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tinygrad
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Tensor.randint is Tensor.uniform with dtypes.int32 (#2801)

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chenyu 2023-12-16 15:14:50 -05:00 committed by GitHub
parent 0bb5d8f956
commit 86c2f267d4
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2 changed files with 5 additions and 2 deletions
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4
test/test_randomness.py
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@ -63,6 +63,10 @@ class TestRandomness(unittest.TestCase):
self.assertTrue(normal_test(Tensor.randn)) self.assertTrue(normal_test(Tensor.randn))
self.assertTrue(equal_distribution(Tensor.randn, torch.randn, lambda x: np.random.randn(*x))) self.assertTrue(equal_distribution(Tensor.randn, torch.randn, lambda x: np.random.randn(*x)))
def test_randint(self):
self.assertFalse(normal_test(Tensor.randint))
self.assertTrue(equal_distribution(partial(Tensor.randint, low=-2, high=5), numpy_func=lambda x: np.random.randint(low=-2, high=5, size=x)))
def test_normal(self): def test_normal(self):
self.assertTrue(normal_test(Tensor.normal)) self.assertTrue(normal_test(Tensor.normal))
self.assertTrue(equal_distribution(Tensor.normal, lambda x: torch.nn.init.normal_(torch.empty(x), mean=0, std=1), lambda x: np.random.normal(loc=0, scale=1, size=x))) self.assertTrue(equal_distribution(Tensor.normal, lambda x: torch.nn.init.normal_(torch.empty(x), mean=0, std=1), lambda x: np.random.normal(loc=0, scale=1, size=x)))

3
tinygrad/tensor.py
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@ -199,8 +199,7 @@ class Tensor:
return src[0].mul(2*math.pi).cos().mul((1 - src[1]).log().mul(-2).sqrt()).cast(Tensor.default_type if dtype is None else dtype) return src[0].mul(2*math.pi).cos().mul((1 - src[1]).log().mul(-2).sqrt()).cast(Tensor.default_type if dtype is None else dtype)
@staticmethod @staticmethod
def randint(*shape, low=0, high=10, **kwargs) -> Tensor: def randint(*shape, low=0, high=10, **kwargs) -> Tensor: return Tensor.uniform(shape, low=low, high=high, dtype=dtypes.int32)
return (Tensor.rand(*shape, **kwargs)*(high-low)+low).cast(dtypes.int32)
@staticmethod @staticmethod
def normal(*shape, mean=0.0, std=1.0, **kwargs) -> Tensor: return (std * Tensor.randn(*shape, **kwargs)) + mean def normal(*shape, mean=0.0, std=1.0, **kwargs) -> Tensor: return (std * Tensor.randn(*shape, **kwargs)) + mean