update for sherpa-ncnn v2.0

export-for-ncnn-fr-streaming-zipformer.sh

@@ -46,7 +46,7 @@ pnnx joiner_jit_trace-pnnx.pt
 #  7767517
 # -2028 2547
 # +2029 2547
-# +SherpaMetaData           sherpa_meta_data1        0 0 0=2 1=32 2=4 3=7 -23316=5,2,4,3,2,4 -23317=5,384,384,384,384,384 -23318=5,192,192,192,192,192 -23319=5,1,2,4,8,2 -23320=5,31,31,31,31,31
+# +SherpaMetaData           sherpa_meta_data1        0 0 0=2 1=32 2=4 3=7 15=1 -23316=5,2,4,3,2,4 -23317=5,384,384,384,384,384 -23318=5,192,192,192,192,192 -23319=5,1,2,4,8,2 -23320=5,31,31,31,31,31
 #  Input                    in0                      0 1 in0
 #  Input                    in1                      0 1 in1
 #  Split                    splitncnn_0              1 2 in1 2 3
@@ -61,11 +61,12 @@ pnnx joiner_jit_trace-pnnx.pt
 # (5) 1=32, attribute 1, 32 is the value of --decode-chunk-len
 # (6) 2=4, attribute 2, 4 is the value of --num-left-chunks
 # (7) 3=7, attribute 3, 7 is the pad length. The first subsampling layer is using (x_len - 7) // 2, so we use 7 here
-# (8) -23316=5,2,4,3,2,4, attribute 16, this is an array attribute. It is attribute 16 since -23300 - (-23316) = 16
+# (8) 15=1, attribute 15, 1 is the model version. We require it >= 1 for sherpa-ncnn v2.0
+# (9) -23316=5,2,4,3,2,4, attribute 16, this is an array attribute. It is attribute 16 since -23300 - (-23316) = 16
 #       the first element of the array is the length of the array, which is 5 in our case.
 #       2,4,3,2,4 is the value of --num-encoder-layers
-# (9) -23317=5,384,384,384,384,384, attribute 17. 384,384,384,384,384 is the value of --encoder-dims
-# (10) -23318=5,192,192,192,192,192, attribute 18, 192,192,192,192,192 is the value of --attention-dims
-# (11) -23319=5,1,2,4,8,2, attribute 19, 1,2,4,8,2 is the value of --zipformer-downsampling-factors
-# (12) -23320=5,31,31,31,31,31, attribute 20, 31,31,31,31,31 is the value of --cnn-module-kernels
+# (10) -23317=5,384,384,384,384,384, attribute 17. 384,384,384,384,384 is the value of --encoder-dims
+# (11) -23318=5,192,192,192,192,192, attribute 18, 192,192,192,192,192 is the value of --attention-dims
+# (12) -23319=5,1,2,4,8,2, attribute 19, 1,2,4,8,2 is the value of --zipformer-downsampling-factors
+# (13) -23320=5,31,31,31,31,31, attribute 20, 31,31,31,31,31 is the value of --cnn-module-kernels