Made label data optional for inference and adopted other required changes

[laxmareddyp]

Adapted the architecture preprocessor to conform with the current code guidelines and typical model interface.

• removed call from SegFormerImageSegmenterPreprocessor, perform transformations in the image converter instead
• adapted convert_segformer_checkpoints.py accordingly

These are the points/bugs changed in segformer_image_segmenter_tests.py:

• MiTBackbone parameter names were wrong (had not been adapted for [MiT and SegFormer] Refactor Backbone Arg Names #1958)
• Added label data in train_data for self.run_task_test
• expected_output_shape in test_task was wrong
• use self.assertAllEqual instead of plain assert
• a valid preprocessor needs to be used for self.run_task_test to succeed
• fixed a wrong input shape in test_segformer_call

[sachinprasadhs]

LGTM

[mattdangerw]

This looks great to me, but does this mean we need new segformer presets? If so, let's update the preset on this PR as well.

[laxmareddyp]

This looks great to me, but does this mean we need new segformer presets? If so, let's update the preset on this PR as well.

Yes, we need to generate new set of presets for these changes to be included. I will update the presets on this PR soon. Thanks