CODEWITHSUNDEEP
machine-learninglinear-regression
user697911
user697911

Reputation: 10531

Are epochs and training steps the same thing?

features = [tf.contrib.layers.real_valued_column("x", dimension=1)]
estimator = tf.contrib.learn.LinearRegressor(feature_columns=features)
y = np.array([0., -1., -2., -3.])
input_fn = tf.contrib.learn.io.numpy_input_fn({"x":x}, y, batch_size=4,
                                              num_epochs=1000)

estimator.fit(input_fn=input_fn, steps=1000)

For example, do these "steps=1000" and "num_epochs=1000" mean exactly the same thing? If yes, why does it need to be duplicated? If not, can i set these two parameters differently?

Upvotes: 3

Views: 1598

Answers (2)

Prune
Prune

Reputation: 77837

No, they are not the same. As with most (all?) Frameworks, Tensorflow has some commands that specify epochs, and some that work on steps, a.k.a iterations. A step is one batch, which is governed by the batch size specified in the model's input.

For instance, if you are using AlexNet with its default batch size of 256, and the ILSVRC 2012 data set of roughly 1.28M images, then you have about 5000 steps per epoch (1,280,000 / 256).

Batch size is the number of images processed in parallel. If there are 1.28M images in the data set, then you have to process 12.8M images per epoch: that's the definition of epoch -- process each input once. Now is that arithmetic clear?

Upvotes: 2

Abhimanu Kumar
Abhimanu Kumar

Reputation: 1791

Here is the basic difference between epoch and steps in any machine learning algorithm or framework:

Once the framework goes through all the data points in its training set to update its parameters it's called one epoch. A step is one update of the parameters (e.g. weights of the neural network if it training DNN). This update can be obtained using a single data point, or a mini-batch of data points (e.g. randomly drawing 100 data points, with or without replacement), or all the points. Hence as you can see if all your datapoints are used in one step (or update of parameters) it becomes one epoch i.e. one step = one epoch.

Typically frameworks use mini-batching and in one step they batch 100 (or some other number) datapoints together and do one update. In this case, if say you have total 1 million datapoints (10^6) then one epoch has 10000 steps since one step contains 100 datapoints.

Upvotes: 3

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