/************************************************************************* * Copyright (c) 2022-2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved. * * See LICENSE for license information. ************************************************************************/ #include "jax/csrc/extensions.h" namespace transformer_engine { namespace jax { template pybind11::capsule EncapsulateFunction(T *fn) { return pybind11::capsule(reinterpret_cast(fn), "xla._CUSTOM_CALL_TARGET"); } pybind11::dict Registrations() { pybind11::dict dict; dict["te_transpose"] = EncapsulateFunction(Transpose); dict["te_cast_transpose"] = EncapsulateFunction(CastTranspose); dict["te_act_lu"] = EncapsulateFunction(ActLu); dict["te_act_lu_fp8"] = EncapsulateFunction(ActLuFP8); dict["te_dact_lu"] = EncapsulateFunction(DActLu); dict["te_dbias_cast_transpose"] = EncapsulateFunction(DBiasCastTranspose); dict["te_dact_lu_dbias_cast_transpose"] = EncapsulateFunction(DActLuDBiasCastTranspose); dict["te_dgated_act_lu_cast_transpose"] = EncapsulateFunction(DGatedActLuCastTranspose); dict["te_layernorm_forward"] = EncapsulateFunction(LayerNormForward); dict["te_layernorm_forward_fp8"] = EncapsulateFunction(LayerNormForwardFP8); dict["te_layernorm_backward"] = EncapsulateFunction(LayerNormBackward); dict["te_rmsnorm_forward"] = EncapsulateFunction(RMSNormForward); dict["te_rmsnorm_forward_fp8"] = EncapsulateFunction(RMSNormForwardFP8); dict["te_rmsnorm_backward"] = EncapsulateFunction(RMSNormBackward); dict["te_quantize"] = EncapsulateFunction(Quantize); dict["te_dequantize"] = EncapsulateFunction(Dequantize); dict["te_scaled_softmax_forward"] = EncapsulateFunction(ScaledSoftmaxForward); dict["te_scaled_softmax_backward"] = EncapsulateFunction(ScaledSoftmaxBackward); dict["te_scaled_masked_softmax_forward"] = EncapsulateFunction(ScaledMaskedSoftmaxForward); dict["te_scaled_masked_softmax_backward"] = EncapsulateFunction(ScaledMaskedSoftmaxBackward); dict["te_scaled_upper_triang_masked_softmax_forward"] = EncapsulateFunction(ScaledUpperTriangMaskedSoftmaxForward); dict["te_scaled_upper_triang_masked_softmax_backward"] = EncapsulateFunction(ScaledUpperTriangMaskedSoftmaxBackward); dict["te_fused_attn_forward"] = EncapsulateFunction(FusedAttnForward); dict["te_fused_attn_backward"] = EncapsulateFunction(FusedAttnBackward); return dict; } PYBIND11_MODULE(transformer_engine_jax, m) { m.def("registrations", &Registrations); m.def("pack_common_descriptor", &PackCustomCallCommonDescriptor, pybind11::arg(), pybind11::arg(), pybind11::arg(), pybind11::arg("act_num") = 0); m.def("pack_common_wk_descriptor", &PackCustomCallCommonWkDescriptor, pybind11::arg(), pybind11::arg(), pybind11::arg(), pybind11::arg(), pybind11::arg(), pybind11::arg("act_num") = 0); m.def("pack_norm_descriptor", &PackCustomCallNormDescriptor); m.def("pack_softmax_descriptor", &PackCustomCallSoftmaxDescriptor); m.def("pack_fused_attn_descriptor", &PackCustomCallFusedAttnDescriptor); m.def("get_fused_attn_backend", &GetFusedAttnBackend); m.def("get_cuda_version", &GetCudaRuntimeVersion); m.def("get_device_compute_capability", &GetDeviceComputeCapability); m.def("get_cublasLt_version", &cublasLtGetVersion); m.def("get_dact_dbias_ct_workspace_sizes", &GetDActDBiasCastTransposeWorkspaceSizes); m.def("get_dbias_ct_workspace_sizes", &GetDBiasCastTransposeWorkspaceSizes); m.def("get_layernorm_fwd_workspace_sizes", &GetLayerNormForwardWorkspaceSizes); m.def("get_layernorm_bwd_workspace_sizes", &GetLayerNormBackwardWorkspaceSizes); m.def("get_fused_attn_fwd_workspace_sizes", &GetFusedAttnForwardWorkspaceSizes); m.def("get_fused_attn_bwd_workspace_sizes", &GetFusedAttnBackwardWorkspaceSizes); pybind11::enum_(m, "DType", pybind11::module_local()) .value("kByte", DType::kByte) .value("kInt32", DType::kInt32) .value("kInt64", DType::kInt64) .value("kFloat32", DType::kFloat32) .value("kFloat16", DType::kFloat16) .value("kBFloat16", DType::kBFloat16) .value("kFloat8E4M3", DType::kFloat8E4M3) .value("kFloat8E5M2", DType::kFloat8E5M2); pybind11::enum_(m, "NVTE_Bias_Type", pybind11::module_local()) .value("NVTE_NO_BIAS", NVTE_Bias_Type::NVTE_NO_BIAS) .value("NVTE_PRE_SCALE_BIAS", NVTE_Bias_Type::NVTE_PRE_SCALE_BIAS) .value("NVTE_POST_SCALE_BIAS", NVTE_Bias_Type::NVTE_POST_SCALE_BIAS); pybind11::enum_(m, "NVTE_Mask_Type", pybind11::module_local()) .value("NVTE_NO_MASK", NVTE_Mask_Type::NVTE_NO_MASK) .value("NVTE_PADDING_MASK", NVTE_Mask_Type::NVTE_PADDING_MASK) .value("NVTE_CAUSAL_MASK", NVTE_Mask_Type::NVTE_CAUSAL_MASK) .value("NVTE_PADDING_CAUSAL_MASK", NVTE_Mask_Type::NVTE_PADDING_CAUSAL_MASK); pybind11::enum_(m, "NVTE_QKV_Layout", pybind11::module_local()) .value("NVTE_BS3HD", NVTE_QKV_Layout::NVTE_BS3HD) .value("NVTE_BSHD_BS2HD", NVTE_QKV_Layout::NVTE_BSHD_BS2HD) .value("NVTE_BSHD_BSHD_BSHD", NVTE_QKV_Layout::NVTE_BSHD_BSHD_BSHD); pybind11::enum_(m, "NVTE_Activation_Type", pybind11::module_local()) .value("GELU", NVTE_Activation_Type::GELU) .value("GEGLU", NVTE_Activation_Type::GEGLU) .value("SILU", NVTE_Activation_Type::SILU) .value("SWIGLU", NVTE_Activation_Type::SWIGLU) .value("RELU", NVTE_Activation_Type::RELU) .value("REGLU", NVTE_Activation_Type::REGLU) .value("QGELU", NVTE_Activation_Type::QGELU) .value("QGEGLU", NVTE_Activation_Type::QGEGLU) .value("SRELU", NVTE_Activation_Type::SRELU) .value("SREGLU", NVTE_Activation_Type::SREGLU); pybind11::enum_(m, "NVTE_Fused_Attn_Backend", pybind11::module_local()) .value("NVTE_No_Backend", NVTE_Fused_Attn_Backend::NVTE_No_Backend) .value("NVTE_F16_max512_seqlen", NVTE_Fused_Attn_Backend::NVTE_F16_max512_seqlen) .value("NVTE_F16_arbitrary_seqlen", NVTE_Fused_Attn_Backend::NVTE_F16_arbitrary_seqlen) .value("NVTE_FP8", NVTE_Fused_Attn_Backend::NVTE_FP8); } } // namespace jax } // namespace transformer_engine