@@ -87,3 +87,112 @@ def test_case_6():
8787 """
8888 )
8989 obj .run (pytorch_code , ["out" ])
90+
91+
92+ def test_case_7 ():
93+ """1D tensor input"""
94+ pytorch_code = textwrap .dedent (
95+ """
96+ import torch
97+ t = torch.tensor([5.0, 1.0, 3.0, 9.0, 2.0])
98+ result = torch.aminmax(t)
99+ """
100+ )
101+ obj .run (pytorch_code , ["result" ])
102+
103+
104+ def test_case_8 ():
105+ """3D tensor with dim=0"""
106+ pytorch_code = textwrap .dedent (
107+ """
108+ import torch
109+ t = torch.tensor([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]])
110+ result = torch.aminmax(t, dim=0)
111+ """
112+ )
113+ obj .run (pytorch_code , ["result" ])
114+
115+
116+ def test_case_9 ():
117+ """3D tensor with dim=1 and keepdim=True"""
118+ pytorch_code = textwrap .dedent (
119+ """
120+ import torch
121+ t = torch.tensor([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]])
122+ result = torch.aminmax(t, dim=1, keepdim=True)
123+ """
124+ )
125+ obj .run (pytorch_code , ["result" ])
126+
127+
128+ def test_case_10 ():
129+ """float64 dtype"""
130+ pytorch_code = textwrap .dedent (
131+ """
132+ import torch
133+ t = torch.tensor([[1.5, 2.3, 3.7], [4.1, 5.9, 6.2]], dtype=torch.float64)
134+ result = torch.aminmax(t, dim=1)
135+ """
136+ )
137+ obj .run (pytorch_code , ["result" ])
138+
139+
140+ def test_case_11 ():
141+ """explicit keepdim=False"""
142+ pytorch_code = textwrap .dedent (
143+ """
144+ import torch
145+ t = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=torch.float)
146+ result = torch.aminmax(t, dim=0, keepdim=False)
147+ """
148+ )
149+ obj .run (pytorch_code , ["result" ])
150+
151+
152+ def test_case_12 ():
153+ """input as keyword argument only"""
154+ pytorch_code = textwrap .dedent (
155+ """
156+ import torch
157+ result = torch.aminmax(input=torch.tensor([3.0, 1.0, 4.0, 1.0, 5.0]))
158+ """
159+ )
160+ obj .run (pytorch_code , ["result" ])
161+
162+
163+ def test_case_13 ():
164+ """kwargs unpacking"""
165+ pytorch_code = textwrap .dedent (
166+ """
167+ import torch
168+ t = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
169+ kwargs = {"dim": 0, "keepdim": True}
170+ result = torch.aminmax(t, **kwargs)
171+ """
172+ )
173+ obj .run (pytorch_code , ["result" ])
174+
175+
176+ def test_case_14 ():
177+ """expression as dim argument"""
178+ pytorch_code = textwrap .dedent (
179+ """
180+ import torch
181+ t = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
182+ result = torch.aminmax(t, dim=2 - 1)
183+ """
184+ )
185+ obj .run (pytorch_code , ["result" ])
186+
187+
188+ def test_case_15 ():
189+ """dim with out parameter and keepdim"""
190+ pytorch_code = textwrap .dedent (
191+ """
192+ import torch
193+ t = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
194+ out = tuple([torch.tensor([0.0, 0.0]), torch.tensor([0.0, 0.0])])
195+ result = torch.aminmax(t, dim=1, keepdim=False, out=out)
196+ """
197+ )
198+ obj .run (pytorch_code , ["out" , "result" ])
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