github/tinygrad
1
1
Fork 0
mirror of https://github.com/tinygrad/tinygrad.git synced 2026-01-09 15:08:02 -05:00
Code Issues Packages Projects Releases Wiki Activity

Revert "Make Tensor creation allow multi-dim list of int and bool (#2793)" (#2810)

Browse Source 
This reverts commit 798bf813b1.
This commit is contained in:
chenyu
2023-12-17 02:03:52 -05:00
committed by GitHub
parent 798bf813b1
commit 71a60762ed
4 changed files with 7 additions and 57 deletions
Download Patch File Download Diff File Expand all files Collapse all files

44
test/test_tensor.py
View File

@@ -239,46 +239,10 @@ class TestTinygrad(unittest.TestCase):
assert Tensor(arr, dtype=dtypes.float64).dtype == dtypes.float64 # check that it works for something else
def test_tensor_list_dtype(self):
for arr in ([1], [[[1]]], [[1,1],[1,1]], [[[1,1],[1,1]],[[1,1],[1,1]]]):
assert Tensor(arr).dtype == dtypes.int32
assert Tensor(arr, dtype=dtypes.float32).dtype == dtypes.float32
assert Tensor(arr, dtype=dtypes.float64).dtype == dtypes.float64
for arr in ([True], [[[False]]], [[True,False],[True,False]], [[[False,True],[False,False]],[[True,True],[False,True]]]):
assert Tensor(arr).dtype == dtypes.bool
assert Tensor(arr, dtype=dtypes.float32).dtype == dtypes.float32
assert Tensor(arr, dtype=dtypes.float64).dtype == dtypes.float64
# empty tensor defaults
for arr in ([], [[[]]], [[],[]]):
t = Tensor(arr)
assert t.dtype == Tensor.default_type
np.testing.assert_allclose(t.numpy(), np.array(arr))
# mixture of bool and int
for arr in ([True, 3], [[True],[3]], [[[True]], [[3]]], [[True, 3], [3, True]]):
t = Tensor(arr)
assert t.dtype == dtypes.int32
np.testing.assert_allclose(t.numpy(), np.array(arr))
# mixture of bool, int and float
for arr in ([[True,True],[3.,True]], [[0,1],[3.,4]], [[[0],[1]],[[3.],[4]]], [[[True],[1]],[[3.],[4]]]):
t = Tensor(arr)
assert t.dtype == Tensor.default_type
np.testing.assert_allclose(t.numpy(), np.array(arr))
def test_tensor_list_shapes(self):
self.assertEqual(Tensor([[[]]]).shape, (1,1,0))
self.assertEqual(Tensor([[],[]]).shape, (2,0))
self.assertEqual(Tensor([[[[]],[[]]], [[[]],[[]]], [[[]],[[]]]]).shape, (3,2,1,0))
def test_tensor_list_errors(self):
# inhomogeneous shape
with self.assertRaises(ValueError): Tensor([[],[[]]])
with self.assertRaises(ValueError): Tensor([[1],[]])
with self.assertRaises(ValueError): Tensor([[1],[1],1])
with self.assertRaises(ValueError): Tensor([[[1,1,1],[1,1]]])
with self.assertRaises(ValueError): Tensor([[1,1,1],[[1,1,1]]])
arr = [1]
assert Tensor(arr).dtype == dtypes.int32
assert Tensor(arr, dtype=dtypes.float32).dtype == dtypes.float32
assert Tensor(arr, dtype=dtypes.float64).dtype == dtypes.float64
def test_tensor_copy(self):
x = copy.deepcopy(Tensor.ones((3,3,3)))