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Questions tagged [tensorflow]

A Python library for deep learning developed by Google. Use this tag for any on-topic question that (a) involves tensorflow either as a critical part of the question or expected answer, & (b) is not just about how to use tensorflow.

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6 views

How to reshape input data in RNN model for prediction [on hold]

While making prediction with a built model using new data, an error returned because the shape is different: Here's the code: ...
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1answer
64 views

How to compare CNN models with non-reproducible results?

I try to compare different CNN models. I use Keras and for training, I use a GPU, Google Colab with Tensorflow backend. Unfortunately I'm not able to create the same initial conditions for the CNNs (...
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14 views

Is skip-gram model of word embedding actually a multi-class task not a multi-label task, right?

So curious about this question, that I can't describe it in short. Please forgive me. Description: From multiclass and multilabel algorithms, we can get the definition of the multi-class and multi-...
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11 views

Why does Dice loss neglect to predict a random subset of classes?

I implemented Dice loss for a semantic segmentation problem (with a severe class imbalance in my dataset) as follows: ...
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19 views

Unable to tackle Poor Predictions despite high training and validation accuracies [duplicate]

I have trained a transfer learning model for classifying image objects (Rocks) as Large or Small. I have obtained 98% accuracies for both : training and validation. On using the model to make ...
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2answers
41 views

What does it means when MSE almost equal with labels' variance?

I did a training for my dataset of 6000 images. running np.var(train_data), I get 2435. After training of enough epochs, my MSE is nearly 2415+-. Is this means, that the model is unable to find any ...
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23 views

Teaching movie recommendation network to avoid duplicates

I'm trying to implement a simple movie recommender using a neural network and collaborative filtering, i.e. given a list of movies the user has watched, what is a good movie recommendation. Results ...
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16 views

How can I coumpute Policy Gradient LOSS in tensorflow

I am self-studying RL and currently doing hw2 from Berkeley CS294-112. The thing I cannot figure out is how to compute loss in policy gradients. Basically, REINFORCE algorithm has the following update ...
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1answer
38 views

Which machine learning model could be used for the following?

I am an experienced programmer but very new to machine learning. I have a data set that consists of about 50,000 sets of 2,000 ordered values. All of the values are floats normalised to between 0 and ...
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18 views

Is it a good idea to implement a sklearn model for a real time image processing application?

I'm testing a support vector machine (SVM) model trained with scikit learn library for image processing, but i don't know exactly if for real time this library could be better than tensorflow or both ...
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20 views

Why the Logistic regression model trained with tensorflow performed so poor

I trained a logistic regression model with tensorflow but the accuracy of the model was so poor (accuracy = 0.68). The model was trained using simulated dataset and the result should be very good. is ...
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33 views

Why Massive Random Spikes of Validation Loss?

My problem is to estimate the length of a straight line in an image, in pixel. My training size is 6000 images, validation is 1000 images. Each image has 200 x 200 pixels. My data is generated using ...
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1answer
108 views

Loss function (and encoding?) for angles

I'm training a network to predict the angle of arrival of a signal. Labels are single values in the [-180, 180) interval. I'm seeing a discontinuity in predictions around ±180 degrees, which makes ...
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28 views

What is default error threshold Tensorflow? [closed]

My homework states that I am asked "to report the default error threshold used in the TensorFlow default configuration for convergence. Usually it is documented for MNIST and CIFAR-10". What's that? ...
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7 views

Can a neural network independently change its learning parameters while the error between what was predicted and what was not the most minimal in R

I performed script which create forecast of usd/btc pair. Data was taken form open source https://www.cryptodatadownload.com/apac/ https://www.cryptodatadownload.com/cdd/Binance_BTCUSDT_1h.csv Here ...
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1answer
80 views

no attribute '_inbound_nodes' error even when using Lambda layer in Keras [closed]

I have a (28,000 x 300) dimension matrix, let's call it label_embedding, which I want to do a dot product with the bottleneck layer of my model. I have created an architecture which gives a (...
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37 views

Unable to learn weights of a Word2Vec model [duplicate]

I was going to implement a word embedding model - namely Word2Vec - by following this TensorFlow tutorial and adapting the code a little bit. Unfortunately, though, my model won't learn anything. I've ...
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7 views

Needing 4th dimension for shape [closed]

I was working on a transfer learning solution to categorize between diseases in the eye. I was using the Xception model built into Keras and it uses a data set that I was able to accumulate. However ...
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1answer
26 views

How do I fix this dimenion error in keras / tensorflow? [closed]

This is the code I am trying to run. X is an array of shape (1000,26) and Y is of shape (1000, 1). I am trying to fit a model that predicts a 1 or a 0 for each row of the X array. For whatever reason ...
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21 views

Chinese character recognition from generated images - Validation accuracy does not improve

I am currently working on creating a simple Chinese character recognition network. Given an grayscale image of a character, the goal is to predict the depicted character. I want to run the model on a ...
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15 views

Data balancing in image classification

I've to segment defects from an image. The image consists of only tomatoes with it's defects in it. The defects and tomatoes in the dataset are as follows: ...
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1answer
15 views

Increasing sample size increases no of trainable parameters

I was working with keras and tensorflow as backend on an NLP problem when I observed that increasing my training data size caused an increase in the number of trainable parameters even when batch size ...
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14 views

How can I iterate on the hidden activations in a neural network? - Lifetime and spatial sparsity in WTA Autoencoders

I've built a convolutional autoencoder and trained it on MNIST in keras and tensorflow. I wanted to make this autoencoder a WTA autoencoder as talked about in this paper. To do so, I need to add ...
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41 views

How to choose number of neurons and hidden layers? [duplicate]

I followed this guy's tutorial on YouTube. Following is the code that was used for classifying 0 to 9 handwritten digits from MNIST dataset. The dataset contains 70,000 images of 28 x 28. Here, 60,000 ...
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1answer
103 views

MAP of Gaussian Process Classification in Tensorflow Probability

I'm attempting to implement Gaussian Process Classification learning in tensorflow-probability, but my estimator turns out to be very biased toward zero. As opposed ...
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1answer
25 views

Dynamic/ Static outputs are not same, why?

I am trying to implement a patch creation function with using tensorflow's extract_image_patches function but dynamic output shape is not same as my expectation. Let me tell briefly what it does. ...
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39 views

MNIST with Tensorflow and Keras, same architecture but less accurate in Tensorflow

I implemented a neural network in Keras and Tensorflow to make predictions on the MNIST dataset. I used the same architecture for both Keras and Tensorflow. While the code in Keras gives me always an ...
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30 views

Neural Network to discover an unknown number of patterns from a dataset of images?

I have a big set of images (>10.000), where there are similarities among them. I need to find a number/group of image patterns (eg, 5) that represent all images. As I do not know what patterns are, ...
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1answer
104 views

Tensorflow 2.0/Keras - loss function with multiple inputs

I have a case where my model has multiple outputs, and I want to backpropagate the loss on one of the outputs based on a different label. Basically, the model should detect whether an object is in an ...
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11 views

How to extract fixed sized feature vector from arbitrary graph data?

So I am dealing with graph data and graph neural networks. Usually a graph convolution network takes an adjacency matrix and one feature vector like this : ...
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0answers
20 views

When should I stop the object detection model training while mAP are not stable?

I am re-training the SSD MobileNet with 900 images from the Berkeley Deep Drive dataset, and eval towards 100 images from that dataset. The problem is that after ...
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12 views

Tensorflow: MNIST CNN only predicting 4s and 5s? [duplicate]

I am attempting to create my first CNN in TensorFlow. The objective is able to predict the MNIST Dataset. I have come across a very odd issue...my model is only able to predict 4s or 5s. There seems ...
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24 views

How can I interpret the result of get_weight of latent size in Seq2Seq model keras

My question is related to Seq2Seq models where we have LSTM as encoder and decoder. Imagine we have the Autoencoder alone, and we extract the weight associated ...
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1answer
19 views

TensorFlow 2.0 output specification in NLP model

I just started playing with TensorFlow 2.0 now that the new api is out. However, I do not get the model output specification. The model below is a simple example ...
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1answer
16 views

Class Imbalence Problem even after Balancing Data

So I am training a neural network on a binary classification problem and my Case (1) and Controls (0) were imbalanced so I oversampled my cases so that that the training set was 0.5053 made up of ...
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1answer
43 views

Why are weights being used in (generalized) dice loss, and why can't I? [closed]

Generalized dice loss is advocated as optimizing mIoU directly in semantic segmentation problems (especially those with a severe class imbalance), as opposed to other loss functions like multinomial ...
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10 views

Electronic equipment failure prediction/abnormal behavior detection model

I have a data set of alarm logs and event logs of network equipment with timestamps and I'm looking to build a machine learning failure prediction/ abnormal behavior detection model using python. ...
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27 views

How do I set up my hyper-parameter space for optimizing a convolutional neural network (using packages Skopt and Tensorflow)

I just finished building a 1D CNN using TensorFlow, and I want to optimize a variety of hyper-parameters using Scikit-Optimize (skopt) (although, I would be willing to use whatever optimization ...
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1answer
25 views

Meaning of Graph from tensorBoard

Can someone please help me to interpret the graph from tensorBoard. I have attached the screenshot herewith.
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13 views

Reference for Inception-v2

Cross-posted from Data Science StackExchange. The "Rethinking" paper doesn't describe the actual implementation of the Inception-v3 model in Tensorflow: an accurate description is written in model....
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58 views

BiLSTMs with Attention model for Multi-Label Multi-Class Classification

I am trying the modify the BiLSTM with Attention model he used in Course 5 Neural Machine Translation for predicting grades (ranging from O,A+,A,B+,B,C,D,E,F) for multiple subject (approx 9 subjects ) ...
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1answer
58 views

How to handle timeseries extremes (sigma > 20) in deep learning?

I'm using 16-channel, 400-Hz, standardized EEG data to train CNN-LSTM for seizure classification. The data contains $O(3)$ sigma > 20 points, rarely thousands in a ...
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41 views

Is there a way to implement something like sklearn's GridSearchCV for Tensorflow estimators?

Grid Search CV works fine for sklearn models as well as keras, however do we have any alternative for this specifically for tf estimators? Would be great if someone can guide in right direction
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63 views

How to reduce impact of false positive images in Tensorflow Object Detection Framework?

I am training a single object detector(for car) with Faster R-CNN with Inception v2 config file. I started with around 300 examples of images of the object with bounding boxes and trained that, got ...
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0answers
253 views

Many false positives in a custom SSD model with Tensorflow object detection API

My model has 2 classes (no background class) and is trained using transfer learning with ssd_mobilenet_v2_coco. It detects and classifies well the objects it was trained on. However, on new images it ...
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1answer
54 views

Softmax with Cross Entropy optimization vs Backpropagation

I am following a tutorial from Analytics Vidhya on creating a neural network to recognize handwritten digits (the classic example). The code from the tutorial states "First we need to define the ...
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0answers
33 views

Create TensorFlow Dataset with multiple data sources

I am trying to create a TensorFlow Dataset by joining data from 2 different sources. I am trying to replicate the dataset creation from the following paper: https://arxiv.org/abs/1809.01984 ...
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25 views

Pytorch logging: Native tensorboard support v/s TensorboardX

PyTorch recently released v 1.1.0, which has native support for Tensorboard. How does this compare with TensorboardX? I thought it would be good to list the pros and cons here. I am new to PyTorch ...