Category "deep-learning"

Tensorflow module is not found when running a code on AWS Deep Learning AMI (p2.xlarge)

when running the following code from a jupyter notebook in the ec2 instance: from keras.datasets import imdb the following error message pops out: ModuleNotFoun

Determining cosine similarity for large datasets

I am currently using a dataset of over 2.5 million images, of which I use the image itself as a comparison to eachother, for use in a content-based recommendati

why the value of X_train, y_train and x_test and y_test become - 100 after I put windowed_dataset in python (prediction with deep learning )

i have a problem about my code , i don't know why the value of xtrain ytrain xtest ytest diminue 100 (time_step) - 1 because i have keep the same value like thi

How to reset the state of an LSTM RNN after each epoch within Keras?

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

How does one invert an encoded prediction in Keras for model serving?

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

Is there any way to increase the size during memory sharing between process in PyTorch

My current code is like this: import torch import torch.multiprocessing as mp t = torch.zeros([10,10]) t.share_memory_() processes = [] for i in range(3):

How to change activation layer in Pytorch pretrained module?

How to change the activation layer of a Pytorch pretrained network? Here is my code : print("All modules") for child in net.children(): if isinstance(chi

TypeError: Failed to convert elements of SparseTensor to Tensor

TypeError: Failed to convert elements of SparseTensor(indices=Tensor("DeserializeSparse:0", shape=(None, 2), dtype=int64), values=Tensor("DeserializeSparse:1",

any script to test the installation of Pytorch

I have installed the pytorch, and would like to check are there any script to test whether the installation is correct, e.g., whether it can enable CUDA or not,

load_from_checkpoint fails after transfer learning a LightningModule

I try to transfer learn a LightningModule. The relevant part of the code is this: class DeepFilteringTransferLearning(pl.LightningModule): def __init__(self

Why is there a difference in Intersection over Union (IoU) calculation while evaluating for same data using same model?

I evaluated the IoU score for the test dataset using the saved model. (model.evaluate(test_gen, steps) Also, I have calculated the IoU score for each image in

Model.fit() Validation Accuracy different than Model.predict()

I have created a CNN to do binary classification in keras with the following code: def neural_network(): classifier = Sequential() # Adding a first convolu

Fine Tuning Pretrained Model MobileNet_V2 in Pytorch

I am new to pyTorch and I am trying to Create a Classifier where I have around 10 kinds of Images Folder Dataset, for this task I am using Pretrained model( Mob

Save, Recover, and Continue Updating Learning Curves while Training a CNN if Server Crashes Suddenly

I am training a deep learning model with TensorFlow on a remote server. The problem is that I am only allocated 2 hours of training at a time and the server may

Input 0 of layer "conv2d_transpose_4" is incompatible with the layer: expected ndim=4, found ndim=2. Full shape received: (None, 100)

I am trying to develop a GAN, I have created the generator and the discriminator and now I am trying to train it. I am using the Mnist dataset but I plan to use

ValueError: logits and labels must have the same shape ((None, 328, 328, 3) vs (None, 1)) with autoencoder

I am trying to build an autoencoder with the following code import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns import

Tensorflow Lite model maker: training chart possible?

i am using the Tensorflow Lite Model Maker library to train an efficient model for object detection. It works well, but I don’t know how to get graphs of

Tensorflow Lite model maker: training chart possible?

i am using the Tensorflow Lite Model Maker library to train an efficient model for object detection. It works well, but I don’t know how to get graphs of

Split files for train and test in Google Colab

I have successfully trained and tested my model on local jupyter notebook, but I want to try the same code in Google Colab as I want to try other expensive mode

How to use keras model inside other model in TPU

I am trying to convert a keras model to tpu model in google colab, but this model has another model inside. Take a look at the code: https://colab.research.goo