Lines Matching full:sparse_coo_tensor
121 " Please use torch.sparse_coo_tensor((0,), dtype=)"
122 x_ref = torch.sparse_coo_tensor((0,), dtype=torch.float64)
128 " Please use torch.sparse_coo_tensor(x._indices(), x._values(), x.shape)"
131 y = torch.sparse_coo_tensor(x._indices(), x._values(), x.shape)
137 " Please use torch.sparse_coo_tensor(indices, values, dtype=, device=)"
138 … x_ref = torch.sparse_coo_tensor([[0, 0, 1, 1], [0, 1, 0, 1]], [1, 2, 3, 4], dtype=torch.float64)
145 " Please use torch.sparse_coo_tensor(indices, values, shape, dtype=, device=)"
146 …x_ref = torch.sparse_coo_tensor([[0, 0, 1, 1], [0, 1, 0, 1]], [1, 2, 3, 4], (2, 3), dtype=torch.fl…
153 " Please use torch.sparse_coo_tensor(shape, dtype=, device=)"
154 x_ref = torch.sparse_coo_tensor((2, 3), dtype=torch.float64)
189 return torch.sparse_coo_tensor(*args, **kwargs)
387 S = torch.sparse_coo_tensor(i, v)
408 lambda: torch.sparse_coo_tensor(
443 …s = torch.sparse_coo_tensor(indices, values, shape, check_invariants=True, is_coalesced=is_coalesc…
915 x = torch.sparse_coo_tensor((2, 3, 4), dtype=torch.float32)
918 x = torch.sparse_coo_tensor((2, 3, 4), dtype=torch.float16)
921 x = torch.sparse_coo_tensor((2, 3, 4), dtype=torch.float16)
924 x = torch.sparse_coo_tensor((2, 3, 4, 0), dtype=torch.float32)
1060 zeros = torch.sparse_coo_tensor(sizes, device=x.device)
1194 s = torch.sparse_coo_tensor(idx, val, size=(3, 3))
1537 weight = torch.sparse_coo_tensor(
1842 empty_S = torch.sparse_coo_tensor(size=with_size, dtype=dtype, device=device)
2148 lhs = torch.sparse_coo_tensor(
2154 rhs = torch.sparse_coo_tensor(
2234 sparse_zeros = torch.sparse_coo_tensor(dense_tensor.shape)
2281 input_coalesced = torch.sparse_coo_tensor(
2291 input_coalesced = torch.sparse_coo_tensor(
2302 input_uncoalesced = torch.sparse_coo_tensor(
2312 input_uncoalesced = torch.sparse_coo_tensor(
2377 input_coalesced = torch.sparse_coo_tensor(
2387 input_coalesced = torch.sparse_coo_tensor(
2398 input_uncoalesced = torch.sparse_coo_tensor(
2408 input_uncoalesced = torch.sparse_coo_tensor(
2442 input_coalesced = torch.sparse_coo_tensor(
2452 input_coalesced = torch.sparse_coo_tensor(
2463 input_uncoalesced = torch.sparse_coo_tensor(
2473 input_uncoalesced = torch.sparse_coo_tensor(
2522 input_coalesced = torch.sparse_coo_tensor(
2532 input_coalesced = torch.sparse_coo_tensor(
2543 input_uncoalesced = torch.sparse_coo_tensor(
2553 input_uncoalesced = torch.sparse_coo_tensor(
2611 x = torch.sparse_coo_tensor((2,), dtype=torch.float32, device=device)
2614 x = torch.sparse_coo_tensor((2, 0), dtype=torch.float32, device=device)
2645 x = torch.sparse_coo_tensor(size, device='cuda', dtype=torch.float64)
2711 … sparse_tensor = torch.sparse_coo_tensor(indices, values, size, dtype=dtype,
2714 … sparse_tensor = torch.sparse_coo_tensor(indices, values, dtype=dtype,
2731 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2735 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2742 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2749 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2756 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2763 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2766 tensor = torch.sparse_coo_tensor(torch.Size([2, 0]), device=device)
2770 tensor = torch.sparse_coo_tensor(torch.Size([2, 2, 0]), device=device)
2774 tensor = torch.sparse_coo_tensor(torch.Size([2, 2, 0, 0]), device=device)
2784 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2790 torch.sparse_coo_tensor(indices, values, sizes, dtype=dtype, device=device)
2796 … t = torch.sparse_coo_tensor(torch.empty(i_shape), torch.empty(v_shape), torch.Size(size),
2799 …t = torch.sparse_coo_tensor(torch.empty(i_shape), torch.empty(v_shape), dtype=dtype, device=device)
2819 torch.sparse_coo_tensor(indices, values, sizes)
2825 torch.sparse_coo_tensor(indices, values, sizes)
2830 t = torch.sparse_coo_tensor(torch.tensor(([0], [2])), torch.tensor([1.], dtype=dtype))
2832 t = torch.sparse_coo_tensor(torch.tensor(([0], [2])), torch.tensor([1]))
2835 t = torch.sparse_coo_tensor(torch.tensor(([0], [2])), torch.HalfTensor(1, 0))
2837 t = torch.sparse_coo_tensor(torch.tensor(([0], [2])), torch.FloatTensor(1, 0))
2839 t = torch.sparse_coo_tensor(torch.tensor(([0], [2])), torch.DoubleTensor(1, 0))
2841 t = torch.sparse_coo_tensor(torch.tensor(([0], [2])), torch.LongTensor(1, 0))
2860 torch.sparse_coo_tensor(indices, values, shape, device=device)
2862 torch.sparse_coo_tensor(indices, empty_values, empty_shape, device=device)
2864 t = torch.sparse_coo_tensor(indices, values, shape, device=device)
2865 t_empty = torch.sparse_coo_tensor(indices, empty_values, empty_shape, device=device)
2873 … sparse_tensor = torch.sparse_coo_tensor(indices, values, dtype=torch.float64, device=device)
2938 x = torch.sparse_coo_tensor(i, v, size, device='cpu')
2945 x = torch.sparse_coo_tensor(i, v, size, device='cuda')
2955 s = torch.sparse_coo_tensor(i, v, size)
2985 v = torch.sparse_coo_tensor(shape, dtype=dtype, device=device, requires_grad=requires_grad)
3034 x = torch.sparse_coo_tensor(torch.zeros(x_i),
3038 y = torch.sparse_coo_tensor(torch.zeros(y_i),
3119 self.assertTrue(torch.sparse_coo_tensor(([0],), 1., (1,), device=device).is_nonzero())
3120 self.assertFalse(torch.sparse_coo_tensor(([0],), 0., (1,), device=device).is_nonzero())
3121 … self.assertFalse(torch.sparse_coo_tensor(([0], [0]), 0., (1, 1), device=device).is_nonzero())
3122 … self.assertFalse(torch.sparse_coo_tensor(([0, 0],), (0., 0.), (1,), device=device).is_nonzero())
3123 … self.assertFalse(torch.sparse_coo_tensor(([0, 0],), (-1., 1.), (1,), device=device).is_nonzero())
3126 … self.assertTrue(torch.sparse_coo_tensor(torch.zeros(0, 1), 12.3, [], device=device).is_nonzero())
3128 … torch.sparse_coo_tensor(([0, 1],), torch.empty(2, 0), (4, 0), device=device).is_nonzero()
3129 …self.assertTrue(torch.sparse_coo_tensor(([0],), 2.3 - 4.5j, (1,), dtype=torch.cfloat, device=devic…
3131 …self.assertTrue(torch.sparse_coo_tensor(([0],), 2.3 - 4.5j, (1,), dtype=torch.cdouble, device=devi…
3133 … self.assertFalse(torch.sparse_coo_tensor(([0],), 0. + 0j, (1,), dtype=torch.cfloat, device=device)
3135 …self.assertFalse(torch.sparse_coo_tensor(([0],), 0. + 0j, (1,), dtype=torch.cdouble, device=device)
3142 t = torch.sparse_coo_tensor(i, v, torch.Size([1, 2, 3]), dtype=dtype, device=device)
3150 t = torch.sparse_coo_tensor(i, v, torch.Size([1, 2, 3]))
3158 t = torch.sparse_coo_tensor(i, v, torch.Size([1, 2, 3]))
3166 t = torch.sparse_coo_tensor(i, v, torch.Size([1, 2, 3]))
3174 t = torch.sparse_coo_tensor(i, v, torch.Size([1, 2, 3]))
3213 …t = torch.sparse_coo_tensor(torch.tensor(([0, 0], [2, 0])), torch.tensor([False, False]), device=d…
3216 …t = torch.sparse_coo_tensor(torch.tensor(([0, 0], [2, 0])), torch.tensor([True, False]), device=de…
3221 … t = torch.sparse_coo_tensor(torch.tensor(([0, 0], [0, 2])), torch.tensor([1, 4]), device=device)
3222 …t_nan = torch.sparse_coo_tensor(torch.tensor(([0, 0], [0, 2])), torch.tensor([False, False]), devi…
3224 …t = torch.sparse_coo_tensor(torch.tensor(([0, 0], [0, 2])), torch.tensor([1, float("nan")]), devic…
3225 …t_nan = torch.sparse_coo_tensor(torch.tensor(([0, 0], [0, 2])), torch.tensor([False, True]), devic…
3262 t = torch.sparse_coo_tensor(torch.tensor(([0, 0], [2, 0])), torch.tensor([1, 4]))
3361 return torch.sparse_coo_tensor(indices,
3367 return torch.sparse_coo_tensor(indices,
3442 v = torch.sparse_coo_tensor(indices, values, shape, dtype=dtype, device=device)
3479 return torch.sparse_coo_tensor(x._indices(), x._values().log(),
3568 …t = torch.sparse_coo_tensor([[] for _ in range(ndim)], [], (0,) * (ndim - 1) + (3,), device=device…
3743 …self.assertEqual(s_res, torch.sparse_coo_tensor(s_res._indices(), s_res._values(), s_res.shape).co…
3902 sscalar = torch.sparse_coo_tensor(idx, val, ())
4008 self.assertTrue(torch.sparse_coo_tensor([[], []], [], (2, 2)).is_coalesced())
4010 self.assertTrue(torch.sparse_coo_tensor([[0], [0]], [1], (2, 2)).is_coalesced())
4012 self.assertFalse(torch.sparse_coo_tensor([[0, 0], [0, 0]], [1, 2], (2, 2)).is_coalesced())
4014 self.assertFalse(torch.sparse_coo_tensor([[0, 1], [0, 1]], [1, 2], (2, 2)).is_coalesced())
4040 torch.sparse_coo_tensor(torch.zeros(1, 4).long().cuda(),
4047 torch.sparse_coo_tensor(torch.zeros(1, 4).long().cuda(),
4054 torch.sparse_coo_tensor(torch.empty(1, 0).long().cuda(),
4061 sparse_y = torch.sparse_coo_tensor(torch.zeros(1, 4).long().cuda(),
4068 sparse_y = torch.sparse_coo_tensor(torch.zeros(1, 4).long().cuda(),
4075 sparse_y = torch.sparse_coo_tensor(torch.empty(1, 0).long().cuda(),
4116 out = torch.sparse_coo_tensor(sample.input.shape, device=device,
4141 # test 0x0 sparse_coo_tensor
4144 sparse_0x0 = torch.sparse_coo_tensor(indices, values, (0, 0))
4145 expected = torch.sparse_coo_tensor(indices, op(values), (0, 0))
4154 sparse_input = torch.sparse_coo_tensor((), dtype=dtype, device=device)
4246 r3 = torch.sparse_coo_tensor(size=(4, 4), device='meta', dtype=dtype)
4336 x = torch.sparse_coo_tensor(indices, values, shape)
4519 return torch.sparse_coo_tensor(invalid_indices, values, shape)
4521 … return torch.sparse_coo_tensor(invalid_indices, values, shape, check_invariants=check_invariants)
4726 return torch.sparse_coo_tensor(*args, **kwargs)
4735 return torch.sparse_coo_tensor(*args, **kwargs)
5244 ones = torch.sparse_coo_tensor(mask._indices(),
5464 return torch.sparse_coo_tensor(*args, **kwargs)