tf-slim

I'm using a script that comes with TF-Slim to validate my trained model. It works fine but I'd like to get a list of the misclassified files. The script makes use of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/slim/python/slim/evaluation.py but even there I cannot find any options for printing the misclassified files. How can I achieve that? At a high level, you need to do 3 things: 1) Get your filename from the data loader. If you are using a tf-slim dataset from tfrecords, it is likely that the filenames are not stored in the tfrecord so you may be out of luck

Is there any way that I can log the validaton loss and accuracy to tensorboard when using tf-slim? When I was using keras, the following code can do this for me: model.fit_generator(generator=train_gen(), validation_data=valid_gen(),...) Then the model will evaluate the validation loss and accuracy after each epoch, which is very convenient. But how to achieve this using tf-slim? The following steps are using primitive tensorflow, which is not what I want: with tf.Session() as sess: for step in range(100000): sess.run(train_op, feed_dict={X: X_train, y: y_train}) if n % batch_size * batches

I am using tf.slim to implement an autoencoder. I's fully convolutional with the following architecture: [conv, outputs = 1] => [conv, outputs = 15] => [conv, outputs = 25] => => [conv_transpose, outputs = 25] => [conv_transpose, outputs = 15] => [conv_transpose, outputs = 1] It has to be fully convolutional and I cannot do pooling (limitations of the larger problem). I want to use tied weights, so encoder_W_3 = decoder_W_1_Transposed (so the weights of the first decoder layer are the ones of the last encoder layer, transposed). If I reuse weights the regular way tfslim lets you reuse them, i