feat: add COSMOS 2.5 DiT implementation

[KyleShao1016]

Implement NVIDIA's COSMOS 2.5 Diffusion Transformer (DiT) architecture in FastVideo with verified numerical accuracy against the official cosmos-predict2.5 reference.

Key changes:

1. Model Architecture (fastvideo/models/dits/cosmos2_5.py):

   • Implement Cosmos25Transformer3DModel with 28 transformer blocks
   • Add AdaLN-LoRA conditioning with proper modulation parameter computation
   • Implement 3D RoPE with NTK-aware extrapolation for spatiotemporal encoding
   • Add QK normalization using RMSNorm for improved training stability
   • Support optional cross-attention projection for high-dimensional embeddings (Qwen 7B)
   • Add learnable positional embeddings as optional feature
   • Implement proper patch embedding/unpatchification for video processing

2. Configuration (fastvideo/configs/models/dits/cosmos2_5.py):

   • Add Cosmos25ArchConfig with complete parameter mapping for checkpoint loading
   • Map official checkpoint structure (net.blocks.) to FastVideo structure (transformer_blocks.)
   • Support AdaLN modulation layers at block level (adaln_modulation_self_attn/cross_attn/mlp)
   • Configure cross-attention projection for 100,352-dim Qwen embeddings
   • Add LoRA parameter mappings for fine-tuning support

3. Tests (fastvideo/tests/transformers/test_cosmos2_5.py):

   • Add comprehensive parity test against official MinimalV1LVGDiT reference
   • Test both single-frame (image) and multi-frame (video) generation
   • Verify checkpoint loading and weight consistency
   • Achieve 0.173% relative difference in bfloat16 (excellent parity)
   • Test video2world conditioning with condition masks

4. Registry (fastvideo/configs/models/dits/init.py):

   • Register Cosmos25VideoConfig for model instantiation

Test Results:

• Max difference: 0.046875
• Mean difference: 0.001869
• Relative difference: 0.173% (excellent parity in bfloat16)

[gemini-code-assist[bot]]

Summary of Changes

Hello @KyleShao1016, I'm Gemini Code Assist[^1]! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request integrates NVIDIA's COSMOS 2.5 Diffusion Transformer architecture into the FastVideo framework. The implementation includes key architectural components like AdaLN-LoRA conditioning, 3D Rotary Positional Embeddings, and QK normalization, along with a robust configuration for checkpoint compatibility. Extensive testing confirms high numerical accuracy against the official reference, ensuring reliable video generation capabilities.

Highlights

• COSMOS 2.5 DiT Implementation: Added the NVIDIA COSMOS 2.5 Diffusion Transformer (DiT) architecture to FastVideo, enabling advanced video generation capabilities.
• Numerical Accuracy Verified: Achieved excellent numerical accuracy, with a 0.173% relative difference in bfloat16, against the official COSMOS 2.5 reference implementation.
• Advanced Architectural Features: Implemented key features including 28 transformer blocks, AdaLN-LoRA conditioning, 3D Rotary Positional Embeddings (RoPE) with NTK-aware extrapolation, QK normalization, and optional cross-attention projection for high-dimensional embeddings (e.g., Qwen 7B).
• Comprehensive Configuration and Checkpoint Loading: Introduced Cosmos25ArchConfig with detailed parameter mappings to ensure seamless loading of official COSMOS 2.5 checkpoints and support for LoRA fine-tuning.
• Robust Testing Suite: Included extensive parity tests covering both single-frame (image) and multi-frame (video) generation, checkpoint loading, and video2world conditioning with condition masks.

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[SolitaryThinker]

also please run pre-commit and fix lint