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[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.
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4 changes: 2 additions & 2 deletions
4
iree_tests/onnx/node/generated/test_adagrad/test_data_flags.txt
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4 changes: 2 additions & 2 deletions
4
iree_tests/onnx/node/generated/test_adagrad_multiple/test_data_flags.txt
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4 changes: 2 additions & 2 deletions
4
iree_tests/onnx/node/generated/test_adam_multiple/test_data_flags.txt
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4 changes: 2 additions & 2 deletions
4
iree_tests/onnx/node/generated/test_add_uint8/test_data_flags.txt
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--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 |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_affine_grid_2d/test_data_flags.txt
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--input=2x2x3xf32=@input_0.bin | ||
--input=4xsi64=@input_1.bin | ||
--input=4xi64=@input_1.bin | ||
--expected_output=2x5x6x2xf32=@output_0.bin |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners/test_data_flags.txt
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--input=2x2x3xf32=@input_0.bin | ||
--input=4xsi64=@input_1.bin | ||
--input=4xi64=@input_1.bin | ||
--expected_output=2x5x6x2xf32=@output_0.bin |
2 changes: 1 addition & 1 deletion
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..._tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/test_data_flags.txt
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--input=2x2x3xf32=@input_0.bin | ||
--input=4xsi64=@input_1.bin | ||
--input=4xi64=@input_1.bin | ||
--expected_output=2x5x6x2xf32=@output_0.bin |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/test_data_flags.txt
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@@ -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 |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_affine_grid_3d/test_data_flags.txt
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--input=2x3x4xf32=@input_0.bin | ||
--input=5xsi64=@input_1.bin | ||
--input=5xi64=@input_1.bin | ||
--expected_output=2x4x5x6x3xf32=@output_0.bin |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners/test_data_flags.txt
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@@ -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 |
2 changes: 1 addition & 1 deletion
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..._tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/test_data_flags.txt
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@@ -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 |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/test_data_flags.txt
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@@ -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 |
2 changes: 1 addition & 1 deletion
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iree_tests/onnx/node/generated/test_ai_onnx_ml_array_feature_extractor/test_data_flags.txt
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--input=3x4xf32=@input_0.bin | ||
--input=2xsi64=@input_1.bin | ||
--input=2xi64=@input_1.bin | ||
--expected_output=3x2xf32=@output_0.bin |
2 changes: 1 addition & 1 deletion
2
iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/test_data_flags.txt
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@@ -1,2 +1,2 @@ | ||
--input=5=@input_0.bin | ||
--input=5x=@input_0.bin | ||
--expected_output=5xi64=@output_0.bin |
2 changes: 1 addition & 1 deletion
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...nx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/test_data_flags.txt
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--input=5=@input_0.bin | ||
--input=5x=@input_0.bin | ||
--expected_output=5xi64=@output_0.bin |
2 changes: 1 addition & 1 deletion
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...ode/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/test_data_flags.txt
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--input=5=@input_0.bin | ||
--input=5x=@input_0.bin | ||
--expected_output=5xi16=@output_0.bin |
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_set_membership/input_0.npy
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_set_membership/model.mlir
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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> | ||
} | ||
} | ||
|
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_set_membership/output_0.npy
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...ests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_set_membership/test_data_flags.txt
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--input=6x1xf32=@input_0.bin | ||
--expected_output=6x4xf32=@output_0.bin |
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_single_tree/input_0.npy
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_single_tree/model.mlir
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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> | ||
} | ||
} | ||
|
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_single_tree/output_0.npy
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iree_tests/onnx/node/generated/test_ai_onnx_ml_tree_ensemble_single_tree/test_data_flags.txt
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--input=3x2xf64=@input_0.bin | ||
--expected_output=3x2xf64=@output_0.bin |
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2 changes: 1 addition & 1 deletion
2
iree_tests/onnx/node/generated/test_averagepool_1d_default/model.mlir
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iree_tests/onnx/node/generated/test_averagepool_2d_ceil/model.mlir
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iree_tests/onnx/node/generated/test_averagepool_2d_default/model.mlir
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