mirror of https://github.com/commaai/tinygrad.git
136 lines
4.5 KiB
Python
136 lines
4.5 KiB
Python
import unittest
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from tinygrad import Tensor, TinyJit, Variable, dtypes
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import numpy as np
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class TestSetitem(unittest.TestCase):
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def test_simple_setitem(self):
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cases = (
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((6,6), (slice(2,4), slice(3,5)), Tensor.ones(2,2)),
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((6,6), (slice(2,4), slice(3,5)), Tensor([1.,2.])),
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((6,6), (slice(2,4), slice(3,5)), 1.0),
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((6,6), (3, 4), 1.0),
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((6,6), (3, None, 4, None), 1.0),
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((4,4,4,4), (Ellipsis, slice(1,3), slice(None)), Tensor(4)),
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((4,4,4,4), (Ellipsis, slice(1,3)), 4),
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((4,4,4,4), (2, slice(1,3), None, 1), 4),
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((4,4,4,4), (slice(1,3), slice(None), slice(0,4,2)), 4),
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((4,4,4,4), (slice(1,3), slice(None), slice(None), slice(0,3)), 4),
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((6,6), (slice(1,5,2), slice(0,5,3)), 1.0),
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((6,6), (slice(5,1,-2), slice(5,0,-3)), 1.0),
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)
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for shp, slc, val in cases:
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t = Tensor.zeros(shp).contiguous()
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t[slc] = val
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n = np.zeros(shp)
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n[slc] = val.numpy() if isinstance(val, Tensor) else val
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np.testing.assert_allclose(t.numpy(), n)
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def test_setitem_into_unrealized(self):
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t = Tensor.arange(4).reshape(2, 2)
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t[1] = 5
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np.testing.assert_allclose(t.numpy(), [[0, 1], [5, 5]])
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def test_setitem_dtype(self):
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for dt in (dtypes.int, dtypes.float, dtypes.bool):
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for v in (5., 5, True):
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t = Tensor.ones(6,6, dtype=dt).contiguous()
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t[1] = v
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assert t.dtype == dt
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def test_setitem_into_noncontiguous(self):
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t = Tensor.ones(4)
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assert not t.lazydata.st.contiguous
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with self.assertRaises(RuntimeError): t[1] = 5
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def test_setitem_inplace_operator(self):
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t = Tensor.arange(4).reshape(2, 2).contiguous()
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t[1] += 2
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np.testing.assert_allclose(t.numpy(), [[0, 1], [4, 5]])
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t = Tensor.arange(4).reshape(2, 2).contiguous()
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t[1] -= 1
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np.testing.assert_allclose(t.numpy(), [[0, 1], [1, 2]])
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t = Tensor.arange(4).reshape(2, 2).contiguous()
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t[1] *= 2
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np.testing.assert_allclose(t.numpy(), [[0, 1], [4, 6]])
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# NOTE: have to manually cast setitem target to least_upper_float for div
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t = Tensor.arange(4, dtype=dtypes.float).reshape(2, 2).contiguous()
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t[1] /= 2
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np.testing.assert_allclose(t.numpy(), [[0, 1], [1, 1.5]])
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t = Tensor.arange(4).reshape(2, 2).contiguous()
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t[1] **= 2
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np.testing.assert_allclose(t.numpy(), [[0, 1], [4, 9]])
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t = Tensor.arange(4).reshape(2, 2).contiguous()
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t[1] ^= 5
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np.testing.assert_allclose(t.numpy(), [[0, 1], [7, 6]])
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@unittest.expectedFailure
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def test_setitem_consecutive_inplace_operator(self):
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t = Tensor.arange(4).reshape(2, 2).contiguous()
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t[1] += 2
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t = t.contiguous()
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# TODO: RuntimeError: must be contiguous for assign ShapeTracker(views=(View(shape=(2,), strides=(1,), offset=2, mask=None, contiguous=False),))
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t[1] -= 1
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np.testing.assert_allclose(t.numpy(), [[0, 1], [3, 4]])
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def test_fancy_setitem(self):
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t = Tensor.zeros(6,6).contiguous()
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t[[1,2], [3,2]] = 3
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n = np.zeros((6,6))
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n[[1,2], [3,2]] = 3
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np.testing.assert_allclose(t.numpy(), n)
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def test_simple_jit_setitem(self):
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@TinyJit
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def f(t:Tensor, a:Tensor):
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t[2:4, 3:5] = a
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for i in range(1, 6):
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t = Tensor.zeros(6, 6).contiguous().realize()
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a = Tensor.full((2, 2), fill_value=i, dtype=dtypes.float).contiguous()
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f(t, a)
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n = np.zeros((6, 6))
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n[2:4, 3:5] = np.full((2, 2), i)
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np.testing.assert_allclose(t.numpy(), n)
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def test_jit_setitem_variable_offset(self):
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@TinyJit
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def f(t:Tensor, a:Tensor, v:Variable):
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t.shrink(((v,v+1), None)).assign(a).realize()
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t = Tensor.zeros(6, 6).contiguous().realize()
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n = np.zeros((6, 6))
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for i in range(6):
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v = Variable("v", 0, 6).bind(i)
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a = Tensor.full((1, 6), fill_value=i+1, dtype=dtypes.float).contiguous()
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n[i, :] = i+1
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f(t, a, v)
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np.testing.assert_allclose(t.numpy(), n)
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np.testing.assert_allclose(t.numpy(), [[1,1,1,1,1,1],[2,2,2,2,2,2],[3,3,3,3,3,3],[4,4,4,4,4,4],[5,5,5,5,5,5],[6,6,6,6,6,6]])
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class TestWithGrad(unittest.TestCase):
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def test_no_requires_grad_works(self):
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z = Tensor.rand(8, 8)
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x = Tensor.rand(8)
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z[:3] = x
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def test_set_into_requires_grad(self):
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z = Tensor.rand(8, 8, requires_grad=True)
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x = Tensor.rand(8)
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with self.assertRaises(NotImplementedError):
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z[:3] = x
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def test_set_with_requires_grad(self):
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z = Tensor.rand(8, 8)
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x = Tensor.rand(8, requires_grad=True)
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with self.assertRaises(NotImplementedError):
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z[:3] = x
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if __name__ == '__main__':
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unittest.main() |