[onnx] Update test suite for new importer

Element types were fixed for running the onnx test suite. This is the
result of rerunning the previously committed script.

iree_tests/onnx/node/generated/test_acos/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acos(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acos(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_acos_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acos_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acos_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_acosh/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_acosh/output_0.bin

@@ -1 +1 @@
-��@D{,@�#@��@�8@��&@w�@��8@Zm=@@�22@*�@�@>;@���?ZT�?~/?�5@�81@Վ7@�P>@%�2@��@�d1@\<�?�N&@~2�?�G<@�6@�@���?��0@�@��@��?j[$@��#@sK$@>9<@o�)@��@��@+@V�?5�(@a�(@յ�?(ճ?�V
@�k@��@\@��>@�^�?��?O��?�n'@��?<<@YZ�?
+��@D{,@�#@��@�8@��&@w�@��8@[m=@@�22@*�@�@>;@���?ZT�?~/?�5@�81@Վ7@�P>@&�2@��@�d1@\<�?�N&@}2�?�G<@�6@�@���?��0@�@��@��?j[$@��#@sK$@>9<@o�)@��@��@+@V�?4�(@a�(@յ�?'ճ?�V
@�k@��@\@��>@�^�?��?O��?�n'@��?<<@YZ�?

iree_tests/onnx/node/generated/test_acosh_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_acosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_acosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_adagrad/test_data_flags.txt

@@ -1,5 +1,5 @@
---input=xf32=@input_0.bin
---input=xsi64=@input_1.bin
+--input=f32=@input_0.bin
+--input=i64=@input_1.bin
 --input=1xf32=@input_2.bin
 --input=1xf32=@input_3.bin
 --input=1xf32=@input_4.bin

iree_tests/onnx/node/generated/test_adagrad_multiple/test_data_flags.txt

@@ -1,5 +1,5 @@
---input=xf32=@input_0.bin
---input=xsi64=@input_1.bin
+--input=f32=@input_0.bin
+--input=i64=@input_1.bin
 --input=1xf32=@input_2.bin
 --input=2xf32=@input_3.bin
 --input=1xf32=@input_4.bin

iree_tests/onnx/node/generated/test_adam/test_data_flags.txt

@@ -1,5 +1,5 @@
---input=xf32=@input_0.bin
---input=xsi64=@input_1.bin
+--input=f32=@input_0.bin
+--input=i64=@input_1.bin
 --input=2xf32=@input_2.bin
 --input=2xf32=@input_3.bin
 --input=2xf32=@input_4.bin

iree_tests/onnx/node/generated/test_adam_multiple/test_data_flags.txt

@@ -1,5 +1,5 @@
---input=xf32=@input_0.bin
---input=xsi64=@input_1.bin
+--input=f32=@input_0.bin
+--input=i64=@input_1.bin
 --input=1xf32=@input_2.bin
 --input=2xf32=@input_3.bin
 --input=1xf32=@input_4.bin

iree_tests/onnx/node/generated/test_add_uint8/test_data_flags.txt

@@ -1,3 +1,3 @@
---input=3x4x5xui8=@input_0.bin
---input=3x4x5xui8=@input_1.bin
+--input=3x4x5xi8=@input_0.bin
+--input=3x4x5xi8=@input_1.bin
 --expected_output=3x4x5xi8=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_2d/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x2x3xf32=@input_0.bin
---input=4xsi64=@input_1.bin
+--input=4xi64=@input_1.bin
 --expected_output=2x5x6x2xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x2x3xf32=@input_0.bin
---input=4xsi64=@input_1.bin
+--input=4xi64=@input_1.bin
 --expected_output=2x5x6x2xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x2x3xf32=@input_0.bin
---input=4xsi64=@input_1.bin
+--input=4xi64=@input_1.bin
 --expected_output=2x5x6x2xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x2x3xf32=@input_0.bin
---input=4xsi64=@input_1.bin
+--input=4xi64=@input_1.bin
 --expected_output=2x5x6x2xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_3d/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x3x4xf32=@input_0.bin
---input=5xsi64=@input_1.bin
+--input=5xi64=@input_1.bin
 --expected_output=2x4x5x6x3xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x3x4xf32=@input_0.bin
---input=5xsi64=@input_1.bin
+--input=5xi64=@input_1.bin
 --expected_output=2x4x5x6x3xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x3x4xf32=@input_0.bin
---input=5xsi64=@input_1.bin
+--input=5xi64=@input_1.bin
 --expected_output=2x4x5x6x3xf32=@output_0.bin

iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=2x3x4xf32=@input_0.bin
---input=5xsi64=@input_1.bin
+--input=5xi64=@input_1.bin
 --expected_output=2x4x5x6x3xf32=@output_0.bin

iree_tests/onnx/node/generated/test_ai_onnx_ml_array_feature_extractor/test_data_flags.txt

@@ -1,3 +1,3 @@
 --input=3x4xf32=@input_0.bin
---input=2xsi64=@input_1.bin
+--input=2xi64=@input_1.bin
 --expected_output=3x2xf32=@output_0.bin

iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/test_data_flags.txt

@@ -1,2 +1,2 @@
---input=5=@input_0.bin
+--input=5x=@input_0.bin
 --expected_output=5xi64=@output_0.bin

iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/test_data_flags.txt

@@ -1,2 +1,2 @@
---input=5=@input_0.bin
+--input=5x=@input_0.bin
 --expected_output=5xi64=@output_0.bin

iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/test_data_flags.txt

@@ -1,2 +1,2 @@
---input=5=@input_0.bin
+--input=5x=@input_0.bin
 --expected_output=5xi16=@output_0.bin

iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_set_membership/model.mlir

@@ -0,0 +1,8 @@
+module {
+  func.func @test_ai_onnx_ml_tree_ensemble_set_membership(%arg0: !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 5 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+    %none = torch.constant.none
+    %0 = torch.operator "onnx.TreeEnsemble"(%arg0) {torch.onnx.aggregate_function = 1 : si64, torch.onnx.leaf_targetids = [0 : si64, 1 : si64, 2 : si64, 3 : si64], torch.onnx.leaf_weights = dense<[1.000000e+00, 1.000000e+01, 1.000000e+03, 1.000000e+02]> : tensor<4xf32>, torch.onnx.membership_values = dense<[1.200000e+00, 3.700000e+00, 8.000000e+00, 9.000000e+00, 0x7FC00000, 1.200000e+01, 7.000000e+00, 0x7FC00000]> : tensor<8xf32>, torch.onnx.n_targets = 4 : si64, torch.onnx.nodes_falseleafs = [1 : si64, 0 : si64, 1 : si64], torch.onnx.nodes_falsenodeids = [2 : si64, 2 : si64, 3 : si64], torch.onnx.nodes_featureids = [0 : si64, 0 : si64, 0 : si64], torch.onnx.nodes_modes = dense<[0, 6, 6]> : tensor<3xui8>, torch.onnx.nodes_splits = dense<[1.100000e+01, 2.323440e+05, 0x7FC00000]> : tensor<3xf32>, torch.onnx.nodes_trueleafs = [0 : si64, 1 : si64, 1 : si64], torch.onnx.nodes_truenodeids = [1 : si64, 0 : si64, 1 : si64], torch.onnx.post_transform = 0 : si64, torch.onnx.tree_roots = [0 : si64]} : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,4],f32> 
+    return %0 : !torch.vtensor<[6,4],f32>
+  }
+}
+

iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_set_membership/test_data_flags.txt

@@ -0,0 +1,2 @@
+--input=6x1xf32=@input_0.bin
+--expected_output=6x4xf32=@output_0.bin

iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_single_tree/model.mlir

@@ -0,0 +1,8 @@
+module {
+  func.func @test_ai_onnx_ml_tree_ensemble_single_tree(%arg0: !torch.vtensor<[3,2],f64>) -> !torch.vtensor<[3,2],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 5 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+    %none = torch.constant.none
+    %0 = torch.operator "onnx.TreeEnsemble"(%arg0) {torch.onnx.aggregate_function = 1 : si64, torch.onnx.leaf_targetids = [0 : si64, 1 : si64, 0 : si64, 1 : si64], torch.onnx.leaf_weights = dense<[5.230000e+00, 1.212000e+01, -1.223000e+01, 7.210000e+00]> : tensor<4xf64>, torch.onnx.n_targets = 2 : si64, torch.onnx.nodes_falseleafs = [0 : si64, 1 : si64, 1 : si64], torch.onnx.nodes_falsenodeids = [2 : si64, 2 : si64, 3 : si64], torch.onnx.nodes_featureids = [0 : si64, 0 : si64, 0 : si64], torch.onnx.nodes_modes = dense<0> : tensor<3xui8>, torch.onnx.nodes_splits = dense<[3.140000e+00, 1.200000e+00, 4.200000e+00]> : tensor<3xf64>, torch.onnx.nodes_trueleafs = [0 : si64, 1 : si64, 1 : si64], torch.onnx.nodes_truenodeids = [1 : si64, 0 : si64, 1 : si64], torch.onnx.post_transform = 0 : si64, torch.onnx.tree_roots = [0 : si64]} : (!torch.vtensor<[3,2],f64>) -> !torch.vtensor<[3,2],f64> 
+    return %0 : !torch.vtensor<[3,2],f64>
+  }
+}
+

iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_single_tree/test_data_flags.txt

@@ -0,0 +1,2 @@
+--input=3x2xf64=@input_0.bin
+--expected_output=3x2xf64=@output_0.bin

iree_tests/onnx/node/generated/test_asin/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_asin(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_asin(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Asin"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_asin/output_0.bin

@@ -1 +1 @@
-ĸ?P
L?*�%?�?���>��3?J��>���?8s�?l{�>��i?�? �?�_�?���=ت�=�<��{?#Hd?��?���?fm?C��>F@e?[��=��1?M>`H�?T�?���>��>Z�b?%��>$�?c�<um*?�(?3*?��?D@?{H�>]��>k�E?9�v=;�:?q-<?�Y>�c>N�>X��>�S?/x�>L��?)Z�=�yW>��%>�06?�>a�>��|>
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L?(�%?�?���>��3?J��>���?8s�?l{�>��i?�? �?�_�?���=ت�=�<��{?"Hd?��?���?fm?C��>E@e?[��=��1?M>`H�?T�?���>��>Z�b?%��>$�?c�<tm*?�(?3*?��?B@?{H�>]��>k�E?9�v=:�:?p-<?�Y>�c>N�>X��>�S?/x�>L��?)Z�=�yW>��%>�06?�>a�>��|>

iree_tests/onnx/node/generated/test_asin_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_asin_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_asin_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Asin"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_asinh/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_asinh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_asinh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_asinh/output_0.bin

@@ -1 +1 @@
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+ɚ�?���>%�]?,��?(��?�~]��{X?ng��ӽ'��>��>���?A�3?b��=�c�>�ѧ><��?��P�ȝ>!<F��Wտ�??>H?��/��q�?�����\;=�>�V=�?��?�	>AG�>�L�����\����t>!��?M=�?���v����Pj��$��P馿��?����J�پ�P���	7?LϠ�D<X��4N�4u�>cQ��-s����漎�>� �=���>���ߵ�

iree_tests/onnx/node/generated/test_asinh_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_asinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_asinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_atan/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_atan(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_atan(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Atan"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_atan/output_0.bin

@@ -1 +1 @@
-#�?~��>�OF?V�?�"�?�F�܂B?~��p�ҽ�z�>4~>|�w?��&?���=���>��>� {?�4O��W�>=�4��F���3?{6?�r#�z�?m�w��K;=�{=�}#~?�%y?j>��>��9�:8���l����>�fc?0�`?�3���N��� O�u��4���m�?jS�fӾH�e�c.)?���d�V�B�:�(�>Q��'8^����s3�>��=�b�>ٵ�t*��
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iree_tests/onnx/node/generated/test_atan_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_atan_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_atan_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Atan"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_atanh/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_atanh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_atanh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Atanh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> 
     return %0 : !torch.vtensor<[3,4,5],f32>

iree_tests/onnx/node/generated/test_atanh/output_0.bin

@@ -1,2 +1,2 @@
-��?q�e?̍2?eo?�~�>+�D?�@�>B�?�W�?���>���?�?�%?/9�?0��=��=Ԧ�<�*�?5�?���?C�@�R�?���>��?w]�=�B?��>
-��??1?���>���>��?
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?�v>
+��?q�e?̍2?eo?�~�>+�D?�@�>B�?�W�?���>���?�?�%?/9�?0��=��=զ�<�*�?5�?���?C�@�R�?���>��?w]�=�B?��>
+��??1?���>���>��?
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?�v>

iree_tests/onnx/node/generated/test_atanh_example/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_atanh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_atanh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.Atanh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> 
     return %0 : !torch.vtensor<[3],f32>

iree_tests/onnx/node/generated/test_averagepool_1d_default/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_averagepool_1d_default(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_averagepool_1d_default(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> 
     return %0 : !torch.vtensor<[1,3,31],f32>

iree_tests/onnx/node/generated/test_averagepool_2d_ceil/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_averagepool_2d_ceil(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_averagepool_2d_ceil(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> 
     return %0 : !torch.vtensor<[1,1,2,2],f32>

iree_tests/onnx/node/generated/test_averagepool_2d_default/model.mlir

@@ -1,5 +1,5 @@
 module {
-  func.func @test_averagepool_2d_default(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
+  func.func @test_averagepool_2d_default(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 22 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
     %none = torch.constant.none
     %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> 
     return %0 : !torch.vtensor<[1,3,31,31],f32>