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support creating Tensor from python tuple (#4944)

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added a small fuzzer to test data with mixed tuple and list of numbers matched with numpy
This commit is contained in:
chenyu
2024-06-13 12:18:37 -04:00
committed by GitHub
parent 74586bc339
commit 7aecea4f56
2 changed files with 14 additions and 2 deletions
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14
test/test_tensor.py
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@@ -1,6 +1,6 @@
import numpy as np
import torch
import unittest, copy, mmap
import unittest, copy, mmap, random
from tinygrad import Tensor, Device, dtypes
from tinygrad.helpers import getenv, temp, CI
from extra.gradcheck import numerical_jacobian, jacobian, gradcheck
@@ -288,6 +288,18 @@ class TestTinygrad(unittest.TestCase):
with self.assertRaises(ValueError): Tensor([[[1,1,1],[1,1]]])
with self.assertRaises(ValueError): Tensor([[1,1,1],[[1,1,1]]])
def test_tensor_mixed_list_tuple(self):
def _list_or_tuple(): return list if random.random() < 0.5 else tuple
def _generate_data(depth):
if depth == 0: return _list_or_tuple()()
if depth == 1: return _list_or_tuple()([random.random(), random.random()])
return _list_or_tuple()([_generate_data(depth-1), _generate_data(depth-1)])
for depth in range(7):
for _ in range(20):
data = _generate_data(depth)
np.testing.assert_allclose(Tensor(data).numpy(), np.array(data))
def test_tensor_copy(self):
x = copy.deepcopy(Tensor.ones((3,3,3)))
np.testing.assert_allclose(x.numpy(), np.ones((3,3,3)))