| ✔️ |
bioimageio format validation |
| status |
passed |
| source |
https://hypha.aicell.io/bioimage-io/artifacts/organized-badger/files/rdf.yaml?version=v0 |
| id |
10.5281/zenodo.6028097/6028098 |
| format version |
model 0.4.10 |
| bioimageio.spec |
0.5.6.0 |
|
Location |
Details |
| ✔️ |
|
Successfully created `ModelDescr` instance. |
| ✔️ |
|
bioimageio.spec format validation model 0.4.10 |
| ⚠ |
weights.pytorch_state_dict.pytorch_version |
missing. Please specify the PyTorch version these PyTorch state dict weights were created with. |
| ⚠ |
weights.torchscript.pytorch_version |
missing. Please specify the PyTorch version these Torchscript weights were created with. |
| ❌ |
weights.pytorch_state_dict |
Reproduce test outputs from test inputs (pytorch_state_dict) |
| ❌ |
weights.pytorch_state_dict |
'unet_7f5b15948e8e2c91f78dcff34fbf30af517073e91ba487f3edb982b948d099b3' |
|
|
See Traceback 1. |
|
weights.pytorch_state_dict |
recommended conda environment (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
|
%YAML 1.2
---
channels:
- pytorch
- conda-forge
- nodefaults
dependencies:
- conda-forge::bioimageio.core
- mkl ==2024.0.0
- numpy <2
- pip
- pytorch==1.10.1
- setuptools <70.0.0
- torchaudio==0.10.1
- torchvision==0.11.2
|
|
weights.pytorch_state_dict |
conda compare (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
|
See Conda Environment Comparison 1. |
| ✔️ |
weights.torchscript |
Reproduce test outputs from test inputs (torchscript) |
|
weights.torchscript |
recommended conda environment (Reproduce test outputs from test inputs (torchscript)) |
|
|
%YAML 1.2
---
channels:
- pytorch
- conda-forge
- nodefaults
dependencies:
- conda-forge::bioimageio.core
- mkl ==2024.0.0
- numpy <2
- pip
- pytorch==1.10.1
- setuptools <70.0.0
- torchaudio==0.10.1
- torchvision==0.11.2
|
|
weights.torchscript |
conda compare (Reproduce test outputs from test inputs (torchscript)) |
|
|
See Conda Environment Comparison 1. |
Traceback 1
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/share/miniconda/envs/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/lib/p │
│ │
│ 108 │ module = sys.modules.get(module_name) │
│ 109 │ if module is None: │
│ 110 │ │ try: │
│ ❱ 111 │ │ │ tmp_dir = TemporaryDirectory(ignore_cleanup_errors=True) │
│ 112 │ │ │ module_path = Path(tmp_dir.name) / module_name │
│ 113 │ │ │ if reader.original_file_name.endswith(".zip") or is_zipfile(reader): │
│ 114 │ │ │ │ module_path.mkdir() │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
TypeError: __init__() got an unexpected keyword argument 'ignore_cleanup_errors'
During handling of the above exception, another exception occurred:
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/share/miniconda/envs/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/lib/p │
│ │
│ 642 │ │ inputs = get_test_inputs(model) │
│ 643 │ │ expected = get_test_outputs(model) │
│ 644 │ │ │
│ ❱ 645 │ │ with create_prediction_pipeline( │
│ 646 │ │ │ bioimageio_model=model, devices=devices, weight_format=weight_format │
│ 647 │ │ ) as prediction_pipeline: │
│ 648 │ │ │ results = prediction_pipeline.predict_sample_without_blocking(inputs) │
│ │
│ /usr/share/miniconda/envs/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/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/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/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/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/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/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/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/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/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/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/lib/p │
│ │
│ 72 │ │ module = importlib.import_module(node.import_from) │
│ 73 │ │ c = getattr(module, str(node.callable)) │
│ 74 │ elif isinstance(node, CallableFromFile): │
│ ❱ 75 │ │ c = _import_from_file_impl(node.source_file, str(node.callable_name), **kwargs) │
│ 76 │ elif isinstance(node, ArchitectureFromFileDescr): │
│ 77 │ │ c = _import_from_file_impl(node.source, str(node.callable), sha256=node.sha256) │
│ 78 │ else: │
│ │
│ /usr/share/miniconda/envs/6957a898500e9707d2a72c887d10fb220eba92e15c14aaeeddbbc322dd3dedb8/lib/p │
│ │
│ 132 │ │ │ importlib_spec.loader.exec_module(module) │
│ 133 │ │ │
│ 134 │ │ except Exception as e: │
│ ❱ 135 │ │ │ del sys.modules[module_name] │
│ 136 │ │ │ raise ImportError(f"Failed to import {source}") from e │
│ 137 │ │
│ 138 │ try: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
KeyError: 'unet_7f5b15948e8e2c91f78dcff34fbf30af517073e91ba487f3edb982b948d099b3'
Conda Environment Comparison 1
usage: conda [-h] [-v] [--no-plugins] [-V] COMMAND ... conda is a tool for managing and
deploying applications, environments and packages. options: -h, --help Show this
help message and exit. -v, --verbose Can be used multiple times. Once for detailed
output, twice for INFO logging, thrice for DEBUG logging, four
times for TRACE logging. --no-plugins Disable all plugins that are not built into
conda. -V, --version Show the conda version number and exit. commands: The
following built-in and plugins subcommands are available. COMMAND activate
Activate a conda environment. clean Remove unused packages and caches.
commands List all available conda subcommands (including those
from plugins). Generally only used by tab-completion. compare Compare packages
between conda environments. config Modify configuration values in .condarc.
content-trust Signing and verification tools for Conda create Create a
new conda environment from a list of specified packages. deactivate
Deactivate the current active conda environment. doctor Display a health report
for your environment. env Create and manage conda environments. export
Export a given environment info Display information about current conda
install. init Initialize conda for shell interaction. install
Install a list of packages into a specified conda environment. list
List installed packages in a conda environment. notices Retrieve latest channel
notifications. package Create low-level conda packages. (EXPERIMENTAL)
remove (uninstall) Remove a list of packages from a specified conda
environment. rename Rename an existing environment. repoquery
Advanced search for repodata. run Run an executable in a conda environment.
search Search for packages and display associated information
using the MatchSpec format. token Set repository access token and configure
default_channels tos A subcommand for viewing, accepting, rejecting, and
otherwise interacting with a channel's Terms of Service (ToS). This
plugin periodically checks for updated Terms of Service for the
active/selected channels. Channels with a Terms of Service will need
to be accepted or rejected prior to use. Conda will only allow package
installation from channels without a Terms of Service or with an
accepted Terms of Service. Attempting to use a channel with a rejected
Terms of Service will result in an error. update (upgrade) Update conda packages to the
latest compatible version.