chore: import upstream snapshot with attribution

test/cinn/test_same_input_fusion.py

@@ -0,0 +1,169 @@
+# Copyright (c) 2024 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 os
+import unittest
+
+import numpy
+
+os.environ['FLAGS_prim_all'] = 'true'
+os.environ['FLAGS_prim_enable_dynamic'] = 'true'
+os.environ['FLAGS_use_cinn'] = '1'
+os.environ['FLAGS_deny_cinn_ops'] = 'slice;'
+
+import paddle
+
+
+def init():
+    var_52 = paddle.rand([4000, 512])
+    var_54 = paddle.rand([4000, 512])
+    var_38 = paddle.rand([4000, 512])
+    var_17 = paddle.rand([512])
+    var_57 = paddle.rand([4000, 512])
+    var_53 = paddle.rand([4000, 512])
+    var_58 = paddle.rand([4000, 512])
+    var_56 = paddle.rand([4000, 512])
+    var_55 = paddle.rand([4000, 512])
+    return (
+        var_52,
+        var_54,
+        var_38,
+        var_17,
+        var_57,
+        var_53,
+        var_58,
+        var_56,
+        var_55,
+    )
+
+
+def func(
+    var_52, var_54, var_38, var_17, var_57, var_53, var_58, var_56, var_55
+):
+    var_86 = paddle.broadcast_to(var_17, [4000, 512])
+    var_87 = var_38 + var_86
+    var_88 = var_87
+    var_89 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=-1)
+    var_90 = var_89 * var_87
+    var_91 = paddle.exp(var_90)
+    var_92 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_93 = var_91 + var_92
+    var_94 = var_87 / var_93
+    var_95 = var_87 * -1.0 + 0.0
+    var_96 = paddle.exp(var_95)
+    var_97 = var_96
+    var_98 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_99 = var_98 + var_96
+    var_100 = var_99
+    var_101 = var_52 / var_99
+    var_102 = var_87 * -1.0 + 0.0
+    var_103 = paddle.exp(var_102)
+    var_104 = var_103
+    var_105 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_106 = var_105 + var_103
+    var_107 = var_106
+    var_108 = var_53 / var_106
+    var_109 = var_87 * -1.0 + 0.0
+    var_110 = paddle.exp(var_109)
+    var_111 = var_110
+    var_112 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_113 = var_112 + var_110
+    var_114 = var_113
+    var_115 = var_54 / var_113
+    var_116 = var_99 * var_99
+    var_117 = var_87 * -1.0 + 0.0
+    var_118 = paddle.exp(var_117)
+    var_119 = var_118
+    var_120 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_121 = var_120 + var_118
+    var_122 = var_121
+    var_123 = var_55 / var_121
+    var_124 = var_99 * var_99
+    var_125 = var_87 * -1.0 + 0.0
+    var_126 = paddle.exp(var_125)
+    var_127 = var_126
+    var_128 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_129 = var_128 + var_126
+    var_130 = var_129
+    var_131 = var_56 / var_129
+    var_132 = var_106 * var_106
+    var_133 = var_87 * -1.0 + 0.0
+    var_134 = paddle.exp(var_133)
+    var_135 = var_134
+    var_136 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_137 = var_136 + var_134
+    var_138 = var_137
+    var_139 = var_57 / var_137
+    var_140 = var_106 * var_106
+    var_141 = var_87 * -1.0 + 0.0
+    var_142 = paddle.exp(var_141)
+    var_143 = var_142
+    var_144 = paddle.full(shape=[4000, 512], dtype='float32', fill_value=1)
+    var_145 = var_144 + var_142
+    var_146 = var_145
+    var_147 = var_58 / var_145
+
+    return (
+        var_88,
+        var_94,
+        var_97,
+        var_100,
+        var_101,
+        var_104,
+        var_107,
+        var_108,
+        var_111,
+        var_114,
+        var_115,
+        var_116,
+        var_119,
+        var_122,
+        var_123,
+        var_124,
+        var_127,
+        var_130,
+        var_131,
+        var_132,
+        var_135,
+        var_138,
+        var_139,
+        var_140,
+        var_143,
+        var_146,
+        var_147,
+    )
+
+
+class TestCase(unittest.TestCase):
+    def setUp(self):
+        pass
+
+    def tearDown(self):
+        pass
+
+    def compare_result(self, dy_compute, data_init):
+        static_compute = paddle.jit.to_static(full_graph=True, backend="CINN")(
+            dy_compute
+        )
+        inputs = data_init()
+        dy_out = dy_compute(*inputs)
+        st_out = static_compute(*inputs)
+        numpy.testing.assert_allclose(dy_out, st_out, atol=1e-5, rtol=1e-6)
+
+    def test_case(self):
+        self.compare_result(func, init)
+
+
+if __name__ == "__main__":
+    unittest.main()