import math, unittest from unittest.mock import patch from tinygrad import Tensor from tinygrad.device import Device from tinygrad.dtype import Invalid, dtypes from tinygrad.helpers import unwrap_class_type class TestInvalidTensor(unittest.TestCase): def _invalid_test_helper(self, out, expected): before = None original_call = (runtime_cls:=unwrap_class_type(Device[Device.DEFAULT].runtime)).__call__ def patched_call(self_prg, *bufs, **kwargs): nonlocal before before = Device[Device.DEFAULT].allocator._as_buffer(bufs[0]).cast(out.dtype.fmt).tolist() return original_call(self_prg, *bufs, **kwargs) with patch.object(runtime_cls, '__call__', patched_call): ret = out.tolist() for i,v in enumerate(expected): if v is None: assert before[i] == ret[i] or (math.isnan(before[i]) and math.isnan(ret[i])) else: assert ret[i] == v return before, ret def test_where_x_invalid(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Invalid) self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_where_invalid_x(self): mask = Tensor.arange(4) < 2 out = mask.where(Invalid, Tensor([1.0, 2.0, 3.0, 4.0])) self._invalid_test_helper(out, [None, None, 3.0, 4.0]) def test_where_invalid_2d(self): mask = Tensor.arange(6).reshape(2, 3) < 3 vals = Tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]) out = mask.where(vals, Invalid) before, ret = self._invalid_test_helper(out, []) assert ret[0] == [1.0, 2.0, 3.0] assert before[3] == ret[1][0] or (math.isnan(before[3]) and math.isnan(ret[1][0])) assert before[4] == ret[1][1] or (math.isnan(before[4]) and math.isnan(ret[1][1])) assert before[5] == ret[1][2] or (math.isnan(before[5]) and math.isnan(ret[1][2])) def test_where_invalid_int(self): mask = Tensor.arange(3) < 2 out = mask.where(Tensor([10, 20, 30]), Invalid) self._invalid_test_helper(out, [10, 20, None]) def test_where_invalid_add(self): mask = Tensor.arange(3) < 2 mixed = mask.where(Tensor([10.0, 20.0, 30.0]), Invalid) out = mixed + Tensor([1.0, 2.0, 3.0]) self._invalid_test_helper(out, [11.0, 22.0, None]) def test_where_invalid_add_left(self): mask = Tensor.arange(3) < 2 mixed = mask.where(Tensor([10.0, 20.0, 30.0]), Invalid) out = Tensor([1.0, 2.0, 3.0]) + mixed self._invalid_test_helper(out, [11.0, 22.0, None]) def test_where_always_true(self): mask = Tensor.arange(3) < 10 out = mask.where(Tensor([10.0, 20.0, 30.0]), Invalid) self._invalid_test_helper(out, [10.0, 20.0, 30.0]) def test_where_cast(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Invalid).cast(dtypes.int) self._invalid_test_helper(out, [1, 2, None, None]) def test_where_compare(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Invalid) > 1 self._invalid_test_helper(out, [False, True, None, None]) def test_where_unary(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 4.0, 9.0, 16.0]), Invalid).sqrt() self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_where_where(self): mask1 = Tensor.arange(4) < 2 mask2 = Tensor.arange(4) > 0 out = mask2.where(mask1.where(Tensor([1.0, 2.0, 3.0, 4.0]), Invalid), Invalid) self._invalid_test_helper(out, [None, 2.0, None, None]) def test_where_reduce_always_true(self): mask = Tensor.arange(4) < 9 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Invalid).sum() before, ret = self._invalid_test_helper(out, []) assert ret == 10.0 def test_invalid_unary(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Tensor.full((4,), Invalid, dtype=dtypes.float).sqrt()) self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_invalid_binary(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Tensor.full((4,), Invalid, dtype=dtypes.float) + 2) self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_invalid_binary_left(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), 2 + Tensor.full((4,), Invalid, dtype=dtypes.float)) self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_invalid_reshape(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Invalid).reshape(2,2) before, ret = self._invalid_test_helper(out, []) assert ret[0] == [1.0, 2.0] assert ret[1][0] == before[2] or (math.isnan(ret[1][0]) and math.isnan(before[2])) assert ret[1][1] == before[3] or (math.isnan(ret[1][1]) and math.isnan(before[3])) def test_invalid_cast(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Tensor.full((4,), Invalid, dtype=dtypes.int).cast(dtypes.float)) self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_invalid_bitcast(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Tensor.full((4,), Invalid, dtype=dtypes.int).bitcast(dtypes.float)) self._invalid_test_helper(out, [1.0, 2.0, None, None]) def test_where_bitcast(self): mask = Tensor.arange(4) < 2 out = mask.where(Tensor([1.0, 2.0, 3.0, 4.0]), Tensor.full((4,), Invalid, dtype=dtypes.int)).bitcast(dtypes.int) self._invalid_test_helper(out, [0x3f800000, 0x40000000, None, None]) # tensor indexing uses reduce, so the entire result becomes invalid @unittest.expectedFailure def test_tensor_index(self): idx = (Tensor.arange(4) < 2).where(Tensor([0, 1, 2, 3]), Invalid) out = Tensor([1.0, 2.0, 3.0, 4.0])[idx] self._invalid_test_helper(out, [1.0, 2.0, None, None]) if __name__ == '__main__': unittest.main()