optimize_dl_model_for_inference( : : DLModelHandle, DLDeviceHandle, Precision, DLSamples, GenParam : DLModelHandleConverted, ConversionReport)DescriptionThe operator optimize_dl_model_for_inference optimizes the input model DLModelHandle for inference on the device DLDeviceHandle and returns the ...
halcon深度学习 optimize_dl_model_for_inference( : : DLModelHandle, DLDeviceHandle, Precision, DLSamples, GenParam : DLModelHandleConverted, ConversionReport) optimize_dl_model_for_inference()Optimize a model for inference on a device via the AI2-interface.The parameterDLSamplesspecifies the samples...
优化深度学习模型进行推理，`optimize_dl_model_for_inference`函数通过AI2接口完成。建议使用的`DLSamples`样本应具有代表性，通常每个类别提供10-20个样本即可达到良好的结果。获取设备参数使用`get_dl_device_param`函数，反之，`set_dl_device_param`用于设置设备参数。深度学习模型参数的设置与获取，`s...
'optimize_for_inference' is not supported. Default: 'false' 'precision': Defines the data type that is internally used for the calculation of a forward pass of a deep learning model. Default: 'float32' 'precision_is_converted': Indicates whether the model was subjected to a conversion ...
* To convert the model to'float16'/'float32'precision, no samples have to be provided to* optimize_dl_model_for_inference.* No additional conversion parameters are required, so use thedefaultparameters.get_dl_device_param (DLDeviceHandleOpenVINO,'optimize_for_inference_params', OptimizeForInferen...
Python下的VGG网络模型源码: importtensorflowastfclassVGG16(Model):def__init__(self):super(VGG16,self).__init__()#1self.c1=Conv2D(filters=64,kernel_size=(3,3),padding='same') # 卷积层1self.b1=BatchNormalization()# BN层1self.a1=Activation('relu') # 激活层1# 2self.c2=Conv2D(filter...
stop () endfor * * Optimize the memory consumption. set_dl_model_param (DLModelHandle, 'optimize_for_inference', 'true') write_dl_model (DLModelHandle, RetrainedModelFileName) *Close the windows. dev_close_window_dict (WindowHandleDict) 1. 2. 3. 4. 5. 6. 7. 8....
List of values:'ai_accelerator_interface','calibration_precisions','cast_precisions','conversion_supported','id','inference_only','name','optimize_for_inference_params','precisions','runtime','settable_device_params','type' GenParamValue(input_control)attribute.value(-array)→(string /integer...
enhanced.hdl', this network is suited for more complex tasks. But its structure differs, bringing the advantage of making the training more stable and being internally more robust. Compared to the neural network'pretrained_dl_classifier_resnet50.hdl'it is less complex and has faster inference ...
‘optimize_for_inference‘, ‘true‘) 34 2020/5/28 使用内/显存优化模型进行推断 Activations Weights apply_model 更少的内/显存占用(Classification) pretrained_dl_classifier_compact.hdl pretrained_dl_classifier_enhanced.hdl CPU GPU CPU GPU 内/显存占用 ~ 5622 MB ~ 6451 MB ~ 4940 MB ~ 6169 MB ...