code: def forward(
      self,
      input_ids: torch.Tensor,
      position_ids: torch.Tensor,
      cu_seqlen_prefill: Optional[torch.Tensor],
      kv_cache: List[Tuple[torch.Tensor, torch.Tensor]],
      block_tables: torch.Tensor,
      slots: torch.Tensor,
      input_lengths: torch.Tensor,
      max_s: int,
      prefill_cache_indices: Optional[torch.Tensor],
      lm_head_indices: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      true_max_s = max_s
      if prefill_cache_indices is not None:
          # Slots also need to be sliced as it has the same size as the whole kv tensor
          slots = slots[prefill_cache_indices]
      elif self.max_past is not None:
          # Clamp in decode mode as paged attention requires clamped values whereas the flash attention
          # kernel requires the true values
          max_s = min(self.max_past, max_s)
          input_lengths = torch.clamp(input_lengths, max=self.max_past)
  
      hidden_states = self.model(
          input_ids,
          position_ids,
          cu_seqlen_prefill,
          kv_cache,
          block_tables,
          slots,
          input_lengths,
          max_s,
          true_max_s,
          prefill_cache_indices,
      )
      if lm_head_indices is not None:
          hidden_states = hidden_states[lm_head_indices]
      logits = self.lm_head(hidden_states)
      return logits
  
imports: import torch
  import torch.distributed
  import numpy
  from torch import nn
  from transformers.activations import ACT2FN
  from transformers.configuration_utils import PretrainedConfig
  from typing import Optional, List, Tuple
  from loguru import logger
  from text_generation_server.utils import paged_attention, flash_attn
  from text_generation_server.utils.layers import FastLinear, FastRMSNorm, TensorParallelRowLinear, TensorParallelColumnLinear, TensorParallelEmbedding, PositionRotaryEmbedding, TensorParallelHead, get_linear
label_desc: Use image node_id 2 for calling the FlashMixtralForCausalLM obj's underlying member method code with example usage: obj.forward(input_ids, position_ids, cu_seqlen_prefill, kv_cache, block_tables, slots, input_lengths, max_s, prefill_cache_indices, lm_head_indices) and returns: logits