Main objective PyTorch equivalent for SeparableConv2D with padding = 'same': from tensorflow.keras.layers import SeparableConv2D x = SeparableConv2D(64, (1, 16), use_bias = False, padding = 'same')...

I'm using Lasagne to create a CNN for the MNIST dataset. I'm following closely to this example: Convolutional Neural Networks and Feature Extraction with Python. The CNN architecture I have at the...

This seems to be one of the common questions on here (1, 2, 3), but I am still struggling to define the right shape for input to PyTorch conv1D. I have text sequences of length 512 (number of token...

I'm trying to use a pre-trained template on my image set by following the tutorial right here : https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html Only I always get ...

I'm using Pytorch to classify a series of images. The NN is defined as follows: model = models.vgg16(pretrained=True) model.cuda() for param in model.parameters(): param.requires_grad = False cl...

import os.path as osp import torch import torch.nn as nn import torch.nn.functional as F from torch_geometric.datasets import MNISTSuperpixels import torch_geometric.transforms as T from torch_geom...

I am reading through Residual learning, and I have a question. What is "linear projection" mentioned in 3.2? Looks pretty simple once got this but could not get the idea... Can some...

The documentation for the conv2d_transpose() operation does not clearly explain what it does: The transpose of conv2d. This operation is sometimes called "deconvolution" after Deconvolutiona...

I've seen division by 255 used many times as normalization in CNN tutorials online, and this is done across the entire dataset before train test split. I was under the impression that the test set...

I'm trying to train a basic CNN on the image dataset that contains faces of celebrities with the class assigned corresponding to each person. Given that there are about 10,000 classes I used sparse...

I'm adding some batch normalization to my model in order to improve the training time, following some tutorials. This is my model: model = Sequential() model.add(Conv2D(16, kernel_size=(3, 3), ac...

I am trying to tune the hyper parameter i.e batch size in CNN.I have a computer of corei7,RAM 12GB and i am training a CNN network with CIFAR-10 dataset which can be found in this blog.Now At first...

I would like to understand the ConvLSTM2D Keras layer a bit better. Does it execute an 2D convolution on a 2D input (image) and then average/ flatten its ouptut and feed that into a LSTM module? Bu...

Hello question regarding reshaping an array. I have an array train_x (2D) which content is (103,784) In this case 103 is the amount of examples. 784 is the input of my neural network. Now I wan...

A lot of articles are using CNNs to extract audio features. The input data is a spectrogram with two dimensions, time and frequency. When creating an audio spectrogram, you need to specify the exa...

I installed the mtcnn package, as can be seen: # confirm mtcnn was installed correctly import mtcnn # print version print(mtcnn.__version__) Result: 0.0.9 Then I use the following: # prepare...

I am working on a project in which I have to pass the output of CNN to Bi directional LSTM. I created the model as below but it is throwing 'incompatible' error. Please let me know where I am going...

I trained two models in order to ensemble them, when I try to load them with this code: from tensorflow.keras.models import load_model models=[] modelTemp=load_model('models/full.h5') modelTem...

Import libraries and models, from __future__ import print_function import keras from keras.datasets import mnist from keras.models import Sequential from keras.layers import Dense, Dropout, Flatten...

I saw MTCNN being recommended but haven't seen a direct comparison of DLIB and MTCNN. I assume since MTCNN uses a neural networks it might work better for more use cases, but also have some surpri...

I am building a CNN with Conv1D layers, and it trains pretty well. I'm now looking into how to reduce the number of features before feeding it into a Dense layer at the end of the model, so I've be...

We can generate image dataset using ImageDataGenerator with flow_from_directory method. For calling list of class, we can use oject.classes. But, how to call list of values? I've searched and still...

I am trying to create several LSTM models for time series prediction (e.g. Vanilla, Stacked, Bidirectional). After creating a model I want to save it using tf.keras.models.save_model This works fi...

I was running TensorFlow and I happen to have something yielding a NaN. I'd like to know what it is but I do not know how to do this. The main issue is that in a "normal" procedural program I would...

Currently I use the following code: callbacks = [ EarlyStopping(monitor='val_loss', patience=2, verbose=0), ModelCheckpoint(kfold_weights_path, monitor='val_loss', save_best_only=True, verbose=0...