renderer: add support for rendering high dimensional textures for classification/segmentation use cases

[d4l3k]

For 3D segmentation problems it's really useful to be able to train the models from multiple viewpoints using Pytorch3D as the renderer. Currently due to hardcoded assumptions in a few spots the mesh renderer only supports rendering RGB (3 dimensional) data. You can encode the classification information as 3 channel data but if you have more than 3 classes you're out of luck.

This relaxes the assumptions to make rendering semantic classes work with HardFlatShader and AmbientLights with no diffusion/specular. The other shaders/lights don't make any sense for classification since they mutate the texture values in some way.

This only requires changes in Materials and AmbientLights. The bulk of the code is the unit test.

Test plan:

Added unit test that renders a 5 dimensional texture and compare dimensions 2-5 to a stored picture.

[facebook-github-bot]

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