Category "keras"

tensorflow:Can save best model only with val_acc available, skipping

I have an issue with tf.callbacks.ModelChekpoint. As you can see in my log file, the warning comes always before the last iteration where the val_acc is calcula

Tensorflow's seq2seq: tensorflow.python.framework.errors_impl.InvalidArgumentError

I am following quite closely the Seq2seq for translation tutorial here https://www.tensorflow.org/addons/tutorials/networks_seq2seq_nmt#define_the_optimizer_and

Getting error in Spyder Anaconda from Keras Libraries CNN: WARNING:root:Limited tf.compat.v2.summary API due to missing TensorBoard installation

I am trying to implement the Keras libraries for Convolutional Neural Networks on my Spyder IDE using Anaconda as such: from keras.models import Sequential

nearly 0% GPU-Util but high GPU Memory

A newbie for machine learning here. I'm now training a fairly easy model from tutorial using the dataset fashion_mnist on Win10. However, the training process t

frequency of words in text not present in another text with tf.Tokenizer

I have a text A and a text B. I wish to find the percentage of words in text B (counting all occurrences) not present in the vocabulary (i.e., the list of all u

making GRU/LSTM states trainable in Tensorflow/Keras and add some random noise

I train the following model based on GRU, note that I am passing the argument stateful=True to the GRU builder. class LearningToSurpriseModel(tf.keras.Model):

Tensorflow LSTM/GRU reset states once per epoch and not for each new batch

I train the following model based on GRU, note that I am passing the argument stateful=True to the GRU builder. class LearningToSurpriseModel(tf.keras.Model):

How to properly initialize TensorFlow GRU-layer with noisy states?

I wish to experiement with noisy GRU states instead of resetting them to zero for each batch. I try below an implementation. My initial code was resetting initi

TypeError: Inputs to a layer should be tensors. Got: <tensorflow.python.keras.engine.functional.Functional object at 0x000001ADE3B6BEE0>

I'm trying to Implement Inception_resnet_v2 inside Faster-RCNN instead of using ResNet50. but when I try to run the code I got this TypeError: TypeError: Inputs

How to overcome "TypeError: Exception encountered when calling layer "tf.keras.backend.rnn" (type TFOpLambda)"?

I'm trying to re-implement the text summarization tutorial here. The tutorial employs the Attention Layer proposed for Keras on GitHub (which does not come with

sklearn train_test_split on list of 3-dimensional arrays

I want to do image classification and I have as data_X a list of 12000 three-dimensional numpy arrays. Those arrays all have the shape 300 x 300 x 3 (height, wi

Tensorflow Keras Dataset Filepath within PyCharm

I have seen this question and the answer. This doesn't help. I have MAC environment. Used Anaconda. And there is no .Keras folder under users directory. I was

Having issues with SGD/Keras in my AI chatbot

Hello there guys. First time making a post here. So I am trying to make an AI chatbot using Python, in a Pycharm IDLE. While trying to start training the neura

keras AssertionError: Duplicate registrations for type 'experimentalOptimizer'

I'm trying to build a Deep Q Learning code for CartPole-v1 game. However I encounter an AssertionError: AssertionError: Duplicate registrations for type 'experi

Is it possible to automatically infer the class_weight from flow_from_directory in Keras?

I have an imbalanced multi-class dataset and I want to use the class_weight argument from fit_generator to give weights to the classes according to the number o

Keras: network doesn't train with fit_generator()

I'm using Keras on the large dataset (Music autotagging with MagnaTagATune dataset). So I've tried to use fit_generator() fuction with a custom data generator.

Keras - Plot training, validation and test set accuracy

I want to plot the output of this simple neural network: model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) history = model.fit

Could not load dynamic library 'cudart64_101.dll' on tensorflow CPU-only installation

I just installed the latest version of Tensorflow via pip install tensorflow and whenever I run a program, I get the log message: W tensorflow/stream_execut

Keras verbose training progress bar writing a new line on each batch issue

running a Dense feed-forward neural net in Keras. there are class_weights for two outputs, and sample_weights for a third output. fore some reason it prints the

Keras verbose training progress bar writing a new line on each batch issue

running a Dense feed-forward neural net in Keras. there are class_weights for two outputs, and sample_weights for a third output. fore some reason it prints the