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Tools
Explore tools to support and accelerate TensorFlow workflows.
Colab
Colaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud, allowing you to execute TensorFlow code in your browser with a single click.
Visual Blocks
A visual coding web framework to prototype ML workflows using I/O devices, models, data augmentation, and even Colab code as reusable building blocks.
TensorBoard
A suite of visualization tools to understand, debug, and optimize TensorFlow programs.
What-If Tool
A tool for code-free probing of machine learning models, useful for model understanding, debugging, and fairness. Available in TensorBoard and jupyter or colab notebooks.
ML Perf
A broad ML benchmark suite for measuring performance of ML software frameworks, ML hardware accelerators, and ML cloud platforms.
XLA
XLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes TensorFlow computations. The results are improvements in speed, memory usage, and portability on server and mobile platforms.
TPU Research Cloud
The TPU Research Cloud (TRC) program enables researchers to apply for access to a cluster of more than 1,000 Cloud TPUs at no charge to help them accelerate the next wave of research breakthroughs.
MLIR
A new intermediate representation and compiler framework.
[null,null,[],[],[],null,["# Tools\n=====\n\nExplore tools to support and accelerate TensorFlow workflows. \n[Colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb) \nColaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud, allowing you to execute TensorFlow code in your browser with a single click. \n[Learn more](https://colab.sandbox.google.com/notebooks/welcome.ipynb) \n[Visual Blocks](https://visualblocks.withgoogle.com/) \nA visual coding web framework to prototype ML workflows using I/O devices, models, data augmentation, and even Colab code as reusable building blocks. \n[Learn more](https://visualblocks.withgoogle.com/) \n[TensorBoard](/tensorboard) \nA suite of visualization tools to understand, debug, and optimize TensorFlow programs. \n[Learn more](/tensorboard) [View code](https://github.com/tensorflow/tensorboard) \n[What-If Tool](https://pair-code.github.io/what-if-tool/) \nA tool for code-free probing of machine learning models, useful for model understanding, debugging, and fairness. Available in TensorBoard and jupyter or colab notebooks. \n[Learn more](https://pair-code.github.io/what-if-tool/) [Get started](https://colab.research.google.com/github/PAIR-code/what-if-tool/blob/master/What_If_Tool_Notebook_Usage.ipynb) \n[ML Perf](https://mlperf.org/) \nA broad ML benchmark suite for measuring performance of ML software frameworks, ML hardware accelerators, and ML cloud platforms. \n[Learn more](https://mlperf.org/) \n[XLA](/xla) \nXLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes TensorFlow computations. The results are improvements in speed, memory usage, and portability on server and mobile platforms. \n[Learn more](/xla) \n[TensorFlow Playground](https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.04620&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false) \nTinker with a neural network in your browser. Don't worry, you can't break it. \n[Learn more](https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.04620&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false) \n[TPU Research Cloud](https://sites.research.google/trc/) \nThe TPU Research Cloud (TRC) program enables researchers to apply for access to a cluster of more than 1,000 Cloud TPUs at no charge to help them accelerate the next wave of research breakthroughs. \n[Learn more](https://sites.research.google/trc/) \n[MLIR](/mlir) \nA new intermediate representation and compiler framework. \n[Learn more](/mlir) \n\nExplore libraries that build advanced models, methods, and extensions using TensorFlow\n--------------------------------------------------------------------------------------\n\n[See libraries](/resources/libraries-extensions)"]]
