榜单
IT文库
服务器优惠
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Core
Core vision Helpers None [source] Image.n_px None [source] Image.shape None [source] Image.aspect Image.reshape [source] Image.to_bytes_format [source] Image.t... -
FAQ
FAQ Questions Common issues FAQ Below is a list of frequently asked questions and common issues encountered. Questions Question What models are recommended? Answer S... -
ML ONNX
MLOnnx Example Methods MLOnnx Exports a traditional machine learning model (i.e. scikit-learn) to ONNX. Example See the link below for a detailed example. Notebook Descr... -
前言
前言 前言 2018年3月30日，Google在加州山景城举行了第二届TensorFlow Dev Summit开发者峰会，并宣布正式发布TensorFlow 1.8版本。笔者有幸获得Google的资助亲临峰会现场，见证了这一具有里程碑式意义的新版本发布。众多新功能的加入和支持展示了TensorFlow的雄心壮志，同时早在2017年秋就开始测试的Ea... -
Unet
Dynamic UNet class UnetBlock [source] class ResizeToOrig [source] class DynamicUnet [source] Dynamic UNet Unet model using PixelShuffle ICNR upsampling that ca... -
6.5 循环神经网络的简洁实现
6.5 循环神经网络的简洁实现 6.5.1 定义模型 6.5.2 训练模型 小结 6.5 循环神经网络的简洁实现 本节将使用PyTorch来更简洁地实现基于循环神经网络的语言模型。首先，我们读取周杰伦专辑歌词数据集。 import time import math import numpy as np import t... -
Home
Highly scalable and standards based Why KServe KServe Components Single Model Serving ModelMesh Model Explainability Model Monitoring Advanced deployments Adopters Hig... -
Overview
training Training modules overview Walk-through of key functionalities Setup Basic training with Learner Viewing metrics Extending training with callbacks Extending train ... -
迁移第三方框架训练脚本
迁移第三方框架训练脚本 概述 准备环节 算子评估 软硬件环境准备 E2E迁移网络 训练阶段 脚本迁移 精度调试 云上集成 推理阶段 样例参考 迁移第三方框架训练脚本 Linux Ascend GPU CPU 全流程 初级 中级 高级 概述 你可能已经编写过TensorFlow、PyTorch等框架的脚本，... -
ML ONNX
MLOnnx Example Methods __call__(self, model, task='default', output=None, opset=12) special MLOnnx Exports a traditional machine learning model (i.e. scikit-learn) to ON...