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ROCm 7.2 + PyTorch 2.11.0 has a bug where PyTorch passes workspace=0 to MIOpen convolutions, forcing fallback to the slow GemmFwdRest solver. This caused s3gen.inference to take 15-22s instead of <5s, making synthesis 3-4x slower than real-time audio playback. ROCm 6.1 allocates workspace correctly so MIOpen picks fast GEMM solvers without needing torch.compile workarounds. Changes: - Base image: rocm/dev-ubuntu-22.04:7.2 → 6.1 - torch 2.11.0 → 2.5.1 (rocm6.1 wheel index) - Add pytorch_triton_rocm==3.1.0 - transformers 5.2.0 → 4.46.3, safetensors 0.5.3 → 0.4.0 - s3tokenizer unpinned → 0.3.0 - resemble-perth==1.0.1 directly (v1.0.1 is pip-installable; drop stub) - Drop Dockerfile perth_stub steps - Drop torch.compile and timing patches from engine.py (not needed) - Drop multi-pass warmup from main.py (torch JIT warmup not needed) - Drop ROCm 7.2-specific env vars from docker-compose.yml Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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478 B