add r50_tvpt to models (#584)

Co-authored-by: AutoJenkins <[email protected]>

brainscore_vision/models/r50_tvpt/__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
+
+model_registry["r50_tvpt"] = lambda: ModelCommitment(
+    identifier="r50_tvpt",
+    activations_model=get_model("r50_tvpt"),
+    layers=get_layers("r50_tvpt"),
+)

brainscore_vision/models/r50_tvpt/model.py

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+from brainscore_vision.model_helpers.check_submission import check_models
+import functools
+import os
+from urllib.request import urlretrieve
+import torchvision.models
+from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
+from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
+from pathlib import Path
+from brainscore_vision.model_helpers import download_weights
+import torch
+
+# This is an example implementation for submitting resnet-50 as a pytorch model
+
+# Attention: It is important, that the wrapper identifier is unique per model!
+# The results will otherwise be the same due to brain-scores internal result caching mechanism.
+# 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.
+from brainscore_vision.model_helpers.check_submission import check_models
+
+
+def get_model_list():
+    return ["r50_tvpt"]
+
+
+def get_model(name):
+    assert name == "r50_tvpt"
+    model = torchvision.models.resnet50(pretrained=True)
+    preprocessing = functools.partial(load_preprocess_images, image_size=224)
+    wrapper = PytorchWrapper(
+        identifier="resnet50", model=model, preprocessing=preprocessing
+    )
+    wrapper.image_size = 224
+    return wrapper
+
+
+def get_layers(name):
+    assert name == "r50_tvpt"
+    outs = ["conv1", "layer1", "layer2", "layer3", "layer4"]
+    return outs
+
+
+def get_bibtex(model_identifier):
+    return """xx"""
+
+
+if __name__ == "__main__":
+    check_models.check_base_models(__name__)

brainscore_vision/models/r50_tvpt/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',
+)

brainscore_vision/models/r50_tvpt/test.py

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+# Left empty as part of 2023 models migration