def test_basicSD(self):
for mtype in _mtypes:
x = as_sparse_variable(mtype((500, 3)))
x.data[(10, 1)] = 1
x.data[(20, 2)] = 2
self.assertTrue(_is_sparse_variable(x))
y = tensor.as_tensor_variable([[1., 2], [3, 4], [2, 1]])
self.assertTrue(_is_dense_variable(y))
zop = true_dot(x, y)
self.assertTrue(_is_sparse_variable(zop))
z = eval_outputs([zop])
self.assertTrue(_is_sparse(z))
self.assertTrue(z.shape == (500, 2))
self.assertTrue(type(z) is mtype)
w = mtype((500, 2))
w[(10, 0)] = 3.
w[(20, 0)] = 4
w[(10, 1)] = 4
w[(20, 1)] = 2
self.assertTrue(z.shape == w.shape)
self.assertTrue(type(z) == type(w))
self.assertTrue(z.dtype == w.dtype)
#self.assertTrue(z == w)
self.assertTrue(abs(z - w).nnz == 0)
z = z.todense()
w = w.todense()
self.assertTrue((z == w).all() == True)
def test_basicSS(self):
for mtype in _mtypes:
x = as_sparse_variable(mtype((500, 3)))
x.data[(10, 1)] = 1
x.data[(20, 2)] = 2
self.assertTrue(_is_sparse_variable(x))
xT = x.T
self.assertTrue(_is_sparse_variable(xT))
zop = true_dot(x, xT)
self.assertTrue(_is_sparse_variable(zop))
z = eval_outputs([zop])
self.assertTrue(_is_sparse(z))
self.assertTrue(z.shape == (500, 500))
self.assertTrue(type(z) is mtype)
w = mtype((500, 500))
w[(10, 10)] = 1
w[(20, 20)] = 4
self.assertTrue(z.shape == w.shape)
self.assertTrue(type(z) == type(w))
self.assertTrue(z.dtype == w.dtype)
#self.assertTrue(z == w)
self.assertTrue(abs(z - w).nnz == 0)
z = z.todense()
w = w.todense()
self.assertTrue((z == w).all() == True)
def test_basicSS(self):
for mtype in _mtypes:
x = as_sparse_variable(mtype((500,3)))
x.data[(10, 1)] = 1
x.data[(20, 2)] = 2
self.assertTrue(_is_sparse_variable(x))
xT = x.T
self.assertTrue(_is_sparse_variable(xT))
zop = true_dot(x,xT)
self.assertTrue(_is_sparse_variable(zop))
z = eval_outputs([zop])
self.assertTrue(_is_sparse(z))
self.assertTrue(z.shape == (500,500))
self.assertTrue(type(z) is mtype)
w = mtype((500,500))
w[(10, 10)] = 1
w[(20, 20)] = 4
self.assertTrue(z.shape == w.shape)
self.assertTrue(type(z) == type(w))
self.assertTrue(z.dtype == w.dtype)
#self.assertTrue(z == w)
self.assertTrue(abs(z-w).nnz == 0)
z = z.todense()
w = w.todense()
self.assertTrue((z == w).all() == True)
def test_basicSD(self):
for mtype in _mtypes:
x = as_sparse_variable(mtype((500,3)))
x.data[(10, 1)] = 1
x.data[(20, 2)] = 2
self.assertTrue(_is_sparse_variable(x))
y = tensor.as_tensor_variable([[1., 2], [3, 4], [2, 1]])
self.assertTrue(_is_dense_variable(y))
zop = true_dot(x,y)
self.assertTrue(_is_sparse_variable(zop))
z = eval_outputs([zop])
self.assertTrue(_is_sparse(z))
self.assertTrue(z.shape == (500,2))
self.assertTrue(type(z) is mtype)
w = mtype((500,2))
w[(10, 0)] = 3.
w[(20, 0)] = 4
w[(10, 1)] = 4
w[(20, 1)] = 2
self.assertTrue(z.shape == w.shape)
self.assertTrue(type(z) == type(w))
self.assertTrue(z.dtype == w.dtype)
#self.assertTrue(z == w)
self.assertTrue(abs(z-w).nnz == 0)
z = z.todense()
w = w.todense()
self.assertTrue((z == w).all() == True)
def test_basicDS(self):
for mtype in _mtypes:
x = as_sparse_variable(mtype((500, 3)))
x.data[(10, 1)] = 1
x.data[(20, 2)] = 2
self.assertTrue(_is_sparse_variable(x))
y = tensor.as_tensor_variable([[1., 2], [3, 4], [2, 1]])
self.assertTrue(_is_dense_variable(y))
x.data = x.data.T
y.data = y.data.T
zop = true_dot(y, x)
zop = transpose(true_dot(y, x))
self.assertTrue(_is_sparse_variable(zop))
z = eval_outputs([zop])
self.assertTrue(_is_sparse(z))
self.assertTrue(z.shape == (500, 2))
# self.assertTrue(type(z) is mtype)
w = mtype((500, 2))
w[(10, 0)] = 3.
w[(20, 0)] = 4
w[(10, 1)] = 4
w[(20, 1)] = 2
self.assertTrue(z.shape == w.shape)
# Type should switch from csr to csc and vice-versa, so don't perform this test
#self.assertTrue(type(z) == type(w))
self.assertTrue(z.dtype == w.dtype)
# Type should switch from csr to csc and vice-versa, so don't perform this test
#self.assertTrue(z == w)
self.assertTrue(abs(z - w).nnz == 0)
z = z.todense()
w = w.todense()
self.assertTrue((z == w).all() == True)
def test_basicDS(self):
for mtype in _mtypes:
x = as_sparse_variable(mtype((500,3)))
x.data[(10, 1)] = 1
x.data[(20, 2)] = 2
self.assertTrue(_is_sparse_variable(x))
y = tensor.as_tensor_variable([[1., 2], [3, 4], [2, 1]])
self.assertTrue(_is_dense_variable(y))
x.data = x.data.T
y.data = y.data.T
zop = true_dot(y, x)
zop = transpose(true_dot(y, x))
self.assertTrue(_is_sparse_variable(zop))
z = eval_outputs([zop])
self.assertTrue(_is_sparse(z))
self.assertTrue(z.shape == (500,2))
# self.assertTrue(type(z) is mtype)
w = mtype((500,2))
w[(10, 0)] = 3.
w[(20, 0)] = 4
w[(10, 1)] = 4
w[(20, 1)] = 2
self.assertTrue(z.shape == w.shape)
# Type should switch from csr to csc and vice-versa, so don't perform this test
#self.assertTrue(type(z) == type(w))
self.assertTrue(z.dtype == w.dtype)
# Type should switch from csr to csc and vice-versa, so don't perform this test
#self.assertTrue(z == w)
self.assertTrue(abs(z-w).nnz == 0)
z = z.todense()
w = w.todense()
self.assertTrue((z == w).all() == True)
