添加单测调用多样性检测工具 Validate Unittest

paconvert/api_mapping.json

@@ -254,6 +254,7 @@
   "torch.Tensor.apply_": {},
   "torch.Tensor.arccos": {
     "Matcher": "GenericMatcher",
+    "min_input_args": 0,
     "paddle_api": "paddle.Tensor.acos"
   },
   "torch.Tensor.arccos_": {
@@ -263,6 +264,7 @@
   },
   "torch.Tensor.arccosh": {
     "Matcher": "GenericMatcher",
+    "min_input_args": 0,
     "paddle_api": "paddle.Tensor.acosh"
   },
   "torch.Tensor.arccosh_": {
@@ -271,7 +273,8 @@
     "paddle_api": "paddle.Tensor.acosh_"
   },
   "torch.Tensor.arcsin": {
-    "Matcher": "UnchangeMatcher"
+    "Matcher": "UnchangeMatcher",
+    "min_input_args": 0
   },
   "torch.Tensor.arcsin_": {
     "Matcher": "GenericMatcher",
@@ -354,7 +357,8 @@
   },
   "torch.Tensor.argwhere": {
     "Matcher": "GenericMatcher",
-    "paddle_api": "paddle.Tensor.nonzero"
+    "paddle_api": "paddle.Tensor.nonzero",
+    "min_input_args": 0
   },
   "torch.Tensor.as_strided": {
     "Matcher": "GenericMatcher",
@@ -420,6 +424,7 @@
     "Matcher": "TensorBF16Matcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -527,6 +532,7 @@
     "Matcher": "TensorBoolMatcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -545,6 +551,7 @@
     "Matcher": "TensorByteMatcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -553,6 +560,7 @@
     "Matcher": "TensorCdoubleMatcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -567,6 +575,7 @@
     "Matcher": "TensorCfloatMatcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -575,6 +584,7 @@
     "Matcher": "TensorCharMatcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -791,6 +801,7 @@
     "min_input_args": 1,
     "args_list": [
       "dim",
+      "*",
       "dtype"
     ],
     "kwargs_change": {
@@ -948,6 +959,7 @@
     "Matcher": "TensorDoubleMatcher",
     "min_input_args": 0,
     "args_list": [
+      "*",
       "memory_format"
     ]
   },
@@ -2533,7 +2545,7 @@
   "torch.Tensor.roll": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.Tensor.roll",
-    "min_input_args": 2,
+    "min_input_args": 1,
     "args_list": [
       "shifts",
       "dims"
@@ -8741,6 +8753,7 @@
   "torch.nn.NLLLoss": {
     "Matcher": "SizeAverageMatcher",
     "paddle_api": "paddle.nn.NLLLoss",
+    "min_input_args": 0,
     "args_list": [
       "weight",
       "size_average",
@@ -11744,6 +11757,7 @@
   "torch.roll": {
     "Matcher": "GenericMatcher",
     "paddle_api": "paddle.roll",
+    "min_input_args": 2,
     "args_list": [
       "input",
       "shifts",

tests/test_Tensor_absolute.py

@@ -46,7 +46,7 @@ def test_case_3():
         """
         import torch
         try:
-            a = torch.tensor([[-4, 9], [-23, 2]])
+            a = torch.tensor([[-4, 9], [-23, 2]]).absolute()
             assert 0, "Raise AssertionError"
         except Exception as e:
             error_msg = str(e)
@@ -60,7 +60,7 @@ def test_case_4():
         """
         import torch
         try:
-            a = torch.tensor([[-4, 9], [-23, 2]])
+            a = torch.tensor([[-4, 9], [-23, 2]]).absolute()
             assert 0, "Raise AssertionError"
         except Exception as e:
             error_msg = str(e)

tests/test_Tensor_add.py

@@ -76,8 +76,19 @@ def test_case_5():
     obj.run(pytorch_code, ["result"])
 
 
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([1., 2, 3])
+        result = x.add(alpha=0.8, other=torch.tensor([1., 4, 6]))
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
 # paddle not support type promote and x/y must have same dtype
-def _test_case_6():
+def _test_case_7():
     pytorch_code = textwrap.dedent(
         """
         import torch

tests/test_Tensor_add_.py

@@ -64,8 +64,19 @@ def test_case_4():
     obj.run(pytorch_code, ["x"])
 
 
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([1., 2, 3])
+        x.add_(alpha=0.8, other=torch.tensor([1., 4, 6]))
+        """
+    )
+    obj.run(pytorch_code, ["x"])
+
+
 # paddle not support type promote and x/y must have same dtype
-def _test_case_5():
+def _test_case_6():
     pytorch_code = textwrap.dedent(
         """
         import torch
@@ -77,7 +88,7 @@ def _test_case_5():
 
 
 # paddle not support type promote and x/y must have same dtype
-def _test_case_6():
+def _test_case_7():
     pytorch_code = textwrap.dedent(
         """
         import torch

tests/test_Tensor_addbmm.py

@@ -67,3 +67,16 @@ def test_case_4():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([[[4., 5., 6.], [1., 2., 3.]]])
+        b = torch.tensor([[[1., 2., 3.], [4., 5., 6.], [7., 8., 9.]]])
+        input = torch.tensor([[1., 2., 3.], [4., 5., 6.]])
+        result = input.addbmm(beta=3, alpha=3, batch2=b, batch1=a)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_addcdiv.py

@@ -70,3 +70,31 @@ def test_case_4():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        tensor1 = torch.tensor([1., 2., 3.])
+        tensor2 = torch.tensor([4., 5., 6.])
+        input = torch.tensor([7., 8., 9.])
+        value = 5
+        result = input.addcdiv(tensor1=tensor1, tensor2=tensor2, value=value)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        tensor1 = torch.tensor([1., 2., 3.])
+        tensor2 = torch.tensor([4., 5., 6.])
+        input = torch.tensor([7., 8., 9.])
+        value = 5
+        result = input.addcdiv(value=value, tensor2=tensor2, tensor1=tensor1)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_addcmul.py

@@ -72,3 +72,31 @@ def test_case_4():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        tensor1 = torch.tensor([1., 2., 3.])
+        tensor2 = torch.tensor([4., 5., 6.])
+        input = torch.tensor([7., 8., 9.])
+        value = 5
+        result = input.addcmul(tensor1=tensor1, tensor2=tensor2, value=value)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        tensor1 = torch.tensor([1., 2., 3.])
+        tensor2 = torch.tensor([4., 5., 6.])
+        input = torch.tensor([7., 8., 9.])
+        value = 5
+        result = input.addcmul(tensor1=tensor1, value=value, tensor2=tensor2)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_addmm.py

@@ -80,3 +80,16 @@ def test_case_5():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[1., 2], [4, 5]])
+        mat1 = torch.tensor([[1., 2], [4, 5]])
+        mat2 = torch.tensor([[1., 2], [4, 5]])
+        result = x.addmm(beta=0.6, alpha=0.7, mat1=mat1, mat2=mat2)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_addmm_.py

@@ -93,3 +93,16 @@ def test_case_6():
         """
     )
     obj.run(pytorch_code, ["x"])
+
+
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        x = torch.tensor([[1., 2], [4, 5]])
+        mat1 = torch.tensor([[1., 2], [4, 5]])
+        mat2 = torch.tensor([[1., 2], [4, 5]])
+        x.addmm_(mat1=mat1, mat2=mat2, alpha=0.7, beta=0.6)
+        """
+    )
+    obj.run(pytorch_code, ["x"])

tests/test_Tensor_addmv.py

@@ -67,3 +67,16 @@ def test_case_4():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([[1., 2., 3.], [4., 5., 6.]])
+        b = torch.tensor([1., 2., 3.])
+        input = torch.tensor([1., 2.])
+        result = input.addmv(alpha=3, mat=a, beta=3, vec=b)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_addmr.py → tests/test_Tensor_addr.py

@@ -66,3 +66,16 @@ def test_case_4():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.tensor([4., 5., 6.])
+        b = torch.tensor([1., 2., 3.])
+        input = torch.tensor([1., 2., 3.])
+        result = input.addr(vec1=a, alpha=3, vec2=b, beta=3)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_all.py

@@ -72,3 +72,14 @@ def test_case_5():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        a = torch.rand(4, 3)
+        result = a.all(keepdim=False, dim=0)
+        """
+    )
+    obj.run(pytorch_code, ["result"])

tests/test_Tensor_allclose.py

@@ -67,3 +67,33 @@ def test_case_5():
         """
     )
     obj.run(pytorch_code, ["result"])
+
+
+def test_case_6():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.tensor([10000., 1e-07]).allclose(torch.tensor([10000.1, 1e-08]), 1e-5, 2., False)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_7():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.tensor([10000., 1e-07]).allclose(other=torch.tensor([10000.1, 1e-08]), rtol=1e-5, atol=2., equal_nan=False)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_8():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        result = torch.tensor([10000., 1e-07]).allclose(rtol=1e-5, other=torch.tensor([10000.1, 1e-08]), atol=2., equal_nan=False)
+        """
+    )
+    obj.run(pytorch_code, ["result"])