1 files changed, 118 insertions, 0 deletions
diff --git a/compiler/nnkit-onnxrt/support/include/nnkit/support/onnx/TensorContext.h b/compiler/nnkit-onnxrt/support/include/nnkit/support/onnx/TensorContext.h
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+++ b/compiler/nnkit-onnxrt/support/include/nnkit/support/onnx/TensorContext.h
@@ -0,0 +1,118 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef __NNKIT_SUPPORT_ONNX_TENSOR_CONTEXT_H__
+#define __NNKIT_SUPPORT_ONNX_TENSOR_CONTEXT_H__
+
+#include "nnkit/support/onnx/TensorSet.h"
+
+#include <nnkit/TensorContext.h>
+
+#include <nncc/core/ADT/tensor/LexicalLayout.h>
+#include <nncc/core/ADT/tensor/Overlay.h>
+
+namespace nnkit
+{
+namespace support
+{
+namespace onnx
+{
+
+class TensorContext final : public nnkit::TensorContext
+{
+public:
+  TensorContext(TensorSet &tensors) : _tensors(tensors)
+  {
+    // DO NOTHING
+  }
+
+  uint32_t size(void) const override { return _tensors.size(); }
+
+  std::string name(uint32_t n) const override { return std::string{_tensors.name(n)}; }
+
+  nncc::core::ADT::tensor::Shape shape(uint32_t n) const override
+  {
+    const std::vector<size_t> &dims = _tensors.dim(n);
+
+    nncc::core::ADT::tensor::Shape shape;
+    shape.resize(dims.size());
+    for (size_t i = 0; i < dims.size(); ++i)
+    {
+      shape.dim(i) = dims[i];
+    }
+    return shape;
+  }
+
+  bool isFloatTensor(uint32_t n) const override
+  {
+    return (_tensors.type(n) == ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT);
+  }
+
+  void getMutableFloatTensor(uint32_t n, const TensorContext::TypedAccessor<float> &f) override
+  {
+    if (_tensors.type(n) != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT)
+    {
+      throw std::runtime_error{"type mismatch"};
+    }
+
+    using nncc::core::ADT::tensor::LexicalLayout;
+    using nncc::core::ADT::tensor::make_overlay;
+
+    Status status;
+
+    OrtValue *base = _tensors.mutable_tensor(n);
+    float *data;
+
+    status = OrtGetTensorMutableData(base, (void **)&data);
+    status.throwOnError();
+
+    auto overlay = make_overlay<float, LexicalLayout>(shape(n), data);
+
+    f(*this, n, overlay);
+  }
+
+  void getConstFloatTensor(uint32_t n, const TensorContext::TypedReader<float> &f) const override
+  {
+    if (_tensors.type(n) != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT)
+    {
+      throw std::runtime_error{"type mismatch"};
+    }
+
+    using nncc::core::ADT::tensor::LexicalLayout;
+    using nncc::core::ADT::tensor::make_overlay;
+
+    Status status;
+
+    OrtValue *base = _tensors.mutable_tensor(n);
+    float *data;
+
+    status = OrtGetTensorMutableData(base, (void **)&data);
+    status.throwOnError();
+
+    auto overlay = make_overlay<float, LexicalLayout>(shape(n), data);
+
+    f(*this, n, overlay);
+  }
+
+private:
+  TensorSet &_tensors;
+};
+
+} // namespace onnx
+} // namespace support
+} // namespace nnkit
+
+#endif // __NNKIT_SUPPORT_ONNX_TENSOR_CONTEXT_H__