How to run keras.model.fit() in graph not with eager execution...?? I tried to run my model in graph by using tf.compat.v1.disable_eager_execution(), but the c
When I try to use a custom activation function in keras (2.2.5), I create a new activation function gelu. add it in activations.py : from . import backend as K
So about a week ago I posted this question: Issues running a Keras model with custom layers. The suggestion there was to try to make this question smaller and t
""" Defining two sets of inputs Input_A: input from the features Input_B: input from images my train_features has (792,192) shape my train_images has (792,28,28
Say I have a Custom Layer : class Custom_Layer(keras.layers.Layer): def __init__(self, **kwargs): self.w_0 = tf.Variable(tf.random_uniform_initializ
how can you save a keras model in 64bit format? This is able to 'put tensorflow' in 64bit 'mode' for the current runtime. But I've found that even just saving t
I am new to Machine Learning, and I followed this tutorial to implement LSTM model in Keras/Tensorflow: https://www.tensorflow.org/tutorials/structured_data/tim
I've created a multi-class image classifier using CNN. I am using the keras module specifically and I am using generators to fit and then predict 4 different cl
model.compile( optimizer= keras.optimizers.Adam(), loss= [keras.losses.SparseCategoricalCrossentropy(from_logits= True) ], metrices= ['accuracy']) mode
Tensorflow/Keras I have developed a CNN model to classify images as circle, triangle or square. However, my accuracy values have wide fluctuations. Is it someth
I am new to machine learning. I got the intermediate result of layer 31 of my CNN using the following code: conv2d = Model(inputs = self.model_ori.input, output
tf.keras.layers.TextVectorization layer maps text features to integer sequences, and since it can be added as a keras model layer it makes it easy to deploy the
I followed the tutorial here to try to train my model using CIFAR-100. But I'm getting this error. What do I do? ValueError: Data Params Error: The dataset labe
I'm currently implement the sequantial deep matching model (https://arxiv.org/abs/1909.00385) using tensorflow 2.3. And I included the preprocessing layer as pa
I want to distill knowledge from a teacher student to a student one, so I implemented a class named OCCSE that inherits from tf.keras.Model and accepts both tea
I'm trying to build a model which can be trained on both audio and video samples but I get this error ValueError: Please initialize `TimeDistributed` layer with
I am trying to make a toy example work; there is a simple submodel: Model: "sub_model" _________________________________________________________________ Layer
I am working on an image classification task to classify among cars and buses. The problem is that in most car images, there is buses in the background and vice
I used a convolutional neural network (CNN) for training a dataset and I want to plotting accuracy for this. Before, I tried to use matplotlib but I couldn't su
I've problems integrating Bert Embedding Layer in a BiLSTM model for text classification task. My dataset is in the form where each row has 2 columns: text and