Comments (5)
机器是 x64-avx2 ? 最新版本上结果对么?
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机器是 x64-avx2 ? 最新版本上结果对么?
处理器amd r7 6800H ,要怎么样知道MNN是否使用avx2指令集? 最新版本结果和当前情况一样
from mnn.
@jxt1234
testMNNFromONNX加debug后显示First Error Node is : Resize_709, 模型里的UpsampleLayer使用bicubic插值
部分cpp代码如下
//配置
MNN::BackendConfig backendConfig;
backendConfig.precision = backendConfig.Precision_Low;
backendConfig.memory = backendConfig.Memory_High;
backendConfig.power = backendConfig.Power_Normal;
MNN::ScheduleConfig config;
config.numThread = 4;
config.backendConfig = &backendConfig;
config.type = typeengine;
exe->setGlobalExecutorConfig(typeengine, backendConfig, 4);
rtmgr = std::shared_ptr<Executor::RuntimeManager>(Executor::RuntimeManager::createRuntimeManager(config));
encoder.reset(Module::load(std::vector<std::string>{}, std::vector<std::string>{}, encoder_path, rtmgr));
sam.reset(Module::load(sam_input, sam_output, decoder_path, rtmgr));
rtmgr->setCache(".cachefile");
//推理
auto input = MNN::Express::_Input({1, inference_size, inference_size, 3}, MNN::Express::NHWC, halide_type_of<float>());
::memcpy(input->writeMap<float>(), processed_image.data, inference_size * inference_size * 3 * sizeof(float));
input = _Convert(input, MNN::Express::NCHW);
auto st = std::chrono::system_clock::now();
auto outputs = encoder->onForward({ input });
auto et = std::chrono::system_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::microseconds>(et - st);
printf("# 1. embedding times: %f ms\n", duration.count() * 1e-3);
image_embedding = _Convert(outputs[0], NCHW);
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bicubic改成bilinear后结果正常,看到之前有个类似的问题 #1837
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估计是 bicubic 的 avx2 后端实现有问题,我们检查一下
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