Fashion-MNIST LogReg

class deepobs.tensorflow.testproblems.fmnist_logreg.fmnist_logreg(batch_size, l2_reg=None)[source]

DeepOBS test problem class for multinomial logistic regression on Fasion-MNIST.

No regularization is used and the weights and biases are initialized to 0.0.

Parameters:
  • batch_size (int) -- Batch size to use.
  • l2_reg (float) -- No L2-Regularization (weight decay) is used in this test problem. Defaults to None and any input here is ignored.
dataset

The DeepOBS data set class for Fashion-MNIST.

train_init_op

A tensorflow operation initializing the test problem for the training phase.

train_eval_init_op

A tensorflow operation initializing the test problem for evaluating on training data.

test_init_op

A tensorflow operation initializing the test problem for evaluating on test data.

losses

A tf.Tensor of shape (batch_size, ) containing the per-example loss values.

regularizer

A scalar tf.Tensor containing a regularization term. Will always be 0.0 since no regularizer is used.

accuracy

A scalar tf.Tensor containing the mini-batch mean accuracy.

set_up()[source]

Set up the logistic regression test problem on Fashion-MNIST.