↓ Skip to main content
111qqz’s blog
  1. Categories/

Deep-Learning

2017

分布式 tensorflow 学习笔记(非最终版)

·4 mins
Deep-Learning Tensorflow
感觉资料不是很多，先收集资料好了。 tf-distributed官网文档 SO-between-graph和in-graph的区别 inception.README.md SyncReplicasOptimizer SO_How does ps work in distribute Tensorflow? update:在多个nodes（机）上跑。。。tf默认是异步更新的。。。同步的话。。大概需要syncreplicasoptimizer?

TensorFlow Architecture 学习笔记（二）Adding a New Op

·6 mins
Deep-Learning Tensorflow
Adding a New Op # * [目录](https://www.tensorflow.org/extend/adding_an_op#top_of_page) * [定义运算的接口](https://www.tensorflow.org/extend/adding_an_op#define_the_ops_interface) * [实现运算的核心部分(kernels)](https://www.tensorflow.org/extend/adding_an_op#implement_the_kernel_for_the_op) * [多线程cpu kernels](https://www.tensorflow.org/extend/adding_an_op#multi-threaded_cpu_kernels) * [GPU kernels](https://www.tensorflow.org/extend/adding_an_op#gpu_kernels) * [构建运算库](https://www.tensorflow.org/extend/adding_an_op#build_the_op_library) * [用系统编译器编译你的运算（TensorFlow binary installation）](https://www.tensorflow.org/extend/adding_an_op#compile_the_op_using_your_system_compiler_tensorflow_binary_installation) * [使用bazel编译你的运算(TensorFlow source installation)](https://www.tensorflow.org/extend/adding_an_op#compile_the_op_using_bazel_tensorflow_source_installation) * [在 Python 中使用你的运算](https://www.tensorflow.org/extend/adding_an_op#use_the_op_in_python) * [验证你添加的运算可以工作](https://www.tensorflow.org/extend/adding_an_op#verify_that_the_op_works) * [在你的运算中添加高级特性](https://www.tensorflow.org/extend/adding_an_op#building_advanced_features_into_your_op) * [条件检查和验证](https://www.tensorflow.org/extend/adding_an_op#conditional_checks_and_validation) * [Op registration](https://www.tensorflow.org/extend/adding_an_op#op_registration) * [GPU Support](https://www.tensorflow.org/extend/adding_an_op#gpu_support) * [用python 实现梯度](https://www.tensorflow.org/extend/adding_an_op#implement_the_gradient_in_python) * [Shape functions in C++](https://www.tensorflow.org/extend/adding_an_op#shape_functions_in_c) 对于要添加原生tensorflow中没有定义的运算的需求，首先建议在python层面，能不能将需要的op用其他原生的op拼凑起来。