inference() - Builds the graph as far as is required for running the network forward to make predictions. Executes a graph in the context of a Session.Īlways the same 3-steps pattern: 1. Two phases in the program: Construct the computation graph. Variables maintain state across executions of the graph. In tensorflow computation represented using Graphs. Deep Flexibility: If you can write a computation graph. Interface for expressing machine learning algorithms, and an implementation for executing them. Tensorflow Developed by Google Brain Team and Google’s Machine Intelligence research organization. Install instructions Test the new instalation (tensorflow)$ python > import tensorflow as tf > hello = tf.constant(’Hello, TensorFlow!’) > sess = tf.Session() > print n(hello) Hello, TensorFlow! > a = tf.constant(10) > b = tf.constant(32) > print n(a b) 42 > 5 Install instructions Install tensorflow but only in the new environment (also takes time) Ubuntu/Linux 64-bit, CPU only: $ pip install -upgrade cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl Ubuntu/Linux 64-bit, GPU enabled: $ pip install -upgrade gpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl Mac OS X, CPU only: $ pip install -upgrade tensorflow-0.5.0-py2-none-any.whl 4 Install instructions Create a virtual environment with anaconda (it takes some time) $ conda update conda $ conda create -n tensorflow python=2.7 anaconda (tensorflow is the name of the environment, it can be whatever we want) Activate our new environment, prompt changes to (tensorflow)$ $ source activate tensorflow To deactivate the environment you have to write (do it at the end of the session) $ source deactivate 3 Install What is Tensorflow? Implementing Softmax Regression Deep Convolutional Networks in Tensorflow What else? Introduction to convolutional networks using tensorflow
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