Core Compatibility Report: dazzling-spider/v0¤
| 🟡 | bioimageio format validation |
|---|---|
| status | valid-format |
| source | https://hypha.aicell.io/bioimage-io/artifacts/dazzling-spider/files/rdf.yaml?version=v0 |
| id | dazzling-spider |
| format version | model 0.5.6 |
| bioimageio.spec | 0.5.6.0 |
| Location | Details | |
|---|---|---|
| ✔️ | Successfully created `ModelDescr` instance. | |
| ✔️ | bioimageio.spec format validation model 0.5.6 | |
| ⚠ | 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 |
Reproduce test outputs from test inputs (pytorch_state_dict) |
| ❌ | weights.pytorch_state_dict |
No module named 'careamics' |
| See Traceback 1. | ||
weights.pytorch_state_dict |
recommended conda environment (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
%YAML 1.2
---
name: careamics
channels:
- conda-forge
- nodefaults
dependencies:
- conda-forge::bioimageio.core
- pip
- python=3.10
- pytorch=2.4.0
- torchvision=0.19.0
- pip:
- git+https://github.com/CAREamics/careamics.git
|
||
weights.pytorch_state_dict |
conda compare (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
//github.com/careamics/careamics.git not found |
Traceback 1
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/share/miniconda/envs/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/lib/p │
│ │
│ 781 │ │ test_input = get_test_input_sample(model) │
│ 782 │ │ expected = get_test_output_sample(model) │
│ 783 │ │ │
│ ❱ 784 │ │ with create_prediction_pipeline( │
│ 785 │ │ │ bioimageio_model=model, devices=devices, weight_format=weight_format │
│ 786 │ │ ) as prediction_pipeline: │
│ 787 │ │ │ results = prediction_pipeline.predict_sample_without_blocking(test_input) │
│ │
│ /usr/share/miniconda/envs/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/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/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/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/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/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/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/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/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/lib/p │
│ │
│ 100 │ load_state: bool = True, │
│ 101 │ devices: Optional[Sequence[Union[str, torch.device]]] = None, │
│ 102 ) -> nn.Module: │
│ ❱ 103 │ custom_callable = import_callable( │
│ 104 │ │ weight_spec.architecture, │
│ 105 │ │ sha256=( │
│ 106 │ │ │ weight_spec.architecture_sha256 │
│ │
│ /usr/share/miniconda/envs/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/lib/p │
│ │
│ 68 │ │ module = importlib.import_module(node.module_name) │
│ 69 │ │ c = getattr(module, str(node.callable_name)) │
│ 70 │ elif isinstance(node, ArchitectureFromLibraryDescr): │
│ ❱ 71 │ │ module = importlib.import_module(node.import_from) │
│ 72 │ │ c = getattr(module, str(node.callable)) │
│ 73 │ elif isinstance(node, CallableFromFile): │
│ 74 │ │ c = _import_from_file_impl(node.source_file, str(node.callable_name), **kwargs) │
│ │
│ /usr/share/miniconda/envs/3d5bf57e23beeafd6ea2183cfc86de256c11395f850f34909b53a65354a43210/lib/p │
│ │
│ 123 │ │ │ if character != '.': │
│ 124 │ │ │ │ break │
│ 125 │ │ │ level += 1 │
│ ❱ 126 │ return _bootstrap._gcd_import(name[level:], package, level) │
│ 127 │
│ 128 │
│ 129 _RELOADING = {} │
│ in _gcd_import:1050 │
│ in _find_and_load:1027 │
│ in _find_and_load_unlocked:992 │
│ in _call_with_frames_removed:241 │
│ in _gcd_import:1050 │
│ in _find_and_load:1027 │
│ in _find_and_load_unlocked:992 │
│ in _call_with_frames_removed:241 │
│ in _gcd_import:1050 │
│ in _find_and_load:1027 │
│ in _find_and_load_unlocked:1004 │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ModuleNotFoundError: No module named 'careamics'