From 7382f98600956b451059b472b31e6283acadb8f8 Mon Sep 17 00:00:00 2001
From: nhzlx <zlx_hg@163.com>
Date: Tue, 24 Jul 2018 06:01:44 +0000
Subject: [PATCH] 1. set ut batch > 1 2. readd the mul op(utest will be added
 later)

---
 .../inference/tensorrt/convert/mul_op.cc      | 54 +++++++++++++++++++
 .../tensorrt/convert/test_activation_op.cc    |  2 +-
 .../inference/tensorrt/convert/test_fc_op.cc  |  2 +-
 3 files changed, 56 insertions(+), 2 deletions(-)
 create mode 100644 paddle/fluid/inference/tensorrt/convert/mul_op.cc

diff --git a/paddle/fluid/inference/tensorrt/convert/mul_op.cc b/paddle/fluid/inference/tensorrt/convert/mul_op.cc
new file mode 100644
index 00000000000..9623ac27e2c
--- /dev/null
+++ b/paddle/fluid/inference/tensorrt/convert/mul_op.cc
@@ -0,0 +1,54 @@
+/* Copyright (c) 2018 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. */
+
+#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
+
+namespace paddle {
+namespace inference {
+namespace tensorrt {
+
+/*
+ * MulOp, IMatrixMultiplyLayer in TRT. This Layer doesn't has weights.
+ */
+class MulOpConverter : public OpConverter {
+ public:
+  void operator()(const framework::proto::OpDesc& op,
+                  const framework::Scope& scope, bool test_mode) override {
+    VLOG(4) << "convert a fluid mul op to tensorrt mul layer without bias";
+
+    framework::OpDesc op_desc(op, nullptr);
+    // Declare inputs
+    auto* input1 = engine_->GetITensor(op_desc.Input("X")[0]);
+    auto* input2 = engine_->GetITensor(op_desc.Input("Y")[0]);
+    // Both the input1 and input2 do not need transpose.
+    auto* layer = TRT_ENGINE_ADD_LAYER(
+        engine_, MatrixMultiply, *const_cast<nvinfer1::ITensor*>(input1), false,
+        *const_cast<nvinfer1::ITensor*>(input2), false);
+
+    auto output_name = op_desc.Output("Out")[0];
+    engine_->SetITensor(output_name, layer->getOutput(0));
+    if (test_mode) {  // the test framework can not determine which is the
+                      // output, so place the declaration inside.
+      engine_->DeclareOutput(output_name);
+    }
+  }
+};
+
+}  // namespace tensorrt
+}  // namespace inference
+}  // namespace paddle
+
+USE_OP(mul);
+// TODO(xingzhaolong): change the name to mul then
+REGISTER_TRT_OP_CONVERTER(mul_temp, MulOpConverter);
diff --git a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
index 743c20adc79..7dabfd9f6a9 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
@@ -23,7 +23,7 @@ namespace tensorrt {
 TEST(ReluOpConverter, main) {
   framework::Scope scope;
   std::unordered_set<std::string> parameters;
-  TRTConvertValidation validator(1, parameters, scope, 1000);
+  TRTConvertValidation validator(10, parameters, scope, 1000);
   validator.DeclInputVar("relu-X", nvinfer1::Dims2(10, 6));
   validator.DeclOutputVar("relu-Out", nvinfer1::Dims2(10, 6));
 
diff --git a/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc b/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
index c76f494f8cb..bd90e0ee7ac 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
@@ -23,7 +23,7 @@ namespace tensorrt {
 TEST(fc_op, test) {
   std::unordered_set<std::string> parameters({"mul-Y"});
   framework::Scope scope;
-  TRTConvertValidation validator(1, parameters, scope, 1000);
+  TRTConvertValidation validator(10, parameters, scope, 1000);
 
   validator.DeclInputVar("mul-X", nvinfer1::Dims4(1, 10, 1, 1));
   validator.DeclParamVar("mul-Y", nvinfer1::Dims2(10, 2));
-- 
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