model_analyzer: print new line after dump of tensors

It looks better for multiple subgraphs models.

example)

Your TFLite model has ‘3’ subgraph(s). In the subgraph description below,
T# represents the Tensor numbers. For example, in Subgraph#0, the WHILE op takes
tensor #1 and tensor #1 and tensor #0 as input and produces tensor #2 and tensor #3 and tensor #4 as output.

Subgraph#0 main(T#0) -> [T#4, T#3]
  Op#0 WHILE(T#1, T#1, T#0) -> [T#2, T#3, T#4]

Tensors of Subgraph#0
  T#0(serving_default_inp:0) shape:[], type:FLOAT32
  T#1(Const) shape:[], type:INT32
  T#2(while) shape:[], type:INT32
  T#3(PartitionedCall:0) shape:[], type:INT32
  T#4(PartitionedCall:1) shape:[], type:FLOAT32

Subgraph#1 while_cond(T#0, T#1, T#2) -> [T#4]
  Op#0 LESS(T#1, T#3) -> [T#4]

Tensors of Subgraph#1
  T#0(arg0) shape:[], type:INT32
  T#1(arg1) shape:[], type:INT32
  T#2(arg2) shape:[], type:FLOAT32
  T#3(while/Less/y) shape:[], type:INT32
  T#4(while/Less) shape:[], type:BOOL

Subgraph#2 while_body(T#0, T#1, T#2) -> [T#7, T#5, T#6]
  Op#0 ADD(T#1, T#3) -> [T#5]
  Op#1 MUL(T#2, T#4) -> [T#6]
  Op#2 ADD(T#0, T#3) -> [T#7]

Tensors of Subgraph#2
  T#0(arg0) shape:[], type:INT32
  T#1(arg1) shape:[], type:INT32
  T#2(arg2) shape:[], type:FLOAT32
  T#3(while/Add/y) shape:[], type:INT32
  T#4(while/scalar_mul/scalar) shape:[], type:FLOAT32
  T#5(while/Add) shape:[], type:INT32
  T#6(while/scalar_mul) shape:[], type:FLOAT32
  T#7(while/add_1) shape:[], type:INT32

PiperOrigin-RevId: 390499926
Change-Id: If2dd3fc5b9f4404c83268d56f3eccb1bc1271d0f

tensorflow/lite/python/analyzer_wrapper/model_analyzer.cc

@@ -215,6 +215,7 @@ std::string model_analyzer(const std::string& model_file_or_buffer,
       out_stream << "  ";  // indents for tensors
       dump_tensor_detail(out_stream, tensor, j);
     }
+    out_stream << "\n";
   }
   if (check_gpu_compatibility && model_is_gpu_compatibile) {
     out_stream