code: def __init__(
      self,
      emb_size: int,
      emb_dim: int,
      n_steps: int,
      n_logits: int,
      n_feat: int = 64,
      n_heads: int = 32,
      n_layers: int = 2,
  ):
      super().__init__()
      self.embedding = torch.nn.Embedding(n_logits, n_feat * n_heads)
      self.position_encoding = PositionEncoding(n_feat * n_heads)
      self.decoders = torch.nn.ModuleList(
          [
              PolicyHeadDoubleAttention(
                  n_steps, n_heads, n_feat, emb_size, emb_dim
              )
              for _ in range(n_layers)
          ]
      )
      self.relu = torch.nn.ReLU()
      self.linear2 = torch.nn.Linear(n_feat * n_heads, n_logits)
  
imports: import math
  import torch
  import torch.nn.functional
  from open_alpha_tensor.core.modules.attention import AlphaMultiHeadAttention
label_desc: Use image node_id 1 to create a new PolicyHeadCore object from inherited base classes: torch.nn with example: obj = PolicyHeadCore(emb_size, emb_dim, n_steps, n_logits, n_feat, n_heads, n_layers)