Core Compatibility Report: resourceful-lizard/v0¤
| 🟡 | bioimageio format validation |
|---|---|
| status | valid-format |
| source | https://hypha.aicell.io/bioimage-io/artifacts/resourceful-lizard/files/rdf.yaml?version=v0 |
| id | resourceful-lizard |
| version | 0.1.1 |
| applied format | model 0.5.9 |
| bioimageio.spec | 0.5.9.1 |
| Location | Details | |
|---|---|---|
| ✔️ | Successfully created `ModelDescr` instance. | |
| ✔️ | bioimageio.spec format validation model 0.5.9 | |
| ⚠ | documentation |
No '# Validation' (sub)section found in doc.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 'a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e' |
| ❌ | weights.pytorch_state_dict |
Reproduce test outputs from test inputs (pytorch_state_dict) |
| ❌ | weights.pytorch_state_dict |
/usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/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)) |
|
| See Recommended Conda Environment 1. | ||
weights.pytorch_state_dict |
conda compare (Reproduce test outputs from test inputs (pytorch_state_dict)) |
|
//github.com/facebookresearch/segment-anything.git not found |
||
| ❌ | weights.pytorch_state_dict |
Run pytorch_state_dict inference for parametrized inputs |
| ❌ | weights.pytorch_state_dict |
/usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_NotifyEvent |
| See Traceback 2. |
Traceback 1
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 877 │ │ test_input = get_test_input_sample(model) │
│ 878 │ │ expected = get_test_output_sample(model) │
│ 879 │ │ │
│ ❱ 880 │ │ with create_prediction_pipeline( │
│ 881 │ │ │ bioimageio_model=model, devices=devices, weight_format=weight_format │
│ 882 │ │ ) as prediction_pipeline: │
│ 883 │ │ │ prediction_pipeline.apply_preprocessing(test_input) │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 404 │ │ │ f"deprecated create_prediction_pipeline kwargs: {set(deprecated_kwargs)}" │
│ 405 │ │ ) │
│ 406 │ │
│ ❱ 407 │ model_adapter = model_adapter or create_model_adapter( │
│ 408 │ │ model_description=bioimageio_model, │
│ 409 │ │ devices=devices, │
│ 410 │ │ weight_format_priority_order=weights_format and (weights_format,), │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 182 │ │ assert errors │
│ 183 │ │ if len(weight_format_priority_order) == 1: │
│ 184 │ │ │ assert len(errors) == 1 │
│ ❱ 185 │ │ │ raise errors[0] │
│ 186 │ │ │
│ 187 │ │ else: │
│ 188 │ │ │ msg = ( │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 110 │ │ │ if wf == "pytorch_state_dict": │
│ 111 │ │ │ │ assert weights.pytorch_state_dict is not None │
│ 112 │ │ │ │ try: │
│ ❱ 113 │ │ │ │ │ from .pytorch_backend import PytorchModelAdapter │
│ 114 │ │ │ │ │ │
│ 115 │ │ │ │ │ return PytorchModelAdapter( │
│ 116 │ │ │ │ │ │ model_description=model_description, devices=devices │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/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/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 364 │ # See Note [Global dependencies] │
│ 365 │ if USE_GLOBAL_DEPS: │
│ 366 │ │ _load_global_deps() │
│ ❱ 367 │ from torch._C import * # noqa: F403 │
│ 368 │
│ 369 │
│ 370 class SymInt: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ImportError: /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_NotifyEvent
Recommended Conda Environment 1
%YAML 1.2
---
name: sam-encoder
channels:
- pytorch
- nvidia
- anaconda
- conda-forge
- nodefaults
dependencies:
- bioimageio.core
- cuda=11.8
- pip
- python=3.10
- pytorch
- setuptools
- torchvision
- pip:
- fsspec
- git+https://github.com/facebookresearch/segment-anything.git
- huggingface-hub
- matplotlib
- packaging
- safetensors
- timm
- tqdm
Traceback 2
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 1120 │ try: │
│ 1121 │ │ test_input = get_test_input_sample(model) │
│ 1122 │ │ │
│ ❱ 1123 │ │ with create_prediction_pipeline( │
│ 1124 │ │ │ bioimageio_model=model, devices=devices, weight_format=weight_format │
│ 1125 │ │ ) as prediction_pipeline: │
│ 1126 │ │ │ for n, batch_size, inputs, exptected_output_shape in generate_test_cases(): │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 404 │ │ │ f"deprecated create_prediction_pipeline kwargs: {set(deprecated_kwargs)}" │
│ 405 │ │ ) │
│ 406 │ │
│ ❱ 407 │ model_adapter = model_adapter or create_model_adapter( │
│ 408 │ │ model_description=bioimageio_model, │
│ 409 │ │ devices=devices, │
│ 410 │ │ weight_format_priority_order=weights_format and (weights_format,), │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 182 │ │ assert errors │
│ 183 │ │ if len(weight_format_priority_order) == 1: │
│ 184 │ │ │ assert len(errors) == 1 │
│ ❱ 185 │ │ │ raise errors[0] │
│ 186 │ │ │
│ 187 │ │ else: │
│ 188 │ │ │ msg = ( │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 110 │ │ │ if wf == "pytorch_state_dict": │
│ 111 │ │ │ │ assert weights.pytorch_state_dict is not None │
│ 112 │ │ │ │ try: │
│ ❱ 113 │ │ │ │ │ from .pytorch_backend import PytorchModelAdapter │
│ 114 │ │ │ │ │ │
│ 115 │ │ │ │ │ return PytorchModelAdapter( │
│ 116 │ │ │ │ │ │ model_description=model_description, devices=devices │
│ │
│ /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/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/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/p │
│ │
│ 364 │ # See Note [Global dependencies] │
│ 365 │ if USE_GLOBAL_DEPS: │
│ 366 │ │ _load_global_deps() │
│ ❱ 367 │ from torch._C import * # noqa: F403 │
│ 368 │
│ 369 │
│ 370 class SymInt: │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ImportError: /usr/share/miniconda/envs/a5da52dafabdde7cdd7c07143428e76b22eb95ad536a51113bc0628f90346b5e/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so: undefined symbol: iJIT_NotifyEvent