Transition to ONNX-1.6.0. (#95)
* Transition to ONNX-1.6.0. * Use the version of ONNX inside ONNF when running backend tests. * Install quietly and with sudo previledge.
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@ -38,7 +38,7 @@ jobs:
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- run:
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name: Run End-To-End Tests
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command: |
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sudo pip install -q onnx
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sudo pip install -q -e ./ONNF/third_party/onnx
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cd ONNF/build
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cmake --build . --target run-onnx-backend-test
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- run:
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@ -189,8 +189,9 @@ private:
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}
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}
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mlir::Type elementType =
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convertONNXTypeToMLIRType(input.type().tensor_type().elem_type());
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auto elementOnnxType =
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(onnx::TensorProto_DataType)input.type().tensor_type().elem_type();
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mlir::Type elementType = convertONNXTypeToMLIRType(elementOnnxType);
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llvm::ArrayRef<int64_t> tensor_dims(dims.data(), dims.size());
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arg_types.emplace_back(
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mlir::RankedTensorType::get(tensor_dims, elementType));
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@ -1 +1 @@
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Subproject commit 1439eab5542c625bb3da49860f0cd68c3eafdc18
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Subproject commit 553df22c67bee5f0fe6599cff60f1afc6748c635
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