Category "deep-learning"

A `Concatenate` layer requires inputs with matching shapes except for the concatenation axis. Received: input_shape=[(None, 28), (None, 28, 28)]

""" 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

input_image_meta shape error while using pixellib custom trainig on images

I am using pixellib fot training custom image instance segmentation. I have created a dataset whiche can be seen below in link. Dataset:https://drive.google.com

How to decorate a function that takes a tf.variable as a parameter with tf.function and most importantly using input signature

I have a problem where I need to modify a variable inside a Tensorflow function. Then I need to convert this function to a tensorflow graph. The problem is that

How do I remove nonsensical or incomplete words from a corpus?

I am using some text for some NLP analyses. I have cleaned the text taking steps to remove non-alphanumeric characters, blanks, duplicate words and stopwords, a

CNN model accuracy fluctuates

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

How i can extracte x_train and y_train from train_generator?

In my CNN model I want to extract X_train and y_train from train_generator. I want to use ensemble learning, bagging and boosting to evaluate the model. the mai

How to use the output of a CNN as the input of another in an autonomous vehicle

I am developing a mini autonomous car using 3 CNNs and a camera sensor using this approach. One of the CNNs detects lanes on the images and outputs images wit

ValueError: Please initialize `TimeDistributed` layer with a `Layer` instance

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

got nan in keras tuner but it works when I train it

I trained my network several times and I already got some results. Then I found out about the Keras tuner and wanted to find the best hyperparameters with it. b

How can I use tensorflow to create a recommendation system that returns a ratings matrix?

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

Target Data Missing from tensorflow fit()

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.

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,

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