101 lines
3.0 KiB
Python
101 lines
3.0 KiB
Python
import unittest
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import numpy as np
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from tinygrad import Tensor, Variable
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class TestTensorVariable(unittest.TestCase):
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def test_add_tvar(self):
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vv = Variable("a", 0, 10).bind(1)
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ret = (Tensor(vv) + 3).item()
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assert ret == 4
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def test_inner_tvar_node(self):
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vv = Variable("w", 0, 10).bind(2)
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ret = Tensor.from_uop(vv * 4).item()
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assert ret == 8
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def test_inner_tvar_mul(self):
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vv = Variable("w", 0, 10).bind(2)
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assert (Tensor(3) * vv).item() == 6
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def test_inner_tvar_mul_node(self):
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vv = Variable("w", 0, 10).bind(2)
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assert (Tensor(3) * (vv * 4)).item() == 24
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def test_symbolic_mean(self):
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vv = Variable("a", 1, 10).bind(2)
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t = Tensor.ones(2, 10).contiguous()[:, :vv]
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ret = t.mean().item()
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assert ret == 1
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def test_symbolic_mean_2d(self):
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vv = Variable("a", 1, 10).bind(2)
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vv2 = Variable("b", 1, 10).bind(2)
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t = Tensor.ones(10, 10).contiguous()[:vv2, :vv]
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ret = t.mean().item()
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assert ret == 1
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def test_symbolic_mean_2d_axis_1(self):
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vv = Variable("a", 1, 10).bind(2)
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vv2 = Variable("b", 1, 10).bind(2)
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t = Tensor.ones(10, 10).contiguous()[:vv2, :vv]
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ret = t.mean(axis=1)[:2].reshape(2, 1).numpy()
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assert np.all(ret == 1)
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def test_symbolic_mean_2d_add(self):
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add_term = Variable("c", 0, 10).bind(1)
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vv = Variable("a", 1, 10).bind(1)
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vv2 = Variable("b", 1, 10).bind(1)
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t = Tensor.ones(20, 20).contiguous()[:vv2+add_term, :vv+add_term]
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ret = t.mean().item()
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assert ret == 1
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def test_symbolic_var(self):
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vv = Variable("a", 1, 10).bind(2)
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t = Tensor.ones(2, 10).contiguous()[:, :vv]
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ret = t.var().item()
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assert ret == 0
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def test_symbolic_pad(self):
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vv = Variable("a", 1, 10).bind(2)
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t = Tensor.ones(2, 2).contiguous()
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t = t.pad([vv, vv, vv, vv]).mean()
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ones = 4
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zeros = 6+6+4+4+6+6
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self.assertAlmostEqual(t.item(), ones/(ones+zeros))
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def test_symbolic_arange(self):
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vv = Variable("a", 1, 10)
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ret = Tensor.arange(0, vv.bind(4))
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self.assertListEqual(ret[:4].tolist(), [0,1,2,3])
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def test_symbolic_arange_sym_start(self):
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vv = Variable("a", 1, 6)
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ret = Tensor.arange(vv.bind(4), 7)
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self.assertListEqual(ret[:3].tolist(), [4,5,6])
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# TODO: add vmin/vmax pattern for symbolic denominator
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@unittest.expectedFailure
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def test_symbolic_arange_sym_step(self):
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vv = Variable("step", 1, 3)
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ret = Tensor.arange(0, 10, vv.bind(2))
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self.assertListEqual(ret[:5].tolist(), [0,2,4,6,8])
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def test_symbolic_arange_two_vars(self):
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begin = Variable("b", 1, 5)
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end = Variable("e", 6, 10)
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ret = Tensor.arange(begin.bind(4), end.bind(7))
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self.assertListEqual(ret[:3].tolist(), [4,5,6])
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def test_variable_empty(self):
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v = Variable("i", 1, 10)
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# TODO: Tensor creation from unbound variable should assert
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# with self.assertRaises(AssertionError): t = Tensor.empty(3, v)
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vb = v.bind(3)
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t = Tensor.empty(3, vb)
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assert t.uop.base.buffer.size == 30
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assert t.uop.st.shape == (3, vb)
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if __name__ == '__main__':
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unittest.main()
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