from typing import Iterable import torch from torch.utils.data import DataLoader from ppq import BaseGraph, QuantizationSettingFactory, TargetPlatform from ppq.api import export_ppq_graph, quantize_onnx_model BATCHSIZE = 32 INPUT_SHAPE = [3, 224, 224] DEVICE = 'cuda' # only cuda is fully ...
如果PLATFORM = TargetPlatform.QNN_DSP_INT8, quantize_torch_model.py会export出一个 .json 和 .onnx(看起来和fp32原模型一样);如果PLATFORM = TargetPlatform.ONNXRUNTIME,会生成一个.json 和 .onnx(体积比原模型小了,且是一个QDQ模型),如图 但想问一下,如何生成一个QNN模型,比如intel的neural-compresso...
assert os.path.exists(self.onnx_file_path), print('ONNX file {} not found, please first to generate it.'.format(self.onnx_file_path)) self.logger.info('Loading ONNX file from path {}...'.format(self.onnx_file_path)) with open(self.onnx_file_path, 'rb') as model: self.log...
yolov5使用的训练代码取自ultralytics/yolov5 master分支。环境:PC ubuntu18.04 x86_64rknn_tool v1.7.0python3.6.9环境tensorflow-gpu==1.14.0torch==1.2.0 onnx==1.6torchvision == 0.4.0 插入TB-RK1808S0 用yolov5 onnx轉檔rknn時, 設定如下rknn.config(reorder_channel='0 1 2',mean_values=[[0, ...
output_model_path 输入 量化后的模型的存放路径和文件名。 必选。 数据类型:String。 quant_config 输入 根据QuantConfig生成的量化配置实例。 必选。 数据类型:QuantConfig。 调用示例 from msmodelslim.onnx.post_training_quant import QuantConfig, run_quantize def custom_read_data(): calib_data = ...
具体来说，当您尝试将quantize=true作为参数传递给export_onnx()函数时，出现了TypeError错误。
https://community.intel.com/t5/Intel-Distribution-of-OpenVINO/openVino-inference-using-onnx-model/m-p/1460146 I believe OpenVINO supports QuantizeLinear/DeauantizeLinear layers and ONNX format models. However, the model using QuantizeLinear/DeauantizeLinear layers (=Model1) gives...
def export_onnx_model(self, output_dir, verbose)-New def export_torch_script(self, output_dir, verbose) Class Inspector def inspect(…) vai_q_pytorch 消息 VAIQ_WARN VAIQ_ERROR ONNX Runtime 版本 (vai_q_onnx) 安装vai_q_onnx 运行vai_q_onnx 准备浮点模型和校准集 (可选...
Model1 ONNX model (uses QuantizeLinear and DequantizeLinear) : Result when using OpenVINO™ toolkit 2021.4.2 : -1.9281068 Result when using OpenVINO™ toolkit 2022.3 : 0.30328402 Model2 ONNX model (does not use QuantizeLinear and DequantizeLinear): Result when using OpenVIN...
(TF_PATH, "mobilenet_v2_1.0_224.onnx") subprocess.run( [ "python", "-m", "tf2onnx.convert", "--tflite", tflite_model_path, "--output", onnx_model_path, "--opset", 13, ] ) # Note: the inputs of this model is [1, 224, 224, 3] # --- # Please use `quantize_onn...