当A更稀疏时,如果乘积的列大小较小(例如matrix-vector 乘法),如果sp_a.dense_shape取较大的值,则此操作往往会执行良好。 下面是sparse_tensor_dense_matmul,标记为'sparse',和matmul(a_is_sparse=True),标记为'dense'之间的粗略速度比较。出于比较的目的,不包括从SparseTensor转换为密集Tensor所花费的时间,因此在...
Python code to generate a dense matrix from a sparse matrix in NumPy # Import numpyimportnumpyasnpfromscipy.sparseimportcsr_matrix# Creating a sparse matrixA=csr_matrix([[1,0,2],[0,3,0]])# Display original matrixprint("Original Matrix:\n",A,"\n")# Converting sparse matrix to den...
也可以是稀疏矩阵乘以一个稠密矩阵(顺序不能换,不能是稠密矩阵乘以稀疏矩阵,如果需要则先调换二者顺序为 sparse x dense,乘完再转置回来),乘完之后c是稠密矩阵,这类似于tensorflow中的 tf.sparse_tensor_dense_matmul 操作 row = [0, 1, 2] col = [0, 0, 1] value = [1, 2, 3] a = sp.csr_ma...
TypeError如果sp_input不是SparseTensor。 对于这个具有三个非空值的稀疏张量: sp_input = tf.SparseTensor( dense_shape=[3,5], values=[7,8,9], indices =[[0,1], [0,3], [2,0]]) 输出将是一个密集的[3, 5]张量,其值: tf.sparse.to_dense(sp_input).numpy() array([[0,7,0,...
在一些情况下,可能需要手动构造稀疏报文再将其转换为密集报文。以下代码块展示了Python中如何实现这一功能: importtorch# 创建稀疏张量sparse_tensor=torch.sparse.FloatTensor(torch.LongTensor([[0,1],[2,3]]),torch.FloatTensor([1,2]),torch.Size([4,4]))# 转换为密集张量dense_tensor=sparse_tensor.toDe...
针对你遇到的错误 "TypeError: A sparse matrix was passed, but dense data is required. Use X.toarray() to convert to a dense numpy array.",这里是一些详细的解答步骤和代码示例,帮助你解决这个问题: 理解错误消息内容: 这个错误表明你的代码中某个函数或模型期望接收一个密集矩阵(dense matrix),但实际...
>>>importnumpyasnp>>>from scipy.sparseimportcoo_matrix>>>random_state=np.random.RandomState(0)>>>row=random_state.randint(8,size=8)>>>col=random_state.randint(8,size=8)>>>data=random_state.randint(-4,4,8)>>>coo=coo_matrix((data,(row,col)),shape=(8,8))>>>a=coo.toarray()>...
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage retrieval in a multi-stage ranking architecture. Our toolkit is self-contained as a standard Python package and ...
Example: >>> coo_matrix([[0]], dtype=np.float16).todense() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/warren/local_scipy/lib/python2.7/site-packages/scipy/sparse/base.py", line 515, in todense retu...
A sparse matrix was passed, but dense data is required. Use X.toarray() to convert to a dense numpy 原因:数据生成的稀疏矩阵,模型需要的稠密矩阵,两者不兼容 解决:改模型,例如我用高斯朴素贝叶斯出现了这个bug,换用多项式朴素贝叶斯就可以得到较好的结果 解决二:也可以进行转化为稠密矩阵,能力不足,目前...