(self,内容)

(src, trg, device)

(self, d_model, eps = 1e-6)

(词_数表路径, 数_词表路径)

(self, vocab_size, d_model)

(self, 动作数, 输入维度, 优势估计参数G=0.9999, 学习率=0.0003, 泛化优势估计参数L=0.985, 策略裁剪幅度=0.2, 并行条目数=64, 轮数=10,熵系

(key)

(key)

(key)

(图片张量,操作序列,trg_mask)

(self, 状态,device,传入动作,手动=False)

(q, k, v, d_k, mask=None, dropout=None)

(img, text, left, top, textColor=(0, 255, 0), textSize=20)

(x)

(x)

(module, N)

(opt, trg_vocab, model_weights='model_weights')

(name )

(size, device)

(dicts)

(obj, name )

(self,轮号)

(窗口名称)

()

(数_词表,数据, 输出_分)

(self)

(self)

(self,device,状态,回报,动作,动作可能性,评价)

(self, 状态,device,目标输出_分_torch,手动=False)

( self, vocab_size_or_config_json_file=12491, n_positions=1024,

( self, d_model=768, n_layers=12, heads=12, dropou

(self, d_model, heads, dropout=0.1)

(self,ID)

(self, heads, d_model, dropout = 0.1)

(self, d_model, d_ff=2048, dropout = 0.1)

(self,输入_接口, 输出_接口)

(self, resnet)

(self, d_model, max_seq_len=1024, dropout=0.1)

(self, num_embeddings, embedding_dim, padding_idx=None, max_norm=None, norm_type=2., scale_gr

(self, 种类数, 隐藏层尺寸, 输入层尺寸=2048,输入尺寸A=36)

(self, vocab_size, d_model, N, heads, dropout, 最大长度=1024)

(self, trg_vocab, d_model, N, heads, dropout,图向量尺寸=6*6*2048)

(self, 并行条目数量)

(self, x, trg_mask)

(self, x)

(self, q, k, v, mask=None)

(self, x)

(self, x)

(self, img, att_size=6)

(self, x)

(self, x)

(self, input)

(self, 图向量)

(self,图向量,操作 ,trg_mask)

(self, 图向量 ,操作, trg_mask)

(size, device)

(key)

(key)

(key)

(key)

(key)

(key)

(self)

()

()

()

(总词表, 词_数表路径, 数_词表路径)

(状态组,device)

(self,文件名)

(self, 文件名)

(self,device)

(数_词表,数据, 输人_分,标签)

(数_词表,数据, 输人_分)

(输入表单, 词_数表)

(输入表单, 词_数表)

(输入表单, 词_数表, numpy数组路径)

(输入表单, 词_数表, numpy数组路径)

(self, 状态,目标输出,打印,数_词表,操作_分_torch,device)

(self,device,状态,回报,动作,动作可能性,评价,完结集)

(self, 状态, 动作, 动作概率, 评价, 回报, 完结,计数)

(self, 状态, 动作, 动作概率, 评价, 回报, 完结,计数)

(路径)

(路径)

(self,文件名)

(self, 文件名)

(self)

(self, 状态)