This question is a follow-up of tensorflow 2 TextVectorization process tensor and dataset error I would like to make do a word embedding for the processed text
let say I got two tensor where tensor A has shape (100,7), tensor B has shape (100,7,64). I want to pick the first item from A and B and multiply them by tf.mat
I am trying to use Tensorflow to create a recommendation system. What I want to do is to read data from two csv files, one containing 'item_id' and the other co
So I have a problem when train deep learning with BERT with tensorflow which contain text dataset. So i want to fit() the model but got an error when training.
let say I got two tensor where tensor A has shape (100,7), tensor B has shape (100,7,64). I want to pick the first item from A and B and multiply them by tf.mat
I have list of labels corresponding numbers of files in directory example: [1,2,3] train_ds = tf.keras.utils.image_dataset_from_directory( train_path, label
import pandas as pd import numpy as np from sklearn.preprocessing import StandardScaler from keras import Sequential from tensorflow.keras.layers import Dense f
I'm trying to call a TensorFlow model on a linspace but I can't seem to get even a very simple example (based on https://www.tensorflow.org/api_docs/python/tf/k
I have a LSTM model. which when I try to fit i get the error mentioned in the title. I have an array of timeseries data with multiple features I'm feeding as in
I am training a Keras (Tensorflow backend, Python, on MacBook) and am getting an error in the early stopping callback in fit_generator function. The error is a
When trying to run import numpy as np import keras X = np.ones((100,20)) Y1 = np.ones((100,5)) Y2 = np.ones((100,4)) Input_1= keras.layers.Input(shape=X.shape
It is required to resample audio signals within a custom model structure. This resampling task is not a kind of pre/post-processing operation that can be develo
I want to plot my model using Keras.utils.plot_model function. my problem is that when I plot the model, the input and output shapes do not place on top of each
So there's a big update nowadays, moving from TensorFlow 1.X to 2.X. In TF 1.X I got use to a pipeline which helped me to push my keras model to production. Th
I have defined a stateful LSTM RNN, and I want to reset the state of the RNN after each epoch. I have found that one way to do this would be: n_epochs = 50 for
I have a Keras model in which i have successfully added a StringLookUp pre-processing step as part of the model definition. This is generally a good practice be
I try to pass 2 loss functions to a model as Keras allows that. loss: String (name of objective function) or objective function or Loss instance. See losses. I
I am working on a modified resnet, and want to insert dropout after activation layers. I have tried the following but due to the model not being sequential, it
I am running ANFIS algorithm on iris dataset. While adding fuzzylayer to the model i am getting error like below: TypeError: <lambda>() got an unexpected
I have created a CNN to do binary classification in keras with the following code: def neural_network(): classifier = Sequential() # Adding a first convolu