Base for places365

[Amapocho]

Added necessary links and categories as a starting point for places365 #5347

[facebook-github-bot]

💊 CI failures summary and remediations

As of commit cc2aa8c (more details on the Dr. CI page):

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• 1/2 failures introduced in this PR
• 1/2 broken upstream at merge base 97eddc5 since Feb 04

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🕵️ 1 new failure recognized by patterns

The following CI failures do not appear to be due to upstream breakages:

unittest_prototype (1/1)

Step: "Run tests" (full log | diagnosis details | 🔁 rerun)

/home/circleci/project/test/test_prototype_feat...ead to errors or silently give incorrect results).

test/test_prototype_utils.py::test_sequence_to_str[seq5-and -'foo', 'bar', and 'baz'] �[32mPASSED�[0m�[31m [100%]�[0m

=================================== FAILURES ===================================
�[31m�[1m________________________________ test_coverage _________________________________�[0m
Traceback (most recent call last):
  File "/home/circleci/project/test/test_prototype_builtin_datasets.py", line 24, in test_coverage
    f"The dataset(s) {sequence_to_str(sorted(untested_datasets), separate_last='and ')} "
AssertionError: The dataset(s) 'places365' are exposed through `torchvision.prototype.datasets.load()`, but are not tested. Please add mock data to `test/builtin_dataset_mocks.py`.
�[33m=============================== warnings summary ===============================�[0m
test/test_prototype_features.py::TestJit::test_bounding_box
  /home/circleci/project/test/test_prototype_features.py:150: TracerWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won't change the number of iterations executed (and might lead to errors or silently give incorrect results).
    new_height, new_width = size

test/test_prototype_features.py::TestJit::test_bounding_box
  /home/circleci/project/torchvision/prototype/features/_feature.py:78: TracerWarning: torch.as_tensor results are registered as constants in the trace. You can safely ignore this warning if you use this function to create tensors out of constant variables that would be the same every time you call this function. In any other case, this might cause the trace to be incorrect.
    return torch.as_tensor(data, dtype=dtype, device=device)

test/test_prototype_features.py::TestJit::test_bounding_box
  /home/circleci/project/test/test_prototype_features.py:164: TracerWarning: Converting a tensor to a Python list might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
    new_x1, new_y1, new_x2, new_y2, like=input, format="xyxy", image_size=tuple(size.tolist())

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🚧 1 ongoing upstream failure:

These were probably caused by upstream breakages that are not fixed yet.

• binary_win_wheel_py3.9_cu115 since Feb 04 (22f8dc4)
  • 🔁 rerun

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[pmeier]

@Amapocho thanks a lot for the PR so other might use it as base for their work. I've added a cleanup commit that might also be beneficial for you to look at.

[pmeier]

Superseded by #5679.