Fix gather op convert for Paddle-TensorRT (#46779) (#46825)

* fix gather op convert to only support int32 index as input.
* add ut

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -534,6 +534,16 @@ struct SimpleOpTypeSetTeller : public Teller {
                      "the pass.";
           return false;
         }
+
+        auto index_var_name = desc.Input("Index")[0];
+        auto* index_var_desc = block->FindVar(index_var_name);
+
+        // The index input must be int32 datatype.
+        if (index_var_desc->GetDataType() !=
+            paddle::framework::proto::VarType_Type::VarType_Type_INT32) {
+          VLOG(3) << "gather op Index input data type must be int32";
+          return false;
+        }
 #if !IS_TRT_VERSION_GE(7000)
         auto* x_var_desc = block->FindVar(desc.Input("X")[0]);
         const auto x_shape = x_var_desc->GetShape();

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_gather.py

@@ -42,6 +42,9 @@ class TrtConvertGatherTest(TrtLayerAutoScanTest):
         def generate_input2(index):
             return np.array(index).astype(np.int32)
 
+        def generate_input4(index):
+            return np.array(index).astype(np.int64)
+
         def generate_input3(axis):
             return np.array([axis]).astype(np.int32)
 
@@ -57,9 +60,11 @@ class TrtConvertGatherTest(TrtLayerAutoScanTest):
                                 "Index": ["index_data"],
                                 "Axis": ["axis_data"]
                         }]:
+                            for index_type_int32 in [True, False]:
                                 self.shape = shape
                                 self.axis = axis
                                 self.input_num = len(input)
+                                self.index_type_int32 = index_type_int32
                                 dics = [{"overwrite": overwrite, "axis": axis}]
                                 ops_config = [{
                                     "op_type": "gather",
@@ -80,7 +85,9 @@ class TrtConvertGatherTest(TrtLayerAutoScanTest):
                                             generate_input1, shape)),
                                         "index_data":
                                         TensorConfig(data_gen=partial(
-                                        generate_input2, index)),
+                                            generate_input2
+                                            if index_type_int32 ==
+                                            True else generate_input4, index)),
                                     } if len(input) == 2 else {
                                         "input_data":
                                         TensorConfig(data_gen=partial(
@@ -162,7 +169,7 @@ class TrtConvertGatherTest(TrtLayerAutoScanTest):
             if self.input_num == 3:
                 return 0, 5
             else:
-                if dynamic_shape:
+                if dynamic_shape and self.index_type_int32 == True:
                     return 1, 3
                 else:
                     return 0, 4