Function dump_output_data

internal/bin/test_flatten_op.cpp:189–237

}

void dump_output_data(node_t test_node)
{
    tensor_t output_tensor = get_node_output_tensor(test_node, 0);
    int dims[4];

    get_tensor_shape(output_tensor, dims, 4);

    void* o_buf = get_tensor_buffer(output_tensor);
    int data_type = get_tensor_data_type(output_tensor);
    float scale = 0.1f;
    int zero = 0;
    if(data_type == TENGINE_DT_INT8 || data_type == TENGINE_DT_UINT8)
    {
        get_tensor_quant_param(output_tensor, &scale, &zero, 1);
        printf("output  scale: %f ,zero: %d\n", scale, zero);
    }

    for(int i = 0; i < dims[1] * dims[0] * dims[2] * dims[3]; i++)
    {
        if(data_type == TENGINE_DT_FP32)
        {
            float* p = ( float* )o_buf;
            std::cout << i << " " << p[i] << "\n";
        }
        else if(data_type == TENGINE_DT_FP16)
        {
            __fp16* p = ( __fp16* )o_buf;

#ifdef __ARM_ARCH
            std::cout << i << " " << ( float )p[i] << "\n";
#else
            std::cout << i << " " << fp16_to_fp32(p[i]) << "\n";
#endif
        }
        else if(data_type == TENGINE_DT_INT8)
        {
            int8_t* p = ( int8_t* )o_buf;
            std::cout << i << " " << ( int )p[i] << "\n";
        }
        else
        {
            uint8_t* p = ( uint8_t* )o_buf;

            std::cout << i << " " << ( int )p[i] << "\n";
        }
    }

    release_graph_tensor(output_tensor);
}

int main(int argc, char* argv[])
{