def __init__( self, num_embeddings, embedding_dim, padding_idx, freeze_embed=False, normalize_embed=False, normalize_decay_rate=0.99, ): super().__init__(num_embeddings, embedding_dim, padding_idx=padding_idx) nn.init.uniform_(self.weight, -0.1, 0.1) nn.init.constant_(self.weight[pa...
self.input_spec = InputSpec(ndim=4) 開發者ID:cvjena,項目名稱:semantic-embeddings,代碼行數:7,代碼來源:cifar_resnet.py 示例9: __init__ ▲點讚 5▼ # 需要導入模塊: from keras.utils import conv_utils [as 別名]# 或者: from keras.utils.conv_utils importnormalize_data_format[as 別名]...
Hello, Many thanks to the team for making Seurat such powerful analysis tool. However upon update to Seurat v5, I have come across few hurdles. Running NormalizeData() became virtually impossible, as its runtime has gone from few seconds...
"task"],# ["experiment_setup", "subcategory"],# ["experiment_setup", "method"],# ["experiment_setup", "embeddings"]]dframe =json_normalize(data)if"details"indframe:
而Titan嵌入模型没有这样做。运行上述代码将给出以下输出：
similarity_search_with_score("I like apples", k=1) print(results) normalize_L2 = True vectorstore = FAISS.from_texts( texts, embeddings, distance_strategy=distance_strategy, normalize_L2=normalize_L2 ) results = vectorstore.similarity_search_with_score("I like apples", k=1) print(results)...
(rand_values, id2word, word2vec)embeddings=theano.shared(value=rand_values,borrow=True)# allocate symbolic variables for the data# index = T.lscalar()left=T.imatrix()#(2*batch, len)left_mask=T.fmatrix()#(2*batch, len)span=T.imatrix()#(2*batch, span_len)span_mask=T.fmatrix()#...
We also propose new three and two-dimensional performance graphs for total recall studies in a range of embeddings.HuijsmansLeidenDionysiusLeidenP.LeidenSebeLeidenNicuLeidenEBSCO_bspIEEE Transactions on Pattern Analysis & Machine IntelligenceD.P. Huijsmans and N. Sebe, "How to Complete Performance ...
parser.add_argument('-e','--embed', action='store_true', help='Use embeddings instead of bong')returnparser.parse_args() 开发者ID:NLPrinceton,项目名称:SARC,代码行数:18,代码来源:eval.py 示例6: strip_accents_unicode ▲点赞 6▼
开发者ID:cvjena,项目名称:semantic-embeddings,代码行数:7,代码来源:cifar_resnet.py 示例6: __init__ ▲点赞 5▼ # 需要导入模块: from keras.utils import conv_utils [as 别名]# 或者: from keras.utils.conv_utils importnormalize_tuple[as 别名]def__init__(self, upsampling=(2,2), output_si...