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brain-score.org submission (user:413) | (public:False) #1075

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Nov 15, 2024
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12 changes: 12 additions & 0 deletions brainscore_vision/models/yudixie_resnet18_240719_6/__init__.py
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from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers


def commit_model(identifier):
return ModelCommitment(identifier=identifier,
activations_model=get_model(identifier),
layers=get_layers(identifier))

model_registry['yudixie_resnet18_distance_translation_rotation_0_240719'] = lambda: commit_model('yudixie_resnet18_distance_translation_rotation_0_240719')

60 changes: 60 additions & 0 deletions brainscore_vision/models/yudixie_resnet18_240719_6/model.py
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import os
from pathlib import Path
import functools
from urllib.request import urlretrieve

import numpy as np
import torch
import torch.nn as nn
from torchvision.models import resnet18

from brainscore_vision.model_helpers.check_submission import check_models
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper, load_preprocess_images


# Please load your pytorch model for usage in CPU. There won't be GPUs available for scoring your model.
# If the model requires a GPU, contact the brain-score team directly.


def get_model(name):
pytorch_device = torch.device('cpu')

weigth_url = f'https://yudi-brainscore-models.s3.amazonaws.com/{name}.pth'
fh = urlretrieve(weigth_url, f'{name}_weights.pth')
load_path = fh[0]

pytorch_model = resnet18()
pytorch_model.fc = nn.Linear(pytorch_model.fc.in_features, 674)
pytorch_model = pytorch_model.to(pytorch_device)

# load model from saved weights
saved_state_dict = torch.load(load_path, map_location=pytorch_device)
state_dict = {}
for k, v in saved_state_dict.items():
if k.startswith('_orig_mod.'):
# for compiled models
state_dict[k[10:]] = v
else:
state_dict[k] = v
pytorch_model.load_state_dict(state_dict, strict=True)
print(f'Loaded model from {load_path}')

preprocessing = functools.partial(load_preprocess_images, image_size=224)
wrapper = PytorchWrapper(identifier=name,
model=pytorch_model,
preprocessing=preprocessing)
wrapper.image_size = 224
return wrapper


def get_layers(name):
return ['conv1','layer1', 'layer2', 'layer3', 'layer4', 'fc']


def get_bibtex(model_identifier):
return """xx"""


if __name__ == '__main__':
check_models.check_base_models(__name__)
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{
"V1": "layer1",
"V2": "layer2",
"V4": "layer1",
"IT": "layer3"
}
25 changes: 25 additions & 0 deletions brainscore_vision/models/yudixie_resnet18_240719_6/setup.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-

from setuptools import setup, find_packages

requirements = [ "torchvision",
"torch"
]

setup(
packages=find_packages(exclude=['tests']),
include_package_data=True,
install_requires=requirements,
license="MIT license",
zip_safe=False,
keywords='brain-score template',
classifiers=[
'Development Status :: 2 - Pre-Alpha',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Natural Language :: English',
'Programming Language :: Python :: 3.7',
],
test_suite='tests',
)
1 change: 1 addition & 0 deletions brainscore_vision/models/yudixie_resnet18_240719_6/test.py
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# Left empty as part of 2023 models migration
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