Fix 123 unittests by autofix

tests/test_logcumsumexp.py

@@ -72,3 +72,29 @@ def test_case_5():
         """
     )
     obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[0.56, 0.34, 0.78], [0.98, 0.21, 1.78]])
+        out = torch.tensor([[0.56, 0.34, 0.78], [0.98, 0.21, 1.78]])
+        result = torch.logcumsumexp(input=x, dim=1, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[0.56, 0.34, 0.78], [0.98, 0.21, 1.78]])
+        out = torch.tensor([[0.56, 0.34, 0.78], [0.98, 0.21, 1.78]])
+        result = torch.logcumsumexp(out=out, dim=1, input=x)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logical_and.py

@@ -90,3 +90,31 @@ def _test_case_6():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        b = torch.tensor([4, 0, 1, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_and(input=a, other=b, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        b = torch.tensor([4, 0, 1, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_and(out=out, other=b, input=a)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logical_not.py

@@ -73,3 +73,29 @@ def test_case_5():
         """
     )
     obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_not(input=a, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_not(out=out, input=a)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logical_or.py

@@ -90,3 +90,31 @@ def _test_case_6():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        b = torch.tensor([4, 0, 1, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_or(input=a, other=b, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        b = torch.tensor([4, 0, 1, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_or(out=out, other=b, input=a)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logical_xor.py

@@ -90,3 +90,31 @@ def _test_case_6():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        b = torch.tensor([4, 0, 1, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_xor(input=a, other=b, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([0, 1, 10, 0], dtype=torch.float32)
+        b = torch.tensor([4, 0, 1, 0], dtype=torch.float32)
+        out = torch.tensor([True, False, True, True])
+        result = torch.logical_xor(out=out, other=b, input=a)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logit.py

@@ -63,3 +63,42 @@ def test_case_4():
         """
     )
     obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_4
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([0.2796, 0.9331, 0.6486, 0.1523, 0.6516])
+        out = torch.tensor([0.2796, 0.9331, 0.6486, 0.1523, 0.6516])
+        result = torch.logit(input=input, eps=1e-6, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_4
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([0.2796, 0.9331, 0.6486, 0.1523, 0.6516])
+        out = torch.tensor([0.2796, 0.9331, 0.6486, 0.1523, 0.6516])
+        result = torch.logit(out=out, eps=1e-6, input=input)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_4
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([0.2796, 0.9331, 0.6486, 0.1523, 0.6516])
+        out = torch.tensor([0.2796, 0.9331, 0.6486, 0.1523, 0.6516])
+        result = torch.logit(input)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logspace.py

@@ -88,3 +88,26 @@ def test_case_7():
         """
     )
     obj.run(pytorch_code, ["result", "out"])
+
+
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        out = torch.tensor([1., 2, 3], dtype=torch.float64)
+        result = torch.logspace(-1, 3, 4, base=10.0, dtype=torch.float64, out=out, layout=torch.strided, device=None, requires_grad=False)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_8
+def test_case_9():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        out = torch.tensor([1., 2, 3], dtype=torch.float64)
+        result = torch.logspace(start=-1, end=3, steps=4, base=10.0, out=out, dtype=torch.float64, layout=torch.strided, device=None, requires_grad=False)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])

tests/test_logsumexp.py

@@ -85,3 +85,42 @@ def _test_case_6():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
+        out = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
+        result = torch.logsumexp(input, 1, True)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
+        out = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
+        result = torch.logsumexp(input=input, dim=1, keepdim=True, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_9():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
+        out = torch.tensor([[1.4907, 1.0593, 1.5696], [1.4907, 1.0593, 1.5696]])
+        result = torch.logsumexp(out=out, keepdim=True, dim=1, input=input)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_lt.py

@@ -86,3 +86,31 @@ def test_case_6():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([[1, 2], [3, 4]])
+        other = torch.tensor([[1, 2], [3, 4]])
+        out = torch.tensor([True, False])
+        result = torch.lt(input=input, other=other, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+# generated by validate_unittest autofix, based on test_case_5
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        input = torch.tensor([[1, 2], [3, 4]])
+        other = torch.tensor([[1, 2], [3, 4]])
+        out = torch.tensor([True, False])
+        result = torch.lt(out=out, other=other, input=input)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])