fix(qwenimage): Add padding for context parallelism

[Ratish1]

What does this PR do?

This PR fixes a bug that causes the QwenImage model to crash when using context parallelism with a prompt whose sequence length is not divisible by the world size.

The fix is implemented within the QwenImageTransformer2DModel and consists of three parts:

1. Input Padding: The text prompt embeddings (encoder_hidden_states) and their attention mask are padded at the
   start of the forward method to ensure their length is divisible by the world size.
2. RoPE Correction: The model is updated to use the new, padded sequence length to generate the rotary positional
   embeddings (RoPE), preventing a tensor shape mismatch that was causing a RuntimeError.
3. Attention Masking: The QwenDoubleStreamAttnProcessor2_0 is corrected to build and use a proper additive attention mask. This ensures the new padded tokens are correctly ignored by the attention mechanism, preserving the numerical output of the model.

A new unit test is also added to simulate a distributed environment. It verifies that the padding logic prevents the crash while ensuring the output is numerically equivalent to the baseline, non-padded run.

Fixes #12568

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