Improve Code Docs

torch_sparse/coalesce.py

@@ -13,8 +13,8 @@ def coalesce(index, value, m, n, op='add', fill_value=0):
     Args:
         index (:class:`LongTensor`): The index tensor of sparse matrix.
         value (:class:`Tensor`): The value tensor of sparse matrix.
-        m (int): The first dimension of sparse matrix.
-        n (int): The second dimension of sparse matrix.
+        m (int): The first dimension of corresponding dense matrix.
+        n (int): The second dimension of corresponding dense matrix.
         op (string, optional): The scatter operation to use. (default:
             :obj:`"add"`)
         fill_value (int, optional): The initial fill value of scatter

torch_sparse/eye.py

@@ -5,7 +5,7 @@ def eye(m, dtype=None, device=None):
     """Returns a sparse matrix with ones on the diagonal and zeros elsewhere.
 
     Args:
-        m (int): The first dimension of sparse matrix.
+        m (int): The first dimension of corresponding dense matrix.
         dtype (`torch.dtype`, optional): The desired data type of returned
             value vector. (default is set by `torch.set_default_tensor_type()`)
         device (`torch.device`, optional): The desired device of returned

torch_sparse/spmm.py

@@ -7,8 +7,8 @@ def spmm(index, value, m, n, matrix):
     Args:
         index (:class:`LongTensor`): The index tensor of sparse matrix.
         value (:class:`Tensor`): The value tensor of sparse matrix.
-        m (int): The first dimension of sparse matrix.
-        n (int): The second dimension of sparse matrix.
+        m (int): The first dimension of corresponding dense matrix.
+        n (int): The second dimension of corresponding dense matrix.
         matrix (:class:`Tensor`): The dense matrix.
 
     :rtype: :class:`Tensor`

torch_sparse/spspmm.py

@@ -16,10 +16,10 @@ def spspmm(indexA, valueA, indexB, valueB, m, k, n):
         valueA (:class:`Tensor`): The value tensor of first sparse matrix.
         indexB (:class:`LongTensor`): The index tensor of second sparse matrix.
         valueB (:class:`Tensor`): The value tensor of second sparse matrix.
-        m (int): The first dimension of first sparse matrix.
-        k (int): The second dimension of first sparse matrix and first
-            dimension of second sparse matrix.
-        n (int): The second dimension of second sparse matrix.
+        m (int): The first dimension of first corresponding dense matrix.
+        k (int): The second dimension of first corresponding dense matrix and first
+            dimension of second corresponding dense matrix.
+        n (int): The second dimension of second corresponding dense matrix.
 
     :rtype: (:class:`LongTensor`, :class:`Tensor`)
     """

torch_sparse/transpose.py

@@ -8,8 +8,8 @@ def transpose(index, value, m, n):
     Args:
         index (:class:`LongTensor`): The index tensor of sparse matrix.
         value (:class:`Tensor`): The value tensor of sparse matrix.
-        m (int): The first dimension of sparse matrix.
-        n (int): The second dimension of sparse matrix.
+        m (int): The first dimension of corresponding dense matrix.
+        n (int): The second dimension of corresponding dense matrix.
 
     :rtype: (:class:`LongTensor`, :class:`Tensor`)
     """