From 4030e756fbe039563beaf979231f661b38bc7c55 Mon Sep 17 00:00:00 2001
From: HappyAngel <chenjiaobuaa@126.com>
Date: Tue, 16 Jun 2020 21:59:02 -0500
Subject: [PATCH] [arm]fix concat axis < 0 compute error problem (#3802)

* fix concatt axis < 0 errorr,ttest=develop

* fix format. test=develop
---
 lite/core/mir/fusion/conv_activation_fuse_pass.cc | 8 ++++----
 lite/kernels/arm/concat_compute.cc                | 9 ++++-----
 2 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/lite/core/mir/fusion/conv_activation_fuse_pass.cc b/lite/core/mir/fusion/conv_activation_fuse_pass.cc
index 68c07c0ffd..fa89bc2a5f 100644
--- a/lite/core/mir/fusion/conv_activation_fuse_pass.cc
+++ b/lite/core/mir/fusion/conv_activation_fuse_pass.cc
@@ -25,21 +25,21 @@ namespace mir {
 void ConvActivationFusePass::Apply(const std::unique_ptr<SSAGraph>& graph) {
   std::vector<std::string> act_types{"relu"};
   bool has_int8 = false;
-  bool has_arm_float = false;
+  bool has_arm = false;
   bool has_cuda = false;
   for (auto& place : graph->valid_places()) {
     if (place.precision == PRECISION(kInt8)) {
       has_int8 = true;
     }
-    if (place.target == TARGET(kARM) && place.precision == PRECISION(kFloat)) {
-      has_arm_float = true;
+    if (place.target == TARGET(kARM)) {
+      has_arm = true;
     }
     if (place.target == TARGET(kCUDA)) {
       has_cuda = true;
     }
   }
 
-  if (!has_int8 && has_arm_float) {
+  if (has_arm) {
     act_types.push_back("relu6");
     act_types.push_back("leaky_relu");
   }
diff --git a/lite/kernels/arm/concat_compute.cc b/lite/kernels/arm/concat_compute.cc
index dc78e1b955..9ab4ca54bb 100644
--- a/lite/kernels/arm/concat_compute.cc
+++ b/lite/kernels/arm/concat_compute.cc
@@ -52,11 +52,7 @@ void ConcatFunc(const std::vector<lite::Tensor*> inputs,
       output_offset += in_stride[0];
     }
   } else {
-    std::vector<lite::Tensor*> inputs_concat(inputs.size());
-    for (int j = 0; j < inputs.size(); ++j) {
-      inputs_concat[j] = inputs[j];
-    }
-    lite::arm::math::concat_func<T>(inputs_concat, axis, out);
+    lite::arm::math::concat_func<T>(inputs, axis, out);
   }
 }
 
@@ -71,6 +67,9 @@ void ConcatCompute::Run() {
     auto* axis_tensor_data = axis_tensor->data<int>();
     axis = axis_tensor_data[0];
   }
+  if (axis < 0) {
+    axis += inputs[0]->dims().size();
+  }
 
   switch (inputs.front()->precision()) {
     case PRECISION(kFloat):
-- 
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