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...
batching.dense_to_sparse_batch(4, [12])).make_initializable_iterator()) init_op = iterator.initializer get_next = sparse_tensor.SparseTensor(*iterator.get_next())withself.test_session()assess:# Initialize with an input tensor of incompatible rank.sess.run(init_op, feed_di...
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...
numpy.matrix:numpy 和上面一样,也是模块名,我们依旧完全没有必要去管它。至于 matrix,它没有上面那么复杂,和 array 一样,直接翻译成中文就行了,它就是矩阵。因此,numpy.matrix 表示 NumPy 模块中的矩阵类。 因此,当 ndarray 的 n≠2 的时候,ndarray 类的某个实例就绝对不可能是一个矩阵,至少无法看作是一个...
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...
Issue and/or context: As tracked on issue #2407 / [sc-51048]. Note that the intended Python and R API changes are all agreed on and finalized as described in #2407. Changes: This is a split-out to ...
>>>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()>...
API Functions of ``xf::sparse`` Terms and Conditions. API Functions of xf::sparse L2 Kernel User Guide CSCMV Overview 1. Matrix partitioning and device memory layout 1. The functionality of the CUs 1. Build and test the design Double Precision SpMV Overview 1. Matrix partitionin...
《python之禅》 | The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. ...
tf.data.experimental.dense_to_sparse_batch( batch_size, row_shape ) 参数 batch_sizetf.int64标量tf.Tensor,表示要在单个批次中组合的此数据集的连续元素的数量。 row_shape一个tf.TensorShape或tf.int64向量 tensor-like 对象,表示生成的tf.sparse.SparseTensor中一行的等效密集形状。此数据集的每个元素必须具...