[CINN / Symbolic]Fix gather infer symbolic bugs

paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/binary_infer_sym.cc

@@ -235,8 +235,22 @@ bool GatherOpInferSymbolicShape(
     return numel;
   }();
 
-  const auto &axis_shape_or_data =
-      shape_analysis->GetShapeOrDataForValue(op->operand_source(2));
+  int axis = 0;
+  const auto &attributes = op->attributes();
+  if (op->HasAttribute("axis")) {  // CINN Dialect
+    axis = attributes.at("axis").dyn_cast<pir::Int32Attribute>().data();
+  } else {
+    PADDLE_ENFORCE_EQ(
+        op->num_operands() == 3,
+        true,
+        phi::errors::InvalidArgument(
+            "in GatherOpInferSymbolicShape: The number of operands should be "
+            "3 when the axis is not set."));
+    const auto &axis_shape_or_data =
+        shape_analysis->GetShapeOrDataForValue(op->operand_source(2));
+    axis =
+        static_cast<int>(axis_shape_or_data.data().value()[0].Get<int64_t>());
+  }
 
   const std::vector<symbol::DimExpr> &input_sym_shape =
       input_shape_or_data.data().has_value()
@@ -248,8 +262,6 @@ bool GatherOpInferSymbolicShape(
           ? index_shape_or_data.data().value()
           : index_shape_or_data.shape();
 
-  int axis =
-      static_cast<int>(axis_shape_or_data.data().value()[0].Get<int64_t>());
   if (axis < 0) axis += input_sym_shape.size();
 
   const auto &out_sym_shape = [&] {

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

@@ -79,42 +79,43 @@ def test_eval(self):
         )
 
 
-# class TestGatherAxisPosSymbolic(unittest.TestCase):
-#     def setUp(self):
-#         paddle.seed(2022)
-#         self.prepare_data()
-#
-#     def prepare_data(self):
-#         self.shape = [None, 4 ]
-#         self.x = paddle.randn(self.shape, dtype="float32")
-#         self.x.stop_gradient = True
-#         self.index = paddle.to_tensor([1])
-#         self.index.stop_gradient = True
-#
-#     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 = GatherLayerAxisPos()
-#         input_spec = [
-#             InputSpec(shape=[None, 4], dtype='float32'),
-#             InputSpec(shape=[1], dtype='int32'),
-#         ]
-#         net = utils.apply_to_static(net, use_cinn, input_spec)
-#         net.eval()
-#         out = net(self.x, self.index)
-#         if use_cinn:
-#             self.check_jit_kernel_info(net.forward)
-#         return out
-#
-#     def test_eval(self):
-#         cinn_out = self.eval(use_cinn=True)
-#         dy_out = self.eval(use_cinn=False)
-#         np.testing.assert_allclose(
-#             cinn_out.numpy(), dy_out.numpy(), atol=1e-6, rtol=1e-6
-#         )
-#
+class TestGatherAxisPosSymbolic(unittest.TestCase):
+    def setUp(self):
+        paddle.seed(2022)
+        self.prepare_data()
+
+    def prepare_data(self):
+        self.shape = [32, 4]
+        self.x = paddle.randn(self.shape, dtype="float32")
+        self.x.stop_gradient = True
+        self.index = paddle.to_tensor([1])
+        self.index.stop_gradient = True
+
+    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 = GatherLayerAxisPos()
+        input_spec = [
+            InputSpec(shape=[None, 4], dtype='float32'),
+            InputSpec(shape=[1], dtype='int32'),
+        ]
+        net = utils.apply_to_static(net, use_cinn, input_spec)
+        net.eval()
+        out = net(self.x, self.index)
+        if use_cinn:
+            self.check_jit_kernel_info(net.forward)
+        return out
+
+    def test_eval(self):
+        cinn_out = self.eval(use_cinn=True)
+        dy_out = self.eval(use_cinn=False)
+        np.testing.assert_allclose(
+            cinn_out.numpy(), dy_out.numpy(), atol=1e-6, rtol=1e-6
+        )
+
+
 class TestGatherAxisNegStatic(unittest.TestCase):
     def setUp(self):
         paddle.seed(2022)