chore: import upstream snapshot with attribution

test/amp/test_compare_accuracy_api.py

@@ -0,0 +1,147 @@
+# 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 unittest
+
+import numpy as np
+
+import paddle
+from paddle.base import core
+
+
+@unittest.skipIf(
+    not core.is_compiled_with_cuda(),
+    "not support cpu TestEagerCompareAccuracyApi",
+)
+class TestEagerCompareAccuracyApi(unittest.TestCase):
+    def calc(self, path, dtype):
+        paddle.base.core.set_nan_inf_debug_path(path)
+        x = paddle.to_tensor(
+            [2000, 3000, 4, 0], place=core.CUDAPlace(0), dtype=dtype
+        )
+        y = paddle.to_tensor(
+            [100, 500, 2, 10000], place=core.CUDAPlace(0), dtype=dtype
+        )
+        # normal
+        z1 = x + y
+        # inf
+        z2 = x * y
+
+    def test(self):
+        paddle.set_flags(
+            {"FLAGS_check_nan_inf": 1, "FLAGS_check_nan_inf_level": 3}
+        )
+        fp32_path = "workerlog_fp32_log_dir"
+        fp16_path = "workerlog_fp16_log_dir"
+        self.calc(fp32_path, "float32")
+        self.calc(fp16_path, "float16")
+
+        out_excel = "compare_accuracy_out_excel.csv"
+        paddle.amp.debugging.compare_accuracy(
+            fp32_path,
+            fp16_path,
+            out_excel,
+            loss_scale=1,
+            dump_all_tensors=False,
+        )
+
+    def test2(self):
+        fp32_path = "workerlog_fp32_log_dir"
+        fp16_path = "workerlog_fp16_null_log_dir"
+        self.calc(fp32_path, "float32")
+        out_excel = "compare_accuracy_out_excel_2.csv"
+        paddle.amp.debugging.compare_accuracy(
+            fp32_path,
+            fp16_path,
+            out_excel,
+            loss_scale=1,
+            dump_all_tensors=False,
+        )
+
+
+@unittest.skipIf(
+    not core.is_compiled_with_cuda(),
+    "not support cpu TestPirCompareAccuracyApi",
+)
+class TestPirCompareAccuracyApi(unittest.TestCase):
+    def calc(self, path, dtype):
+        paddle.base.core.set_nan_inf_debug_path(path)
+        with paddle.pir_utils.IrGuard():
+            startup = paddle.static.Program()
+            main = paddle.static.Program()
+            with paddle.static.program_guard(main, startup):
+                x = paddle.static.data(
+                    'x',
+                    [
+                        4,
+                    ],
+                    dtype,
+                )
+                y = paddle.static.data(
+                    'y',
+                    [
+                        4,
+                    ],
+                    dtype,
+                )
+                # normal
+                z1 = x + y
+                # inf
+                z2 = x * y
+            place = paddle.CUDAPlace(0)
+            exe = paddle.static.Executor(place)
+            exe.run(startup)
+            exe.run(
+                main,
+                feed={
+                    'x': np.array([2000, 3000, 4, 0]).astype(dtype),
+                    'y': np.array([100, 500, 2, 10000]).astype(dtype),
+                },
+                fetch_list=[z2],
+            )
+
+    def test(self):
+        paddle.set_flags(
+            {"FLAGS_check_nan_inf": 1, "FLAGS_check_nan_inf_level": 3}
+        )
+        fp32_path = "workerlog_fp32_log_dir"
+        fp16_path = "workerlog_fp16_log_dir"
+        self.calc(fp32_path, "float32")
+        self.calc(fp16_path, "float16")
+
+        out_excel = "compare_accuracy_out_excel.csv"
+        paddle.amp.debugging.compare_accuracy(
+            fp32_path,
+            fp16_path,
+            out_excel,
+            loss_scale=1,
+            dump_all_tensors=False,
+        )
+
+    def test2(self):
+        fp32_path = "workerlog_fp32_log_dir"
+        fp16_path = "workerlog_fp16_null_log_dir"
+        self.calc(fp32_path, "float32")
+        out_excel = "compare_accuracy_out_excel_2.csv"
+        paddle.amp.debugging.compare_accuracy(
+            fp32_path,
+            fp16_path,
+            out_excel,
+            loss_scale=1,
+            dump_all_tensors=False,
+        )
+
+
+if __name__ == '__main__':
+    unittest.main()