replace hard core name to tensorrt engine input

paddle/fluid/inference/tensorrt/convert/emb_eltwise_layernorm.cc

@@ -114,13 +114,17 @@ class EmbEltwiseLayerNormOpConverter : public OpConverter {
 
       std::vector<nvinfer1::ITensor*> plugin_inputs;
       plugin_inputs.emplace_back(engine_->GetITensor(
-          "eval_placeholder_0"));  // word_embedding, eval_placeholder_0
+          engine_->network()->getInput(0)->getName()));  // word_embedding,
+                                                         // eval_placeholder_0
       plugin_inputs.emplace_back(engine_->GetITensor(
-          "eval_placeholder_1"));  // sent_embedding, eval_placeholder_1
+          engine_->network()->getInput(1)->getName()));  // sent_embedding,
+                                                         // eval_placeholder_1
       plugin_inputs.emplace_back(engine_->GetITensor(
-          "eval_placeholder_2"));  // cu_seqlens, eval_placeholder_2
+          engine_->network()->getInput(2)->getName()));  // cu_seqlens,
+                                                         // eval_placeholder_2
       plugin_inputs.emplace_back(engine_->GetITensor(
-          "eval_placeholder_3"));  // max_seqlen, eval_placeholder_3
+          engine_->network()->getInput(3)->getName()));  // max_seqlen,
+                                                         // eval_placeholder_3
 
       auto creator = GetPluginRegistry()->getPluginCreator(
           "CustomEmbLayerNormPluginDynamic", "2");

paddle/fluid/inference/tensorrt/convert/multihead_matmul_op.cc

@@ -149,9 +149,11 @@ class MultiheadMatMulOpConverter : public OpConverter {
       plugin_inputs.emplace_back(fc_layer->getOutput(0));
       plugin_inputs.emplace_back(mask_tensor);
       plugin_inputs.emplace_back(engine_->GetITensor(
-          "eval_placeholder_2"));  // cu_seqlens, eval_placeholder_2
+          engine_->network()->getInput(2)->getName()));  // cu_seqlens,
+                                                         // eval_placeholder_2
       plugin_inputs.emplace_back(engine_->GetITensor(
-          "eval_placeholder_3"));  // max_seqlen, eval_placeholder_3
+          engine_->network()->getInput(3)->getName()));  // max_seqlen,
+                                                         // eval_placeholder_3
       auto plugin_layer = engine_->network()->addPluginV2(
           plugin_inputs.data(), plugin_inputs.size(), *plugin);
       layer = plugin_layer;

paddle/fluid/inference/tensorrt/convert/slice_op.cc

@@ -50,7 +50,9 @@ class SliceOpConverter : public OpConverter {
       std::vector<nvinfer1::ITensor*> plugin_inputs;
       // plugin_inputs.emplace_back(trans_layer->getOutput(0));
       plugin_inputs.emplace_back(input);
-      plugin_inputs.emplace_back(engine_->GetITensor("eval_placeholder_2"));
+      plugin_inputs.emplace_back(engine_->GetITensor(
+          engine_->network()->getInput(2)->getName()));  // cu_seqlens,
+                                                         // eval_placeholder_2
 
       // bool ban_fp16 = engine_->disable_trt_plugin_fp16();
       plugin::SpecialSlicePluginDynamic* plugin =