From c4a662465e750bb7a0def8a9f24a2ff115ba0e6f Mon Sep 17 00:00:00 2001 From: Matt Graham Date: Thu, 19 Jan 2017 10:49:10 +0000 Subject: [PATCH] Clarifying initializers description: notebook save failed in previous commit. --- notebooks/08_Introduction_to_TensorFlow.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/notebooks/08_Introduction_to_TensorFlow.ipynb b/notebooks/08_Introduction_to_TensorFlow.ipynb index 57c91da..4e610da 100644 --- a/notebooks/08_Introduction_to_TensorFlow.ipynb +++ b/notebooks/08_Introduction_to_TensorFlow.ipynb @@ -47,7 +47,7 @@ "\n", "TensorFlow allows complex computation graphs (also known as data flow graphs in TensorFlow parlance) to be defined via a Python interface, with efficient C++ implementations for running the corresponding operations on different devices. TensorFlow also includes tools for automatic gradient computation and a large and growing suite of pre-define operations useful for gradient-based training of machine learning models.\n", "\n", - "In this notebook we will introduce some of the basic elements of constructing, training and evaluating models with TensorFlow. This will use similar material to some of the [official TensorFlow tutorials](https://www.tensorflow.org/tutorials/) but with an additional emphasis of making links to the material covered in this course last semester. For those who have not used a computational graph framework such as TensorFlow or Theano before you may find the [basic usage tutorial](https://www.tensorflow.org/get_started/basic_usage) useful to go through\n", + "In this notebook we will introduce some of the basic elements of constructing, training and evaluating models with TensorFlow. This will use similar material to some of the [official TensorFlow tutorials](https://www.tensorflow.org/tutorials/) but with an additional emphasis of making links to the material covered in this course last semester. For those who have not used a computational graph framework such as TensorFlow or Theano before you may find the [basic usage tutorial](https://www.tensorflow.org/get_started/basic_usage) useful to go through.\n", "\n", "### Installing TensorFlow\n", "\n", @@ -252,7 +252,7 @@ "\n", "A standard operation which needs to be called before any other operations on a graph which includes variable nodes is a variable *initializer* operation. This, as the name suggests, initialises the values of the variables in the session to the values defined by the `initial_value` argument when adding the variables to the graph. For instance for the graph we have defined here this will initialise the `weights` variable value in the session to a 2D array of zeros of shape `(784, 10)` and the `biases` variable to a 1D array of shape `(10,)`.\n", "\n", - "We can create initializer ops for each variable individually using the `initializer` method of the variables in question and then individually run these, however a common pattern is to use the `tf.global_variables_initializer()` function to create a single initializer op which will initialise all globally defined variables in the default graph and then run this as done below." + "We can access initializer ops for each variable individually using the `initializer` property of the variables in question and then individually run these, however a common pattern is to use the `tf.global_variables_initializer()` function to create a single initializer op which will initialise all globally defined variables in the default graph and then run this as done below." ] }, {