Method BuildTensor

tensorflow/compiler/mlir/lite/flatbuffer_translate.cc:585–692

}

Optional<BufferOffset<tflite::Tensor>> Translator::BuildTensor(
    Value value, const std::string& name, unsigned buffer_idx) {
  auto type = value.getType().cast<TensorType>();

  // TFLite requires tensor shape only for the inputs and constants.
  // However, we output all known shapes for better round-tripping
  auto check_shape =
      [&](llvm::ArrayRef<int64_t> shape_ref) -> mlir::LogicalResult {
    auto is_out_of_range = [](int64_t dim) {
      return dim > std::numeric_limits<int32_t>::max();
    };

    if (std::any_of(shape_ref.begin(), shape_ref.end(), is_out_of_range))
      return mlir::emitError(
          value.getLoc(),
          "result shape dimensions out of 32 bit int type range");

    return mlir::success();
  };

  std::vector<int32_t> shape;
  std::vector<int32_t> shape_signature;
  if (type.hasStaticShape()) {
    llvm::ArrayRef<int64_t> shape_ref = type.getShape();
    if (mlir::failed(check_shape(shape_ref))) return llvm::None;

    shape = std::vector<int32_t>(shape_ref.begin(), shape_ref.end());
  } else if (auto* inst = value.getDefiningOp()) {
    if (IsConst(inst)) {
      // Const op can have a result of dynamic shaped type (e.g. due to constant
      // folding), but we can still derive the shape of a constant tensor for
      // its attribute type.
      mlir::Attribute tensor_attr = inst->getAttr("value");
      llvm::ArrayRef<int64_t> shape_ref =
          tensor_attr.getType().cast<TensorType>().getShape();
      if (mlir::failed(check_shape(shape_ref))) return llvm::None;

      shape = std::vector<int32_t>(shape_ref.begin(), shape_ref.end());
    }
  } else if (type.hasRank()) {
    llvm::ArrayRef<int64_t> shape_ref = type.getShape();
    if (mlir::failed(check_shape(shape_ref))) return llvm::None;

    shape.reserve(shape_ref.size());
    for (auto& dim : shape_ref) {
      shape.push_back(dim == -1 ? 1 : dim);
    }
    shape_signature = std::vector<int32_t>(shape_ref.begin(), shape_ref.end());
  }

  if (auto* inst = value.getDefiningOp()) {
    if (auto cst = dyn_cast<tfl::SparseConstOp>(inst)) {
      // CreateSparsityParameters(cst.s_param());
    } else if (auto cst = dyn_cast<tfl::SparseQConstOp>(inst)) {
      // CreateSparsityParameters(cst.s_param());
    }
  }