Sync TransformerEngine-FL to upstream v2.17 - #105
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Integrates upstream NVIDIA/TransformerEngine v2.17 (commit 2e559f0) into flagos-ai/TransformerEngine-FL:main, preserving all multi-backend plugin work. - Upstream v2.14 -> v2.17 integration (EP, MXFP8/NVFP4, fused router/MLP) - 25 conflict files resolved, fork patches preserved (torch_nv, te_device_type, OpManager dispatcher, 9-backend CI/CD) - P0: removed 2 deleted C++ bindings (convert_host_pointers_to_tensor, get_device_pointer_for_data_and_scales) from plugin + 6 vendors - Enum sync: DType assert ==->subset, NVTE_QKV_Format/Layout members - Device abstraction re-injected (quantized_tensor.py make_empty etc.) - Includes flagos-ai#94 KunlunXin CICD support
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added 3 commits
August 11, 2026 12:18
- Added 15 new v2.17 bindings: splits_to_offsets_multi, copy_data_ptrs_to_device, bulk_allocate, create_empty_quantized_tensor, group_dequantize, multi_tensor_pad_last_dim, multi_tensor_swizzle_scales_for_gemm_, multi_tensor_transpose_to_bhsd, cusolvermp_ctx_create/destroy, newton_schulz, nvfp4_quantize_with_amax, nvfp4_group_quantize_with_amax, swizzle_scales_and_pack_ptrs_for_discrete_weights, get_grouped_gemm_setup_workspace_size - Added new params: tensor_offsets (group_quantize/bgrad_group_quantize/nvfp4_group_quantize_with_amax), glu_linear_offset (clamped_swiglu/clamped_dswiglu) - Removed dead bindings deleted in upstream v2.17 PR#3001: convert_host_pointers_to_tensor, get_device_pointer_for_data_and_scales
… signatures - register_ops.py: register get_grouped_gemm_setup_workspace_size (defined in cuda.py but missing from registry) and create_empty_quantized_tensor - cuda.py: fix get_grouped_gemm_setup_workspace_size stale signature (add num_tensors param per upstream gemm.py); fix swap_first_dims to pass out as keyword-only arg matching the C++ binding - ops.py + vendor backends (enflame/hygon/iluvatar/metax/musa): sync fused attention fwd/bwd signatures with v2.17 new params (o_format, qkv_scale_inv_format, do_format, dqkv_layout, do_scale_inv_format) Fixes runtime AttributeError / arg-count errors surfaced by L0/L1 CUDA unit tests (test_fusible_ops, distributed test_numerics).
- ops.py: add NVTERoutingMapFormat enum (BYTEMAP=0, BITMAP_U8=1) mirroring the C++ pybind enum, bind it in the tex proxy and __dir__ so transformer_engine.pytorch.router can re-export it - cuda.py: align 4 CUDABackend fused-router signatures with upstream v2.17 pybind: append routing_map_format to topk_fwd/bwd and aux_loss_fwd; drop stale num_tokens/num_experts from topk_bwd and aux_loss_bwd Fixes router import (AttributeError) and 891 test_fused_router failures; now 933 passed / 120 skipped / 0 failed.
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Integrates upstream NVIDIA/TransformerEngine v2.17 (commit 2e559f0) into flagos-ai/TransformerEngine-FL:main, preserving all multi-backend plugin work.
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