GraphGallery 0.4.1

New features

• Strided (dense) Tensor

>>> backend()
TensorFlow 2.1.2 Backend

>>> from graphgallery import transforms as T
>>> arr = [1, 2, 3]
>>> T.astensor(arr)
<tf.Tensor: shape=(3,), dtype=int32, numpy=array([1, 2, 3], dtype=int32)>

• Sparse Tensor

>>> import scipy.sparse as sp
>>> sp_matrix = sp.eye(3)
>>> T.astensor(sp_matrix)
<tensorflow.python.framework.sparse_tensor.SparseTensor at 0x7f1bbc205dd8>

• also works for PyTorch, just like

>>> from graphgallery import set_backend
>>> set_backend('torch') # torch, pytorch or th
PyTorch 1.6.0+cu101 Backend

>>> T.astensor(arr)
tensor([1, 2, 3])

>>> T.astensor(sp_matrix)
tensor(indices=tensor([[0, 1, 2],
                       [0, 1, 2]]),
       values=tensor([1., 1., 1.]),
       size=(3, 3), nnz=3, layout=torch.sparse_coo)

• To Numpy or Scipy sparse matrix

>>> tensor = T.astensor(arr)
>>> T.tensoras(tensor)
array([1, 2, 3])

>>> sp_tensor = T.astensor(sp_matrix)
>>> T.tensoras(sp_tensor)
<3x3 sparse matrix of type '<class 'numpy.float32'>'
    with 3 stored elements in Compressed Sparse Row format>

• Or even convert one Tensor to another one

>>> tensor = T.astensor(arr, kind="T")
>>> tensor
<tf.Tensor: shape=(3,), dtype=int64, numpy=array([1, 2, 3])>
>>> T.tensor2tensor(tensor)
tensor([1, 2, 3])

>>> sp_tensor = T.astensor(sp_matrix, kind="T") # set kind="T" to convert to tensorflow tensor
>>> sp_tensor
<tensorflow.python.framework.sparse_tensor.SparseTensor at 0x7efb6836a898>
>>> T.tensor2tensor(sp_tensor)
tensor(indices=tensor([[0, 1, 2],
                       [0, 1, 2]]),
       values=tensor([1., 1., 1.]),
       size=(3, 3), nnz=3, layout=torch.sparse_coo)