update4

Author: spike-zhu

src/ops/concat/cpu/concat_cpu.cc

@@ -23,7 +23,7 @@ infiniopStatus_t cpuCreateConcatDescriptor(
 
     std::vector<uint64_t> output_shape(y->shape, y->shape + ndim);
 
-    // 验证输入张量的形状和步长，并记录形状信息
+    // 验证输入张量的形状和步长
     for (size_t i = 0; i < num_inputs; ++i) {
 
         if (x[i]->dt != y->dt) {
@@ -78,14 +78,13 @@ infiniopStatus_t concatCompute(const ConcatCpuDescriptor_t& desc,
     const std::vector<std::vector<uint64_t>>& input_shapes = desc->input_shapes;
     const std::vector<uint64_t>& output_shape = desc->output_shape;
 
-
     size_t blockOffsetInner = 1;
     for (size_t i = output_shape.size() - 1; i > axis; --i) {
         blockOffsetInner *= output_shape[i];
     }
     size_t blockOffset = output_shape[axis] * blockOffsetInner;
 
-    // 计算每个输入的维度和步长，并将数据拼接到输出中
+    // concat
     for (size_t i = 0; i < num_inputs; ++i) {
         const std::vector<uint64_t>& input_shape = input_shapes[i];
 

src/ops/concat/cpu/concat_cpu.h

@@ -6,10 +6,10 @@
 
 // 支持高维拼接的CPU-specific Concat描述符
 struct ConcatCpuDescriptor {
-    Device device;                                // 设备类型（例如 DevCpu）
-    DT dtype;                                    // 数据类型
-    uint64_t axis;                               // 拼接轴（从0开始）
-    uint64_t num_inputs;                         // 输入张量的数量
+    Device device;                                
+    DT dtype;                                    
+    uint64_t axis;                               
+    uint64_t num_inputs;                        
     std::vector<std::vector<uint64_t>> input_shapes;  // 输入张量的形状
     std::vector<uint64_t> output_shape;              // 输出张量的形状
 };