# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from dataclasses import dataclass
from typing import ClassVar

import torch

from vllm.attention.backends.abstract import AttentionBackend
from vllm.config import VllmConfig
from vllm.v1.attention.backends.utils import (AttentionMetadataBuilder,
                                              CommonAttentionMetadata,
                                              split_decodes_and_prefills)
from vllm.v1.kv_cache_interface import AttentionSpec, MambaSpec


class LinearAttentionBackend(AttentionBackend):

    @staticmethod
    def get_builder_cls() -> type["LinearAttentionMetadataBuilder"]:
        return LinearAttentionMetadataBuilder


@dataclass
class LinearAttentionMetadata:
    num_prefills: int
    num_prefill_tokens: int
    num_decodes: int
    num_decode_tokens: int
    query_start_loc: torch.Tensor
    seq_lens: torch.Tensor

    state_indices_tensor: torch.Tensor  # shape: [batch,]


class LinearAttentionMetadataBuilder(
        AttentionMetadataBuilder[LinearAttentionMetadata]):

    reorder_batch_threshold: ClassVar[int] = 1

    def __init__(self, kv_cache_spec: AttentionSpec, layer_names: list[str],
                 vllm_config: VllmConfig, device: torch.device):
        super().__init__(kv_cache_spec, layer_names, vllm_config, device)
        assert isinstance(kv_cache_spec, MambaSpec)

    def build(self,
              common_prefix_len: int,
              common_attn_metadata: CommonAttentionMetadata,
              fast_build: bool = False) -> LinearAttentionMetadata:
        query_start_loc = common_attn_metadata.query_start_loc
        seq_lens = common_attn_metadata.seq_lens

        state_indices_tensor = common_attn_metadata.block_table_tensor[:, 0]

        num_decodes, num_prefills, num_decode_tokens, num_prefill_tokens = (
            split_decodes_and_prefills(
                common_attn_metadata,
                decode_threshold=self.reorder_batch_threshold))

        attn_metadata = LinearAttentionMetadata(
            num_prefills=num_prefills,
            num_prefill_tokens=num_prefill_tokens,
            num_decodes=num_decodes,
            num_decode_tokens=num_decode_tokens,
            query_start_loc=query_start_loc,
            seq_lens=seq_lens,
            state_indices_tensor=state_indices_tensor,
        )
        return attn_metadata
