/*************************************************************************
 * Copyright (c) 2022-2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 *
 * See LICENSE for license information.
 ************************************************************************/

#include "extensions.h"

namespace transformer_engine {
namespace jax {

template <typename T>
pybind11::capsule EncapsulateFunction(T *fn) {
  return pybind11::capsule(reinterpret_cast<void *>(fn), "xla._CUSTOM_CALL_TARGET");
}

template <typename T>
pybind11::capsule EncapsulateFFI(T *fn) {
  static_assert(std::is_invocable_r_v<XLA_FFI_Error *, T, XLA_FFI_CallFrame *>,
                "Encapsulated function must be an XLA FFI handler");
  return pybind11::capsule(reinterpret_cast<void *>(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);

  dict["te_transpose_ffi"] = EncapsulateFFI(TransposeHandler);
  dict["te_cast_transpose_ffi"] = EncapsulateFFI(CastTransposeHandler);
  dict["te_act_lu_ffi"] = EncapsulateFFI(ActLuHandler);
  dict["te_act_lu_fp8_ffi"] = EncapsulateFFI(ActLuFP8Handler);
  dict["te_dact_lu_ffi"] = EncapsulateFFI(DActLuHandler);
  dict["te_quantize_ffi"] = EncapsulateFFI(QuantizeHandler);
  dict["te_layernorm_forward_fp8_ffi"] = EncapsulateFFI(LayerNormForwardFP8Handler);
  dict["te_layernorm_backward_ffi"] = EncapsulateFFI(LayerNormBackwardHandler);
  dict["te_fused_attn_forward_ffi"] = EncapsulateFFI(FusedAttnForwardHandler);
  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_cudnn_version", &GetCudnnRuntimeVersion);
  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);
  m.def("nvte_get_qkv_format", &nvte_get_qkv_format);

  pybind11::enum_<DType>(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_<NVTE_Bias_Type>(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_<NVTE_Mask_Type>(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)
      .value("NVTE_CAUSAL_BOTTOM_RIGHT_MASK", NVTE_Mask_Type::NVTE_CAUSAL_BOTTOM_RIGHT_MASK)
      .value("NVTE_PADDING_CAUSAL_BOTTOM_RIGHT_MASK",
             NVTE_Mask_Type::NVTE_PADDING_CAUSAL_BOTTOM_RIGHT_MASK);

  pybind11::enum_<NVTE_QKV_Layout>(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)
      .value("NVTE_T3HD", NVTE_QKV_Layout::NVTE_T3HD)
      .value("NVTE_THD_T2HD", NVTE_QKV_Layout::NVTE_THD_T2HD)
      .value("NVTE_THD_THD_THD", NVTE_QKV_Layout::NVTE_THD_THD_THD);

  pybind11::enum_<NVTE_QKV_Format>(m, "NVTE_QKV_Format", pybind11::module_local())
      .value("NVTE_SBHD", NVTE_QKV_Format::NVTE_SBHD)
      .value("NVTE_BSHD", NVTE_QKV_Format::NVTE_BSHD)
      .value("NVTE_THD", NVTE_QKV_Format::NVTE_THD);

  pybind11::enum_<NVTE_Activation_Type>(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)
      .export_values();

  pybind11::enum_<NVTE_Fused_Attn_Backend>(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
