Method fill_tensor

utils/Utils.h:381–539

     */
    template <typename T>
    void fill_tensor(T &tensor)
    {
        ARM_COMPUTE_ERROR_ON(!is_open());
        ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(&tensor, arm_compute::DataType::QASYMM8, arm_compute::DataType::S32,
                                              arm_compute::DataType::F32, arm_compute::DataType::F16);
        try
        {
            // Map buffer if creating a CLTensor
            map(tensor, true);

            // Check if the file is large enough to fill the tensor
            const size_t current_position = _fs.tellg();
            _fs.seekg(0, std::ios_base::end);
            const size_t end_position = _fs.tellg();
            _fs.seekg(current_position, std::ios_base::beg);

            ARM_COMPUTE_ERROR_ON_MSG((end_position - current_position) <
                                         tensor.info()->tensor_shape().total_size() * tensor.info()->element_size(),
                                     "Not enough data in file");
            ARM_COMPUTE_UNUSED(end_position);

            // Check if the typestring matches the given one
            std::string expect_typestr = get_typestring(tensor.info()->data_type());

            bool enable_f32_to_f16_conversion = false;
            if (_typestring != expect_typestr)
            {
                const std::string f32_typestring = "<f4";
                const std::string f16_typestring = "<f2";
                // if typestring does not match, check whether _typestring is F32 and can be downcasted to expect_typestr
                if (_typestring == f32_typestring && expect_typestr == f16_typestring)
                {
                    enable_f32_to_f16_conversion = true;
                }
                else
                {
                    ARM_COMPUTE_ERROR("Typestrings mismatch");
                }
            }

            bool are_layouts_different = (_file_layout != tensor.info()->data_layout());
            // Correct dimensions (Needs to match TensorShape dimension corrections)
            if (_shape.size() != tensor.info()->tensor_shape().num_dimensions())
            {
                for (int i = static_cast<int>(_shape.size()) - 1; i > 0; --i)
                {
                    if (_shape[i] == 1)
                    {
                        _shape.pop_back();
                    }
                    else
                    {
                        break;
                    }
                }
            }

            TensorShape                    permuted_shape = tensor.info()->tensor_shape();