[0D-Tensor] CINN supports softmax and flip, fix infershape

paddle/cinn/hlir/op/nn.cc

@@ -78,8 +78,7 @@ std::shared_ptr<OpStrategy> StrategyForRelu(
 std::vector<framework::shape_t> InferShapeForRelu(
     const std::vector<framework::shape_t> &inputs_shape,
     const framework::AttrMapType &attrs) {
-  CHECK(!inputs_shape.empty())
-      << "The input's shape is empty! Please check again.";
+  CHECK(!inputs_shape.empty()) << "The inputs is empty! Please check again.";
   std::vector<framework::shape_t> res{inputs_shape[0]};
   return res;
 }
@@ -2352,8 +2351,7 @@ std::shared_ptr<OpStrategy> StrategyForSoftmax(
 std::vector<std::vector<int>> InferShapeForSoftmax(
     const std::vector<std::vector<int>> &inputs_shape,
     const framework::AttrMapType &attrs) {
-  CHECK(!inputs_shape.empty() && !inputs_shape[0].empty())
-      << "The input's shape size is 0! Please check again.";
+  CHECK(!inputs_shape.empty()) << "The inputs is empty! Please check again.";
   std::vector<std::vector<int>> res{inputs_shape[0]};
   return res;
 }
@@ -2433,8 +2431,7 @@ std::shared_ptr<OpStrategy> StrategyForDropoutInfer(
 std::vector<std::vector<int>> InferShapeForDropoutInfer(
     const std::vector<std::vector<int>> &inputs_shape,
     const framework::AttrMapType &attrs) {
-  CHECK(!inputs_shape.empty())
-      << "The input's shape size is 0! Please check again.";
+  CHECK(!inputs_shape.empty()) << "The inputs is empty! Please check again.";
   float dropout_prob = 0;
   std::string dropout_implementation = "downgrade_in_infer";
   for (auto &iter : attrs) {

test/cinn/ops/test_zero_dim_tensor.py

@@ -575,6 +575,9 @@ def test_check_results(self):
 create_unit_test(
     TestUnaryOp, "reciprocal", paddle.reciprocal, "builder.reciprocal"
 )
+create_unit_test(
+    TestUnaryOp, "softmax", paddle.nn.functional.softmax, "builder.softmax"
+)
 
 
 # acosh requires input value > 1.0, specific init_input instead of using create_unit_test
@@ -1118,5 +1121,43 @@ def test_check_results(self):
         self.check_outputs_and_grads()
 
 
+@OpTestTool.skip_if(
+    not is_compiled_with_cuda(), "x86 test will be skipped due to timeout."
+)
+class TestFlipOp(OpTest):
+    def setUp(self):
+        np.random.seed(2023)
+        self.dtype = "float32"
+        self.init_input()
+
+    def init_input(self):
+        self.inputs = {
+            "x": np.random.randint(-10, 10, []).astype(self.dtype),
+        }
+        self.target_shape = ()
+
+    def build_paddle_program(self, target):
+        x = paddle.to_tensor(self.inputs["x"], stop_gradient=False)
+        out = paddle.flip(x, axis=[])
+
+        self.paddle_outputs = [out]
+
+    def build_cinn_program(self, target):
+        builder = NetBuilder("flip_op")
+        x = builder.create_input(
+            cinn_dtype_convert(self.dtype), self.inputs["x"].shape, "x"
+        )
+        out = builder.flip(x, [])
+
+        prog = builder.build()
+        res = self.get_cinn_output(prog, target, [x], [self.inputs["x"]], [out])
+
+        self.cinn_outputs = res
+        self.assertEqual(res[0].shape, self.target_shape)
+
+    def test_check_results(self):
+        self.check_outputs_and_grads()
+
+
 if __name__ == "__main__":
     unittest.main()