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 35 │ │ │ raise ValueError("No `pytorch_state_dict` weights found") │
│ 36 │ │ │
│ 37 │ │ devices = get_devices(devices) │
│ ❱ 38 │ │ self._model = load_torch_model(weights, load_state=True, devices=devices) │
│ 39 │ │ if mode == "eval": │
│ 40 │ │ │ self._model = self._model.eval() │
│ 41 │ │ elif mode == "train": │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 113 │ │ if isinstance(weight_spec, v0_4.PytorchStateDictWeightsDescr) │
│ 114 │ │ else weight_spec.architecture.kwargs │
│ 115 │ ) │
│ ❱ 116 │ torch_model = custom_callable(**model_kwargs) │
│ 117 │ │
│ 118 │ if not isinstance(torch_model, nn.Module): │
│ 119 │ │ if isinstance( │
│ │
│ /tmp/tmp8ouxiad4/model_6f309b7a1b5616f8d4f85ab291ae0ea960e1841b44b960099da0bf706e703791.py:132 i │
│ │
│ 129 │ │ │
│ 130 │ │ self.init_inference_params() │
│ 131 │ │ │
│ ❱ 132 │ │ modules = install_and_import_modules() │
│ 133 │ │ transform, Data, Operation, NDModel, Models, models = modules │
│ 134 │ │ self.transform = transform │
│ 135 │ │ self.Data = Data │
│ │
│ /tmp/tmp8ouxiad4/model_6f309b7a1b5616f8d4f85ab291ae0ea960e1841b44b960099da0bf706e703791.py:19 in │
│ │
│ 16 from spotmax.nnet import install_and_download, config_yaml_path │
│ 17 │
│ 18 def install_and_import_modules(): │
│ ❱ 19 │ install_and_download() │
│ 20 │ from spotmax.nnet import transform │
│ 21 │ from spotmax.nnet.models.nd_model import ( │
│ 22 │ │ Data, Operation, NDModel, Models, models │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 10 from spotmax import is_cli, printl, io │
│ 11 │
│ 12 def install_and_download(): │
│ ❱ 13 │ check_install_torch(is_cli=is_cli, caller_name='SpotMAX') │
│ 14 │ │
│ 15 │ check_install_package( │
│ 16 │ │ 'pytorch3dunet', │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 3179 │ │ traceback.print_exc() │
│ 3180 │ │
│ 3181 │ if is_cli: │
│ ❱ 3182 │ │ _install_pytorch_cli(caller_name=caller_name) │
│ 3183 │ │ return │
│ 3184 │ │
│ 3185 │ win = apps.InstallPyTorchDialog(parent=qparent, caller_name=caller_name) │
│ │
│ /usr/share/miniconda/envs/03b5713dcd136d8c1b2a3baa3e4b1fe1a03557d39771c8b7d99e878a25924520/lib/p │
│ │
│ 3495 │ for question, choices in questions.items(): │
│ 3496 │ │ input_txt = get_cli_multi_choice_question(question, choices) │
│ 3497 │ │ while True: │
│ ❱ 3498 │ │ │ answer = input(input_txt) │
│ 3499 │ │ │ if answer.lower() == 'q': │
│ 3500 │ │ │ │ exit('Execution stopped by the user.') │
│ 3501 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
EOFError: EOF when reading a line
Recommended Conda Environment 1
%YAML 1.2
---
name: spotmax_biio
channels:
- conda-forge
- fastai
- nodefaults
dependencies:
- conda-forge::bioimageio.core>=0.9.4
- pip
- python=3.11
- pip:
- cellacdc
- opencv-python-headless
- pytorch3dunet-spotmax
- pyyaml
- spotmax
- torch