(self,
                 vocab_size_or_config_json_file=267735,
                 cutoffs=[20000, 40000, 200000],
                 d_model=1024,
                 d_embed=1024,
                 n_head=16,
                 d_head=64,
                 d_inner=4096,
                 div_val=4,
                 pre_lnorm=False,
                 n_layer=18,
                 tgt_len=128,
                 ext_len=0,
                 mem_len=1600,
                 clamp_len=1000,
                 same_length=True,
                 proj_share_all_but_first=True,
                 attn_type=0,
                 sample_softmax=-1,
                 adaptive=True,
                 tie_weight=True,
                 dropout=0.1,
                 dropatt=0.0,
                 untie_r=True,
                 init="normal",
                 init_range=0.01,
                 proj_init_std=0.01,
                 init_std=0.02,
                 layer_norm_epsilon=1e-5,
                 **kwargs)
Constructs TransfoXLConfig.
Constructs TransfoXLConfig.
Constructs TransfoXLConfig .
def __init__(self,
                 vocab_size_or_config_json_file=267735,
                 cutoffs=[20000, 40000, 200000],
                 d_model=1024,
                 d_embed=1024,
                 n_head=16,
                 d_head=64,
                 d_inner=4096,
                 div_val=4,
                 pre_lnorm=False,
                 n_layer=18,
                 tgt_len=128,
                 ext_len=0,
                 mem_len=1600,
                 clamp_len=1000,
                 same_length=True,
                 proj_share_all_but_first=True,
                 attn_type=0,
                 sample_softmax=-1,
                 adaptive=True,
                 tie_weight=True,
                 dropout=0.1,
                 dropatt=0.0,
                 untie_r=True,
                 init="normal",
                 init_range=0.01,
                 proj_init_std=0.01,
                 init_std=0.02,
                 layer_norm_epsilon=1e-5,
                 **kwargs):
        """Constructs TransfoXLConfig.
        """
        super(TransfoXLConfig, self).__init__(**kwargs)
        self.n_token = vocab_size_or_config_json_file if isinstance(vocab_size_or_config_json_file, int) else -1
        self.cutoffs = []
        self.cutoffs.extend(cutoffs)
        self.tie_weight = tie_weight
        if proj_share_all_but_first:
            self.tie_projs = [False] + [True] * len(self.cutoffs)
        else:
            self.tie_projs = [False] + [False] * len(self.cutoffs)
        self.d_model = d_model
        self.d_embed = d_embed
        self.d_head = d_head
        self.d_inner = d_inner
        self.div_val = div_val
        self.pre_lnorm = pre_lnorm
        self.n_layer = n_layer
        self.n_head = n_head
        self.tgt_len = tgt_len
        self.ext_len = ext_len
        self.mem_len = mem_len
        self.same_length = same_length
        self.attn_type = attn_type
        self.clamp_len = clamp_len
        self.sample_softmax = sample_softmax
        self.adaptive = adaptive
        self.dropout = dropout
        self.dropatt = dropatt
        self.untie_r = untie_r
        self.init = init
        self.init_range = init_range
        self.proj_init_std = proj_init_std
        self.init_std = init_std
        self.layer_norm_epsilon = layer_norm_epsilon

        if isinstance(vocab_size_or_config_json_file, str) or (sys.version_info[0] == 2
                        and isinstance(vocab_size_or_config_json_file, unicode)):
            with open(vocab_size_or_config_json_file, "r", encoding='utf-8') as reader:
                json_config = json.loads(reader.read())
            for key, value in json_config.items():
                self.__dict__[key] = value
        elif not isinstance(vocab_size_or_config_json_file, int):
            raise ValueError("First argument must be either a vocabulary size (int)"
                             " or the path to a pretrained model config file (str)")
def __init__ ( self , vocab_size_or_config_json_file = 267735 , cutoffs = [ 20000 , 40000 , 200000 ] , d_model = 1024 , d_embed = 1024 , n_head = 16 , d_head = 64 , d_inner = 4096 , div_val = 4 , pre_lnorm = False , n_layer = 18 , tgt_len = 128 , ext_len = 0 , mem_len = 1600 , clamp_len = 1000 , same_length = True , proj_share_all_but_first = True , attn_type = 0 , sample_softmax = - 1 , adaptive = True , tie_weight = True , dropout = 0.1 , dropatt = 0.0 , untie_r = True , init = "normal" , init_range = 0.01 , proj_init_std = 0.01 , init_std = 0.02 , layer_norm_epsilon = 1e-5 , * * kwargs ) : super ( TransfoXLConfig , self ) . __init__ ( * * kwargs ) self . n_token = vocab_size_or_config_json_file if isinstance ( vocab_size_or_config_json_file , int ) else - 1 self . cutoffs = [ ] self . cutoffs . extend ( cutoffs ) self . tie_weight = tie_weight if proj_share_all_but_first : self . tie_projs = [ False ] + [ True ] * len ( self . cutoffs ) else : self . tie_projs = [ False ] + [ False ] * len ( self . cutoffs ) self . d_model = d_model self . d_embed = d_embed self . d_head = d_head self . d_inner = d_inner self . div_val = div_val self . pre_lnorm = pre_lnorm self . n_layer = n_layer self . n_head = n_head self . tgt_len = tgt_len self . ext_len = ext_len self . mem_len = mem_len self . same_length = same_length self . attn_type = attn_type self . clamp_len = clamp_len self . sample_softmax = sample_softmax self . adaptive = adaptive self . dropout = dropout self . dropatt = dropatt self . untie_r = untie_r self . init = init self . init_range = init_range self . proj_init_std = proj_init_std self . init_std = init_std self . layer_norm_epsilon = layer_norm_epsilon if isinstance ( vocab_size_or_config_json_file , str ) or ( sys . version_info [ 0 ] == 2 and isinstance ( vocab_size_or_config_json_file , unicode ) ) : with open ( vocab_size_or_config_json_file , "r" , encoding = 'utf-8' ) as reader : json_config = json . loads ( reader . read ( ) ) for key , value in json_config . items ( ) : self . __dict__ [ key ] = value elif not isinstance ( vocab_size_or_config_json_file , int ) : raise ValueError ( "First argument must be either a vocabulary size (int)" " or the path to a pretrained model config file (str)" )