I have been working on incorporating a customized version of the PElu activation function in TensorFlow. The unique feature of this activation function is that it smooths out the knee of the ReLU. I found the equation for this custom activation function in ...
Currently, I am delving into the realm of Keras for multi-GPU modeling. To test its capabilities before dedicating more time to it, I experimented with a simple skipgram model on a 4 GPU setup provided by lambdalabs. The performance on a single GPU falls ...
After reviewing the information on , I am uncertain about how to access all the necessary parameters. Below is the code snippet I am working with: (hits, ndcgs) = evaluate_model(model, testRatings, testNegatives, topK, evaluation_threads) hr, ndcg, loss ...
I am interested in creating a neural network using keras, sklearn, and tensorflow to predict the (n+1)-th value for a given dataset in a 1-dimensional array. For example, if I have [2,3,12,1,5,3] as input, I would like the output to be [2,3,12,1,5,3,x]. H ...
It seems like the error is related to an issue with shapes, but pinpointing the exact source has been challenging. The error message advises trying the following: Also, consider using the tf.function experimental_relax_shapes=True option to relax argum ...
Here is a crucial part of the code snippet: vgg_model = VGG16(include_top=False, weights='imagenet',input_shape=(img_width, img_height, 3)) model = Sequential() model.add(vgg_model) model.add(Flatten()) model.add(Dense(256, activation='rel ...
After training a neural network model and saving it as '.h5', I am looking to extract all the details of the model including training loss, validation loss, training accuracy, validation accuracy, number of layers, and number of neurons. Is there a way fo ...
Recently, I started learning TensorFlow and decided to try image captioning with VGG by following a tutorial. Unfortunately, I encountered an error message: enter image description here Here's the code snippet in question: model = define_model(vocab ...
UPDATE After using the graph model format and updating the code example, I was able to generate a prediction. However, the issue now is that it consistently returns 1 regardless of the image input. So I'm wondering if I might be passing incorrect image dat ...
I have been working on a transfer learning network and now want to train it on two GPUs for faster results. I have received conflicting advice on the most efficient way to utilize both GPUs. strategy = tf.distribute.MirroredStrategy(devices=["/gpu:0&q ...
I'm trying to figure out how to plot an image that has been converted into an array using keras.preprocessing.image.img_to_array. Here's my approach. To provide a simple example, I downloaded a picture of a duck from the internet: import urllib.request ...
I'm currently in the process of developing a GUI using the kivy framework to build a Keras model. However, I've encountered an issue where the GUI freezes when attempting to train the model. After referring to this resource (https://github.com/kivy/kivy/w ...
I have successfully developed a CNN and now I am exploring ways to test a random image with it. The tools I am using are Keras and Tensorflow. Let's say I want to test the image available at this link: . Could someone guide me on how to save, load th ...
Looking for a solution to address class weight imbalance correction in a multi-class classification scenario. In my neural network model, the output layer is: model.add(Dense(4, activation='sigmoid')) The target variable is stored in a DataFrame with the ...
I encountered an issue while attempting to save a model with data augmentation layers using TensorFlow version 2.7.0. Below is the code snippet for the data augmentation: input_shape_rgb = (img_height, img_width, 3) data_augmentation_rgb = tf.keras.Sequen ...
Trying to construct a convolutional neural network in Python has been quite the challenge for me. After importing TensorFlow and Keras libraries, I loaded the weights of vgg16's convolutional layers to create a neural network capable of categorizing input ...
Currently utilizing Google's Colab to execute the Deep Learning scripts from François Chollet's book "Deep Learning with python." The initial exercise involves using the mnist dataset, but encountering an error: ImportError: cannot import name 'to_categor ...
RuntimeError: Issue detected in input validation: expected input_1 to have 3 dimensions, but received array with shape (6, 7) _____________________________________________________________________________ Layer (type) Output Shape ...
I am currently experimenting with building a custom layer in keras, but I've encountered an unusual issue. The problem arises when I try to sum the tensors before returning the result, causing a change in dimensions. This peculiar situation occurs specific ...
I am currently working on a Decoder with an output shape of (None,32,32,1). However, the following code snippet shows a decoder with an output shape of (None,28,28,1): # Decoder latent_dim = 2 latent_inputs = keras.Input(shape=(latent_dim,)) x = layers.Den ...
My model takes in two inputs - a sequence of vectors and a simple vector, producing a simple vector as an output. For example: x1.shape: (50000,50,2) x2.shape: (50000,2) y.shape: (50000,2) The training and evaluation of my model using model.fit and model. ...
Is there a way to fine-tune the optimization function using Keras Tuner? I'm interested in experimenting with SGD, Adam, and RMSprop. I've attempted: hp_lr = hp.Choice('learning_rate', values=[1e-2, 1e-3, 1e-4]) hp_optimizer = hp.Choic ...
I am looking to implement the DQN code from the Keras-rl library (https://github.com/matthiasplappert/keras-rl/blob/master/examples/dqn_atari.py) for 3-channel images without converting them to grayscale. How can I modify the code to achieve this? I attem ...
I am embarking on my machine learning and Keras journey. I created a Neural Network using Keras for regression which has the following structure: model = Sequential() model.add(Dense(57, input_dim=44, kernel_initializer='normal', activation=&ap ...
Having recently ventured into the realm of machine learning, I'm faced with a challenge in applying it to my specific problem. My training dataset consists of 44000 rows of features with a shape of 6 by 25. My goal is to construct a sequential model, but I ...
Encountered the mentioned issue while coding in Spyder using Anaconda. It seems to have occurred when opening a new file in an environment where I had already created and saved a tf Keras model, and then trying to fetch it in that new file. Despite attemp ...
I want to enhance my keras model by incorporating a callback feature. Specifically, I am looking to get updates on val_acc through a telegram bot message after each epoch. While I understand the concept of adding a callback_list as a parameter in classifie ...
import keras keras.__version__ While working in a .ipynb notebook in VSCode, I attempt to import Keras. To check if Keras is imported correctly, I inquire about the version of Keras that is currently "running". However, I encounter the following error mes ...
I'm currently trying to wrap my head around how to interpret the JSON representation of a Keras model. The field inbound_nodes stores the inputs for each layer, but I'm puzzled by why they are nested within arrays. For instance, when there are 2 inputs fo ...
While experimenting with Keras samples and defining models using subclassing, I encountered some difficulty getting it to work. from keras import layers, Model from keras.datasets import mnist from keras.callbacks import TensorBoard import numpy as np impo ...
I am facing a challenge while creating a keras model with multiple input branches as the inputs have different sizes, resulting in an error message from Keras. Below is an example showcasing this issue: import numpy as np from tensorflow import keras fro ...
Is it possible to generate a 3D representation of a deep learning network in .png or .jpeg format? Currently, Keras only provides a two-dimensional model plotting utility, showing the number of layers and basic properties of each layer (see image link b ...
I am currently developing a model that utilizes MLP for both feature extraction and dimension reduction. This model has the ability to condense data from 204 dimensions down to just 80 dimensions through the following process: A dense layer with 512 dimen ...
Having recently delved into the realms of keras and machine learning, I am experiencing some issues with my code that I believe stem from my model. My objective is to train a model using a CSV file where each row represents a flattened image, essentially m ...
As someone new to deep learning, I am struggling to understand the model.add(layers) function when creating a model. Specifically, I am uncertain about the Dropout value and its significance in my model for recognition tasks. Could someone provide insight ...
My partner and I are collaborating on a project to create a model that can classify images based on whether or not they show someone wearing a mask correctly. However, we're encountering an issue when trying to run our model - a ValueError keeps appea ...