add new test

Author: lanxianghit

test/ir/pir/cinn/symbolic/test_if_dy.py

@@ -35,14 +35,11 @@ def exp_sub(self, x):
         y = paddle.exp(x)
         return y - x
 
-    def forward(self, x, y):
+    def forward(self, x):
         if x.shape[-1] > 1:
             x = self.exp_sub(x)
-        else:
-            y = paddle.abs(y)
         x = paddle.nn.functional.relu(x)
-        y = paddle.logical_not(y)
-        return x, y
+        return x
 
 
 class TestIfSubgraph(unittest.TestCase):
@@ -55,36 +52,28 @@ def prepare_data(self):
         self.x = paddle.randn(self.shape, dtype="float32")
         self.x.stop_gradient = False
 
-        self.y_shape = [2, 256]
-        self.y = paddle.randn(self.y_shape, dtype="float32")
-        self.y.stop_gradient = False
-
     def check_jit_kernel_info(self, static_fn):
         utils.check_jit_kernel_number(static_fn, 1)
         utils.check_jit_kernel_structure(static_fn, {utils.JIT_KERNEL_NAME: 1})
 
     def eval(self, use_cinn):
         net = IfSubgraph()
         input_spec = [
-            InputSpec(shape=[None, None], dtype="float32"),
-            InputSpec(shape=[None, None], dtype="float32"),
+            InputSpec(shape=[None, None], dtype="bool"),
         ]
         net = utils.apply_to_static(net, use_cinn, input_spec)
         net.eval()
-        out = net(self.x, self.y)
+        out = net(self.x)
         if use_cinn:
             self.check_jit_kernel_info(net.forward)
         return out
 
     def test_eval(self):
-        dy_out_x, dy_out_y = self.eval(use_cinn=False)
+        dy_out = self.eval(use_cinn=False)
         if utils.unittest_use_cinn():
-            cinn_out_x, cinn_out_y = self.eval(use_cinn=True)
-            np.testing.assert_allclose(
-                cinn_out_x.numpy(), dy_out_x.numpy(), atol=1e-6, rtol=1e-6
-            )
+            cinn_out = self.eval(use_cinn=True)
             np.testing.assert_allclose(
-                cinn_out_y.numpy(), dy_out_y.numpy(), atol=1e-6, rtol=1e-6
+                cinn_out.numpy(), dy_out.numpy(), atol=1e-6, rtol=1e-6
             )
 
 

test/ir/pir/cinn/symbolic/test_if_else_dy.py

@@ -0,0 +1,92 @@
+# 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 sys
+import unittest
+from os.path import dirname
+
+import numpy as np
+
+import paddle
+from paddle import nn
+from paddle.static import InputSpec
+
+sys.path.append(dirname(dirname(__file__)))
+
+import utils
+
+
+class IfSubgraph(nn.Layer):
+    def __init__(self):
+        super().__init__()
+
+    def exp_sub(self, x):
+        y = paddle.exp(x)
+        return y - x
+
+    def forward(self, x, y):
+        if x.shape[-1] > 1:
+            x = self.exp_sub(x)
+        else:
+            y = paddle.abs(y)
+        x = paddle.nn.functional.relu(x)
+        y = paddle.logical_not(y)
+        return x, y
+
+
+class TestIfSubgraph(unittest.TestCase):
+    def setUp(self):
+        paddle.seed(2024)
+        self.prepare_data()
+
+    def prepare_data(self):
+        self.shape = [1, 2048]
+        self.x = paddle.randn(self.shape, dtype="float32")
+        self.x.stop_gradient = False
+
+        self.y_shape = [2, 256]
+        self.y = paddle.randn(self.y_shape, dtype="float32")
+        self.y.stop_gradient = False
+
+    def check_jit_kernel_info(self, static_fn):
+        utils.check_jit_kernel_number(static_fn, 1)
+        utils.check_jit_kernel_structure(static_fn, {utils.JIT_KERNEL_NAME: 1})
+
+    def eval(self, use_cinn):
+        net = IfSubgraph()
+        input_spec = [
+            InputSpec(shape=[None, None], dtype="float32"),
+            InputSpec(shape=[None, None], dtype="float32"),
+        ]
+        net = utils.apply_to_static(net, use_cinn, input_spec)
+        net.eval()
+        out = net(self.x, self.y)
+        if use_cinn:
+            self.check_jit_kernel_info(net.forward)
+        return out
+
+    def test_eval(self):
+        dy_out_x, dy_out_y = self.eval(use_cinn=False)
+        if utils.unittest_use_cinn():
+            cinn_out_x, cinn_out_y = self.eval(use_cinn=True)
+            np.testing.assert_allclose(
+                cinn_out_x.numpy(), dy_out_x.numpy(), atol=1e-6, rtol=1e-6
+            )
+            np.testing.assert_allclose(
+                cinn_out_y.numpy(), dy_out_y.numpy(), atol=1e-6, rtol=1e-6
+            )
+
+
+if __name__ == '__main__':
+    unittest.main()