MNIST LogReg¶
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class
deepobs.tensorflow.testproblems.mnist_logreg.
mnist_logreg
(batch_size, weight_decay=None)[source]¶ DeepOBS test problem class for multinomial logistic regression on MNIST.
No regularization is used and the weights and biases are initialized to
0.0
.Parameters: - batch_size (int) -- Batch size to use.
- weight_decay (float) -- No weight decay (L2-regularization) is used in this
test problem. Defaults to
None
and any input here is ignored.
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dataset
¶ The DeepOBS data set class for MNIST.
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train_init_op
¶ A tensorflow operation initializing the test problem for the training phase.
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train_eval_init_op
¶ A tensorflow operation initializing the test problem for evaluating on training data.
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test_init_op
¶ A tensorflow operation initializing the test problem for evaluating on test data.
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losses
¶ A tf.Tensor of shape (batch_size, ) containing the per-example loss values.
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regularizer
¶ A scalar tf.Tensor containing a regularization term. Will always be
0.0
since no regularizer is used.
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accuracy
¶ A scalar tf.Tensor containing the mini-batch mean accuracy.