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Core Compatibility Report: diplomatic-bug/v0¤

🟡 bioimageio format validation
status valid-format
source https://hypha.aicell.io/bioimage-io/artifacts/diplomatic-bug/files/rdf.yaml?version=v0
id diplomatic-bug
version 1
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
⚠ inputs.0.sample_tensor 
Needs to be filled for FAIR compliance
⚠ inputs.1.sample_tensor 
Needs to be filled for FAIR compliance
⚠ inputs.2.sample_tensor 
Needs to be filled for FAIR compliance
⚠ inputs.3.sample_tensor 
Needs to be filled for FAIR compliance
⚠ inputs.4.sample_tensor 
Needs to be filled for FAIR compliance
⚠ inputs.5.sample_tensor 
Needs to be filled for FAIR compliance
⚠ outputs.0.sample_tensor 
Needs to be filled for FAIR compliance
⚠ outputs.1.sample_tensor 
Needs to be filled for FAIR compliance
⚠ outputs.2.sample_tensor 
Needs to be filled for FAIR compliance
✔️ weights.pytorch_state_dict Found existing conda environment '08f8ffa27c39c9aa97fede9155e0b8428e8e934a25bbb625c5d1dd8c912d76f5'
✔️ weights.pytorch_state_dict Reproduce test outputs from test inputs (pytorch_state_dict)
weights.pytorch_state_dict 
recommended conda environment (Reproduce test outputs from test inputs (pytorch_state_dict))
 
%YAML 1.2
---
name: sam
channels:
  - pytorch
  - conda-forge
  - nodefaults
dependencies:
  - conda-forge::bioimageio.core>=0.9.4
  - pip
  - segment-anything
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.pytorch_state_dict Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n: 0
✔️ weights.pytorch_state_dict Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n: 1
✔️ weights.pytorch_state_dict Run pytorch_state_dict inference for inputs with batch_size: 1 and size parameter n: 2
❌ weights.pytorch_state_dict Run pytorch_state_dict inference for inputs with batch_size: 2 and size parameter n: 0
❌ weights.pytorch_state_dict