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Core Compatibility Report: shivering-raccoon/v0¤

✔️ bioimageio format validation
status passed
source https://hypha.aicell.io/bioimage-io/artifacts/shivering-raccoon/files/rdf.yaml?version=v0
id 10.5281/zenodo.6406803/6406804
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.dependencies
Custom dependencies (conda:environment.yaml) specified. Avoid this whenever possible to allow execution in a wider range of software environments.
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
/usr/share/miniconda/envs/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_NotifyEvent
See Traceback 1.
weights.pytorch_state_dict
recommended conda environment (Reproduce test outputs from test inputs (pytorch_state_dict))
%YAML 1.2
---
name: torch-em-deploy
channels:
  - pytorch
  - conda-forge
  - nodefaults
dependencies:
  - conda-forge::bioimageio.core
  - pip
  - pytorch>=1.6,<2.0
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.
✔️ 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/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/lib/p 
                                                                                                  
    774 │   │   test_input = get_test_input_sample(model)                                         
    775 │   │   expected = get_test_output_sample(model)                                          
    776 │   │                                                                                     
  777 │   │   with create_prediction_pipeline(                                                  
    778 │   │   │   bioimageio_model=model, devices=devices, weight_format=weight_format          
    779 │   │   ) as prediction_pipeline:                                                         
    780 │   │   │   results = prediction_pipeline.predict_sample_without_blocking(test_input)     
                                                                                                  
 /usr/share/miniconda/envs/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/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/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/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/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/lib/p 
                                                                                                  
   107 │   │   │   if wf == "pytorch_state_dict":                                                 
   108 │   │   │   │   assert weights.pytorch_state_dict is not None                              
   109 │   │   │   │   try:                                                                       
 110 │   │   │   │   │   from .pytorch_backend import PytorchModelAdapter                       
   111 │   │   │   │   │                                                                          
   112 │   │   │   │   │   return PytorchModelAdapter(                                            
   113 │   │   │   │   │   │   model_description=model_description, devices=devices               
                                                                                                  
 /usr/share/miniconda/envs/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/lib/p 
                                                                                                  
     5 from pathlib import Path                                                                   
     6 from typing import Any, List, Literal, Optional, Sequence, Union                           
     7                                                                                            
   8 import torch                                                                               
     9 from loguru import logger                                                                  
    10 from numpy.typing import NDArray                                                           
    11 from torch import nn                                                                       
                                                                                                  
 /usr/share/miniconda/envs/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/lib/p 
                                                                                                  
   215 # See Note [Global dependencies]                                                       
   216 if USE_GLOBAL_DEPS:                                                                    
   217 │   │   _load_global_deps()                                                                
 218 from torch._C import *  # noqa: F403                                                   
   219                                                                                            
   220 # Appease the type checker; ordinarily this binding is inserted by the                     
   221 # torch._C module initialization code in C                                                 
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ImportError: /usr/share/miniconda/envs/96189b829af48e5ff48931e2aad6d1ff4eafea247b62c8a70dc5ba4e3f69fc2b/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_NotifyEvent

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.