Tensorflow是一个跨平台库。C API之上兼容很多不同的编程语言。

Client:
- Defines the computation as a dataflow graph.
- Initiates graph execution using a session.
Distributed Master
- Prunes a specific subgraph from the graph, as defined by the arguments to Session.run().
- Partitions the subgraph into multiple pieces that run in different processes and devices.
- Distributes the graph pieces to worker services.
- Initiates graph piece execution by worker services.
Worker Services (one for each task)
- Schedule the execution of graph operations using kernel implementations appropriate to the available hardware (CPUs, GPUs, etc).
- Send and receive operation results to and from other worker services.
Kernel Implementations
- Perform the computation for individual graph operations.

各个模块

layers module provides a high-level API that makes it easy to construct a neural network

High Level APIs

Eager Execution, which is the easiest way to use tensorflow.
Estimators, which introduces a high-level TensorFlow API that greatly simplifies ML programming.
Importing Data, which explains how to set up data pipelines to read data sets into your TensorFlow program.