chainer/utils/sparse.py

8 def _add_at(add_at, x, row, col, data):  argument
9     assert data.size > 0
10     last_nz = data.size - (data != 0)[::-1].argmax()
11     add_at(x, (row[:last_nz], col[:last_nz]), data[:last_nz])
43     def __init__(self, data, row, col, shape, order=None,  argument
45         if not (1 <= data.ndim <= 2):
47         if not (data.ndim == row.ndim == col.ndim):
49         if len(shape) != 2:
51         if not (shape[0] > 0 and shape[1] > 0):
56         self.data = chainer.Variable(data, requires_grad=requires_grad)
59         self.shape = shape  # (row, col)
66         data = self.data
67         if data.ndim == 1:
68             shape = self.shape
69         elif data.ndim == 2:
70             shape = (data.shape[0], *self.shape)
74         xp = data.xp
75         x = xp.zeros(shape, dtype=data.dtype)
77         if data.size > 0:
85             data = data.array
86             if data.ndim == 1:
87                 _add_at(add_at, x, row, col, data)
88             elif data.ndim == 2:
89                 for i in range(data.shape[0]):
90                     _add_at(add_at, x[i], row[i], col[i], data[i])
138         data = xp.zeros((ldnz), dtype=x.dtype)
141         data[:nnz] = x[_row, _col]
144         shape = x.shape
145         return CooMatrix(data, row, col, shape,
149         nb = x.shape[0]
154         data = xp.empty((nb, ldnz), dtype=x.dtype)
159             data[i] = coo.data.data
162         shape = x.shape[1:]
163         return CooMatrix(data, row, col, shape,
193     if row.shape != col.shape:
196         for i in range(row.shape[0]):
205     if _row.shape[0] <= 1:
207     row_diff = xp.zeros(_row.shape, dtype=_row.dtype)
211     col_diff = xp.zeros(_col.shape, dtype=_col.dtype)