#!/usr/bin/env python import numpy as np import unittest from tinygrad import Tensor, Device, dtypes from tinygrad.device import Interpreted class TestLazyBuffer(unittest.TestCase): def test_fromcpu_shape_tracker(self): def helper(a: np.ndarray): print(a.shape, a.strides, a.flags.c_contiguous) b = Tensor(a).lazydata #assert b.st.contiguous == a.flags.c_contiguous assert b.st.shape == a.shape np.testing.assert_equal(a, Tensor(b).numpy()) for ndims in range(1, 4): a = np.random.randn(*(4,)*ndims).astype(np.float32) for stride in [-2, 1, 2]: for start in [0, 1]: helper(a[(slice(start, None, stride),)*ndims]) def test_shuffle_pad_ops_cmpeq(self): y = Tensor([1]).cat(Tensor([1]) == 0).numpy() z = Tensor([1, 0]).numpy() np.testing.assert_allclose(y, z) def test_shuffle_pad_ops_div(self): y = Tensor([1]).cat(Tensor([1]).div(Tensor([2.0]))).numpy() z = Tensor([1, 0.5]).numpy() np.testing.assert_allclose(y, z) def test_shuffle_pad_ops_log(self): y = Tensor([1]).cat(Tensor([1]).log()).numpy() z = Tensor([1, 0]).numpy() np.testing.assert_allclose(y, z) def test_shuffle_pad_ops_exp(self): y = Tensor([1]).cat(Tensor([1]).exp()).numpy() z = Tensor([1, np.e]).numpy() np.testing.assert_allclose(y, z) def test_device_0_is_the_same_device(self): a = Tensor([1, 2, 3], f"{Device.DEFAULT}") b = Tensor([1, 2, 3], f"{Device.DEFAULT}:0") assert a.device == b.device def test_shrink_const_into_zero(self): # regression test to make sure the shapetracker is preserved a = Tensor.zeros(4,4,4).shrink((None, (0,0), None)) b = Tensor.zeros(4,1,4) c = a.cat(b, dim=1) np.testing.assert_allclose(c.numpy(), np.concatenate((a.numpy(), b.numpy()), axis=1)) def test_shrink_const_then_cast(self): # regression test to make sure the shapetracker is preserved a = Tensor.zeros(4,4,4).shrink((None, (0,0), None)).cast(dtypes.int32) b = Tensor.zeros(4,1,4) c = a.cat(b, dim=1) if isinstance(Device[Device.DEFAULT], Interpreted): # TODO: fix cast resets shapetracker and remove this block # this is expectedFailure with a condition try: np.testing.assert_allclose(c.numpy(), np.concatenate((a.numpy(), b.numpy()), axis=1)) except Exception: pass else: raise ValueError("assert_allclose not failed") else: np.testing.assert_allclose(c.numpy(), np.concatenate((a.numpy(), b.numpy()), axis=1)) if __name__ == "__main__": unittest.main()