[Model][ROCm] Enable DeepSeek V4 Vision - #55107
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Resolve model paths without a piecewise provider to safe full-decode or eager modes when breakable graphs are unavailable, preserving platform compile paths and rejecting late-invalid combinations. Co-authored-by: OpenAI Codex <codex@openai.com> Signed-off-by: Andreas Karatzas <Andreas.Karatzas@amd.com>
Enable the shared DeepSeek V4 vision wrapper on ROCm, preserve platform-specific text behavior, and add focused multimodal and attention coverage. Co-authored-by: OpenAI Codex <codex@openai.com> Signed-off-by: Andreas Karatzas <Andreas.Karatzas@amd.com>
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Preserve default compilation dispatch, accept graph-safe auxiliary configs, and keep adaptive verification on a full decode graph when piecewise capture is unavailable. Signed-off-by: Andreas Karatzas <Andreas.Karatzas@amd.com>
Signed-off-by: Andreas Karatzas <akaratza@amd.com>
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Bring in the latest stacked-base changes, including the AMD LoRA allocator configuration fix. Co-authored-by: OpenAI Codex <codex@openai.com> Signed-off-by: Andreas Karatzas <akaratza@amd.com>
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✅ Triggered Buildkite CI #87318 for commit |
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DeepSeek-V4-Flash-Vision-Exp on 4× AMD gfx950 per run (ROCm, TP4/EP, FP8 KV, AITER, 1,024 batched tokens, graph mode NONE; #55107
OCRBench category accuracy uses the official scoring rule, thinking disabled, and a 4,096-token output limit.
DSpark acceptance is aggregated over each full run using Prometheus counter deltas with fixed verification (adaptive verification disabled).
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Use the upstream CUDA graph fallback implementation from #55095 while preserving ROCm vision routing, shared wrapper weight finalization, and complete image-span visibility. Keep incoming runtime, quantization, multimodal embedding, and DeepSeek V4.1 fixes and features. Update the MTP routing test for the registered warmup kernel callable and retain the additional adaptive-verification graph fallback case. Keep row-major FP8 weights for DeepSeek V4's custom ROCm GEMM consumers. The incoming AITER preshuffled backend otherwise rearranges weights before the model's own preparation, causing double shuffling and incorrect raw weight reads. Other linears retain the new backend. Co-authored-by: OpenAI Codex <codex@openai.com> Signed-off-by: Andreas Karatzas <akaratza@amd.com>
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✅ Triggered Buildkite CI #88304 for commit |
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September 11, 2026 10:12
Adopt the upstream AITER FP8 preshuffle fix from #56433 and remove our superseded row-major kernel workaround. Preserve Quark detection so its custom consumers also avoid shuffling weights twice. Keep vision routing, deferred weight finalization and image-span attention support, and retain both DeepSeek vision and incoming HY-V4 tests in the AMD CI job. Update the FP8 numerical regressions for the upstream weight and activation-scale layout contracts. Validation: 346 tests passed, 6 skipped across configuration, adaptive verification, vision/FP8, focused attention and RoPE config checks. Real TP4 vision smoke returned 4 for 2+2 and matched all five prior OCR pass/fail outcomes (3/5 correct), without request errors or truncation. Co-authored-by: OpenAI Codex <codex@openai.com> Signed-off-by: Andreas Karatzas <akaratza@amd.com>
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✅ Triggered Buildkite CI #88338 for commit |
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Signed-off-by: Andreas Karatzas <Andreas.Karatzas@amd.com> Signed-off-by: Andreas Karatzas <akaratza@amd.com> Co-authored-by: OpenAI Codex <codex@openai.com>
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DeepseekV4ForConditionalGenerationon ROCm by moving the platform-neutral wrapper tocommon/, retaining the NVIDIA compatibility shim and unsupported XPU stub, and enabling ROCm registry, dummy-init, and tensor-schema paths.bias_vlin hash and regular ROCm MoE layers, expose local logits, and extend sparse-prefill visibility across complete image spans without changing text-only row width.1356635d837c4ef002ec98c1a0296e7ff60be3c1, which introduced the checkpoint with a NVIDIA-only wrapper and non-CUDA guards.AI assistance: OpenAI Codex assisted with merge resolution, source review, and regression testing.