delete test_tensor_uop (#13951)

old test for shape tracker. also update tests that refer shapetracker

names

test/test_tensor_uop.py

@@ -1,117 +0,0 @@
-#!/usr/bin/env python
-import numpy as np
-import unittest
-from tinygrad import Tensor, Device, dtypes
-from tinygrad.engine.realize import run_schedule
-from tinygrad.uop.ops import UOp
-from tinygrad.helpers import SPLIT_REDUCEOP
-
-class TestTensorUOp(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).uop
-      assert b.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)
-    np.testing.assert_allclose(c.numpy(), np.concatenate((a.numpy(), b.numpy()), axis=1))
-
-  def test_const_dtype(self):
-    lb: UOp = Tensor([1], dtype=dtypes.int).uop
-    assert lb.const_like(1).base.arg == 1
-    assert type(lb.const_like(1).base.arg) is int
-
-    lb: UOp = Tensor([1], dtype=dtypes.float).uop
-    assert lb.const_like(1).base.arg == 1.0
-    assert type(lb.const_like(1).base.arg) is float
-
-  def test_contiguous_alu(self):
-    a = Tensor.randn(2, 2).realize()
-    b = Tensor.randn(2, 2).realize()
-    add = (a+b).contiguous()
-    out = add+2
-    sched = out.schedule()
-    self.assertEqual(len(sched), 2)
-    run_schedule(sched)
-    np.testing.assert_allclose(out.numpy(), a.numpy()+b.numpy()+2)
-
-  # NOTE: contiguous on a buffer collapses
-  @unittest.skip("contiguous on a buffer no longer collapses")
-  def test_contiguous_empty(self):
-    empty = Tensor.empty(1).contiguous()
-    sched = empty.schedule()
-    self.assertEqual(len(sched), 0)
-
-  def test_contiguous_folded_alu(self):
-    a = Tensor.empty(8, 8)
-    # NOTE: the buffer for mul_0 late folds to just a CONST
-    mul_0 = a*0
-    out = mul_0.shrink(((4, 8), (0, 8))).contiguous()
-    out.realize()
-    self.assertEqual(out.tolist(), Tensor.zeros(4, 8).tolist())
-
-@unittest.skipUnless(SPLIT_REDUCEOP, "only for SPLIT_REDUCEOP")
-class TestReduceOp(unittest.TestCase):
-  def test_no_split_reduce_kernel(self):
-    a = Tensor.rand(4, 4).realize()
-    a = a.sum()
-    sched = a.schedule()
-    assert len(sched) == 1
-
-  def test_split_reduce_kernel_dim0(self):
-    a = Tensor.rand(256, 255).realize()
-    a = a.sum()
-    sched = a.schedule()
-    assert len(sched) == 2
-
-  def test_split_reduce_kernel_dim1(self):
-    a = Tensor.rand(255, 256).realize()
-    a = a.sum()
-    sched = a.schedule()
-    assert len(sched) == 2
-
-if __name__ == "__main__":
-  unittest.main()

test/unit/test_masked_tensor.py

@@ -1,13 +1,12 @@
 import unittest
 from tinygrad.tensor import Tensor
 
-class TestMaskedShapeTracker(unittest.TestCase):
+class TestMaskedTensor(unittest.TestCase):
   def test_mul_masked(self):
     a = Tensor([1,1,1,1,1])
     b = Tensor([1,1]).pad(((0,3),))
     c = a*b
     assert c.shape == a.shape
-    #assert c.uop.st.views[0].mask is not None
     ret = c.data()
     assert ret.tolist() == [1.0, 1.0, 0.0, 0.0, 0.0]
 
@@ -16,7 +15,6 @@ class TestMaskedShapeTracker(unittest.TestCase):
     b = Tensor([1,1]).pad(((0,3),))
     c = a*b
     assert c.shape == a.shape
-    #assert c.uop.st.views[0].mask is not None
     ret = c.data()
     assert ret.tolist() == [1.0, 1.0, 0.0, 0.0, 0.0]
 
@@ -24,7 +22,6 @@ class TestMaskedShapeTracker(unittest.TestCase):
     a = Tensor([1,1]).pad(((0,2),))
     b = Tensor([1,1]).pad(((0,2),))
     c = a+b
-    #assert c.uop.st.views[0].mask is not None
     ret = c.data()
     assert ret.tolist() == [2.0, 2.0, 0.0, 0.0]