Remove "NotImplemented" flags if the test is limited by hardware capacity

[xuzhao9]

When a test is flagged as "NotImplemented", there are actually two cases:

1. The test itself doesn't implement or handle the configs, e.g., unsupervised-learning models like pytorch_struct doesn't have eval() tests, or the pyhpc models don't have train() tests.
2. The test doesn't support running on our T4 CI GPU machine, but it runs totally fine on other GPUs, such as V100 or A100.

This PR is to eliminate the second case, so that the test can still run through run.py or run_sweep.py interfaces. Instead, we flag the test to be not_implemented in the metadata.yaml, and the CI script test.py or test_bench.py will read from the metadata and determine they are not suitable to run on the CI machine.

This fixes #688, #626, and #598

[facebook-github-bot]

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[aaronenyeshi]

LGTM. Thanks, this will keep the model code more clean!