import unittest from tinygrad import Tensor, UOp from tinygrad.uop.ops import AxisType, Ops class TestOuterworldReduce(unittest.TestCase): def test_reduce(self): x = Tensor.ones(5, 5).contiguous() a = UOp.range(5, -1, AxisType.REDUCE) out = x[a] # TODO: syntax for this t = Tensor(UOp(Ops.REDUCE, dtype=out.uop.dtype, src=(out.uop, a), arg=Ops.ADD)) self.assertListEqual(t.tolist(), [5.,5.,5.,5.,5.]) class TestOuterworld(unittest.TestCase): def test_range_plus_1(self): t = Tensor.arange(100).reshape(10,10).realize() # passthrough ranges a = UOp.range(10, -1) sel = t[a] + 1 assert sel.shape == (10,) cpy = sel.reshape(1, 10).expand(a, 10).contiguous().realize() self.assertTrue((t+1==cpy).all().item()) def test_range_plus_1_transpose(self): t = Tensor.arange(100).reshape(10,10).realize() # passthrough ranges a = UOp.range(10, -1) sel = t[a] + 1 assert sel.shape == (10,) cpy = sel.reshape(10, 1).expand(10, a).contiguous().realize() self.assertTrue(((t+1).T==cpy).all().item()) def test_flip_range(self): t = Tensor.rand(10, 10).realize() # passthrough ranges a = UOp.range(10, -1) sel = t[9-a] cpy = sel.reshape(1, 10).expand(a, 10).contiguous().realize() self.assertTrue((t.flip(0)==cpy).all().item()) def test_vmap(self): def f(x): return x.sum(axis=0)*2 x = Tensor.ones(3, 10, 2).contiguous() # vmap across axis 0 a = UOp.range(3, -1) out = f(x[a]) out = out.reshape(1, 2).expand(a, 2).contiguous() # 3x2 grid of 20 out.realize() self.assertTrue((out==20).all().item()) def test_fancy_vmap(self): def f(x,y): return x+y x = Tensor.arange(9).reshape(3,3).contiguous() y = Tensor.arange(9).reshape(3,3).contiguous() a = UOp.range(3, -1) out = f(x[:,a], y[a,:]) # TODO: this should support flatten out = out.reshape(1, 3).expand(a, 3).contiguous().realize() self.assertListEqual([[0,4,8],[4,8,12],[8,12,16]], out.tolist()) if __name__ == '__main__': unittest.main()