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I'm working with Tensorflow and Keras and trying to get the output of my model into Tensorboard for easy graph generation and visualization. This has worked fine so far for model.fit's callback, but model.evaluate does not have any sort of writing to Tensorboard. I looked on StackOverflow and I found one other person with this issue, but they never got a response.

This is the relevant part of my code, and I can give more as needed.


log_dir1 = 'C:/Users/myname/Desktop/DATASET/logs'

tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir1, histogram_freq=1)

history = model.fit(train_data_keras, epochs=1, validation_data=valid_data_keras, callbacks= [tensorboard_callback])


model.evaluate(test_data_keras, callbacks = [tensorboard_callback])

I'm working with Tensorflow and Keras and trying to get the output of my model into Tensorboard for easy graph generation and visualization. This has worked fine so far for model.fit's callback, but model.evaluate does not have any sort of writing to Tensorboard. I looked on StackOverflow and I found one other person with this issue, but they never got a response.

This is the relevant part of my code, and I can give more as needed.


log_dir1 = 'C:/Users/myname/Desktop/DATASET/logs'

tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir1, histogram_freq=1)

history = model.fit(train_data_keras, epochs=1, validation_data=valid_data_keras, callbacks= [tensorboard_callback])


model.evaluate(test_data_keras, callbacks = [tensorboard_callback])

本文标签： tensorflowTensorboard callback on modelevaluate()Stack Overflow

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