From cbba4177ccc8d10f469743fb260ce549360041a2 Mon Sep 17 00:00:00 2001
From: co63oc <co63@163.com>
Date: Mon, 28 Aug 2023 20:45:38 +0800
Subject: [PATCH] Add test

---
 paconvert/api_mapping.json            | 17 ++++++
 paconvert/api_matcher.py              |  9 +++
 tests/test_linalg_solve_triangular.py | 81 +++++++++++++++++++++++++++
 3 files changed, 107 insertions(+)
 create mode 100644 tests/test_linalg_solve_triangular.py

diff --git a/paconvert/api_mapping.json b/paconvert/api_mapping.json
index dd045688a..82b20f7dd 100644
--- a/paconvert/api_mapping.json
+++ b/paconvert/api_mapping.json
@@ -5862,6 +5862,23 @@
       "A"
     ]
   },
+  "torch.linalg.solve_triangular": {
+    "Matcher": "LinalgSolveTriangularMatcher",
+    "paddle_api": "paddle.linalg.triangular_solve",
+    "args_list": [
+      "input",
+      "B",
+      "upper",
+      "left",
+      "unitriangular",
+      "out"
+    ],
+    "kwargs_change": {
+      "input": "x",
+      "B": "y",
+      "left": "transpose"
+    }
+  },
   "torch.linalg.svdvals": {
     "Matcher": "LinalgSvdvalsMatcher",
     "paddle_api": "paddle.linalg.svd",
diff --git a/paconvert/api_matcher.py b/paconvert/api_matcher.py
index 4951d4000..189b491a7 100644
--- a/paconvert/api_matcher.py
+++ b/paconvert/api_matcher.py
@@ -4061,6 +4061,15 @@ def generate_code(self, kwargs):
         return code
 
 
+class LinalgSolveTriangularMatcher(BaseMatcher):
+    def generate_code(self, kwargs):
+        new_kwargs = {}
+        if "left" in kwargs:
+            new_kwargs["transpose"] = f"not {kwargs.pop('left')}"
+        new_kwargs.update(kwargs)
+        return GenericMatcher.generate_code(self, new_kwargs)
+
+
 class QrMatcher(BaseMatcher):
     def generate_code(self, kwargs):
         some_v = kwargs.pop("some") if "some" in kwargs else None
diff --git a/tests/test_linalg_solve_triangular.py b/tests/test_linalg_solve_triangular.py
new file mode 100644
index 000000000..91f5ed22a
--- /dev/null
+++ b/tests/test_linalg_solve_triangular.py
@@ -0,0 +1,81 @@
+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import textwrap
+
+from apibase import APIBase
+
+obj = APIBase("torch.linalg.solve_triangular")
+
+
+def test_case_1():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        A = torch.tensor([[ 1.1527, -1.0753], [ 1.23,  0.7986]])
+        B = torch.tensor([[-0.0210,  2.3513, -1.5492], [ 1.5429,  0.7403, -1.0243]])
+        result = torch.linalg.solve_triangular(A, B, upper=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_2():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        A = torch.tensor([[ 1.1527, -1.0753], [ 1.23,  0.7986]])
+        B = torch.tensor([[-0.0210,  2.3513, -1.5492], [ 1.5429,  0.7403, -1.0243]])
+        result = torch.linalg.solve_triangular(input=A, B=B, upper=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_3():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        A = torch.tensor([[ 1.1527, -1.0753], [ 1.23,  0.7986]])
+        B = torch.tensor([[-0.0210,  2.3513, -1.5492], [ 1.5429,  0.7403, -1.0243]])
+        result = torch.linalg.solve_triangular(input=A, B=B, unitriangular=True, upper=True)
+        """
+    )
+    obj.run(pytorch_code, ["result"])
+
+
+def test_case_4():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        A = torch.tensor([[ 1.1527, -1.0753], [ 1.23,  0.7986]])
+        B = torch.tensor([[-0.0210,  2.3513, -1.5492], [ 1.5429,  0.7403, -1.0243]])
+        out = torch.tensor([])
+        result = torch.linalg.solve_triangular(A, B, upper=True, left=True, unitriangular=False, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])
+
+
+def test_case_5():
+    pytorch_code = textwrap.dedent(
+        """
+        import torch
+        A = torch.tensor([[ 1.1527, -1.0753], [ 1.23,  0.7986]])
+        B = torch.tensor([[-0.0210,  2.3513, -1.5492], [ 1.5429,  0.7403, -1.0243]])
+        out = torch.tensor([])
+        result = torch.linalg.solve_triangular(input=A, B=B, upper=True, left=True, unitriangular=False, out=out)
+        """
+    )
+    obj.run(pytorch_code, ["result", "out"])