fix(concat): fix concat mlu kernel wrong output shape

lite/kernels/mlu/bridges/concat_op.cc

@@ -37,25 +37,44 @@ int ConcatConverter(void* ctx, OpLite* op, KernelBase* kernel) {
 
   auto input_num = x_var_name.size();
 
-  auto output = scope->FindVar(out_var_name)->GetMutable<Tensor>();
-  auto output_dims = output->dims().Vectorize();
-  auto output_tensor = graph->AddNode(
-      out_var_name, output_dims, CNML_TENSOR, CNML_NHWC, graph->FPType());
-
-  int axis = (param_axis < 0) ? (param_axis + output_dims.size()) : param_axis;
-
   std::vector<cnmlTensor_t> input_tensor;
+  std::vector<std::vector<int64_t>> input_dims;
   for (auto x_name : x_var_name) {
     CHECK(graph->HasNode(x_name));
     input_tensor.push_back(graph->GetNode(x_name)->mlu_tensor());
+    auto x = scope->FindVar(x_name)->GetMutable<Tensor>();
+    input_dims.push_back(x->dims().Vectorize());
+  }
+
+  auto output = scope->FindVar(out_var_name)->GetMutable<Tensor>();
+  int axis = (param_axis < 0) ? (param_axis + output->dims().size()) : param_axis;
+  int nchw_to_nhwc_axis_map[4] = {0, 3, 1, 2};
+  int nhwc_axis = nchw_to_nhwc_axis_map[axis];
+
+  std::vector<int64_t> output_dims;
+  output_dims.assign(output->dims().size(), 0);
+
+  /* std::cout << string_format("concat axis: %d(NCHW), %d(NHWC)", axis, nhwc_axis) << std::endl; */
+  
+  for (int i = 0; i < output_dims.size(); ++i) {
+    if (i == nhwc_axis) {
+      for (auto &dim : input_dims) output_dims[i] += dim[i];
+    } else {
+      output_dims[i] = input_dims[0][i];
+    }
   }
-  int nchw_to_nhwc_aixs_map[4] = {0, 3, 1, 2};
-  int nhwc_axis = nchw_to_nhwc_aixs_map[axis];
+
+  /* std::cout << string_format("concat output dim: %ld, %ld, %ld, %ld") << std::endl; */
+
+  output->Resize(output_dims);
+  auto output_tensor = graph->AddNode(
+      out_var_name, output_dims, CNML_TENSOR, CNML_NHWC, graph->FPType());
 
   cnmlBaseOp_t concat_op;
-  auto output_t = output_tensor->mlu_tensor();
+  cnmlTensor_t outputs[1];
+  outputs[0] = output_tensor->mlu_tensor();
   CNML_CALL(cnmlCreateNdConcatOp(
-      &concat_op, nhwc_axis, input_tensor.data(), input_num, &output_t, 1));
+      &concat_op, nhwc_axis, input_tensor.data(), input_num, outputs, 1));
   graph->FuseOp(concat_op);
   return SUCCESS;
 }