Fix edge case issue in uniform_temporal_sampling

[yassersouri]

Motivation and Context

Current behavior of the uniform_temporal_sampling function has an undesirable property when dealing with smaller than num_samples input.

For example:

uniform_temporal_subsample(torch.arange(4), num_samples=4, temporal_dim=0)
# tensor([0, 1, 2, 3])  (looks good)

uniform_temporal_subsample(torch.arange(4), num_samples=5, temporal_dim=0)
# tensor([0, 0, 1, 2, 3]) (looks good)

uniform_temporal_subsample(torch.arange(4), num_samples=6, temporal_dim=0)
# tensor([0, 0, 1, 1, 2, 3]) (looks good)

uniform_temporal_subsample(torch.arange(4), num_samples=7, temporal_dim=0)
# tensor([0, 0, 1, 1, 2, 2, 3]) (looks good)

uniform_temporal_subsample(torch.arange(4), num_samples=8, temporal_dim=0)
# tensor([0, 0, 0, 1, 1, 2, 2, 3]) (ISSUE: should be [0, 0, 1, 1, 2, 2, 3, 3])

uniform_temporal_subsample(torch.arange(4), num_samples=9, temporal_dim=0)
# tensor([0, 0, 0, 1, 1, 1, 2, 2, 3])  (ISSUE: should be [0, 0, 0, 1, 1, 2, 2, 3, 3])

How Has This Been Tested

I have tested the implementation myself, but I have not created a test for it.

Types of changes

• Docs change / refactoring / dependency upgrade
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)

Checklist

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.
• I have read the CONTRIBUTING document.
• I have completed my CLA (see CONTRIBUTING)
• I have added tests to cover my changes.
• All new and existing tests passed.

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