code: def __init__(
      self,
      hidden_size: int,
      num_attention_heads: int,
      attention_dropout_prob: float,
      hidden_dropout_prob: float,
      dtype=None,
      checkpoint: bool = False,
      max_position_embeddings=1024,
  ):
      super().__init__(
          hidden_size,
          num_attention_heads,
          attention_dropout_prob,
          hidden_dropout_prob,
          dtype=dtype,
          checkpoint=checkpoint,
          max_position_embeddings=max_position_embeddings,
      )
      self.softmax = kernel.FusedScaleMaskSoftmax(
          input_in_fp16=True,
          input_in_bf16=False,
          attn_mask_type=AttnMaskType.causal,
          scaled_masked_softmax_fusion=True,
          mask_func=None,
          softmax_in_fp32=True,
          scale=math.sqrt(self.attention_head_size),
      )
  
imports: import math
  import torch
  from torch import Tensor
  from torch import nn
  from colossalai import kernel
  from colossalai import nn
  from colossalai.kernel.cuda_native.scaled_softmax import AttnMaskType
  from colossalai.legacy.core import global_context
  from colossalai.legacy.nn.layer import Linear1D_Col, Linear1D_Row
  from colossalai.legacy.nn.layer.base_layer import ParallelLayer
  from colossalai.legacy.nn.layer.utils import ACT2FN, divide
  from colossalai.legacy.utils.activation_checkpoint import checkpoint
  from colossalai.utils import checkpoint
label_desc: Use image node_id 1 to create a new FusedGPTSelfAttention1D object from inherited base classes: GenericGPTSelfAttention1D with example: obj = FusedGPTSelfAttention1D(hidden_size, num_attention_heads, attention_dropout_prob, hidden_dropout_prob, dtype, checkpoint, max_position_embeddings)