Questions tagged [tensorflow]

For questions related to Google's open source library for machine learning and machine intelligence.

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31 views

Why does the bias need to be a vector in a neural network?

I am learning to use tensorflow.js. I am also using the tfvis library to print information about the neural net to the web browser. When I create a create a dense neural net with a layer with 5 ...
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1answer
56 views

What are the differences between TensorFlow and PyTorch?

What are the differences between TensorFlow and PyTorch, both in terms of performance and functionality?
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10 views

How to build sort objects model using Deep Learning

How to build sort objects model using Deep Learning if i have some objects in an image enter image description here if i give him an similar image he sort the detected order according to Learning ...
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16 views

How to use Before / After images to train a model

I am trying to create a model that can clean pictures of noise, blur, high luminosity etc, but I do not know how to do that. I have tried to search for it a lot, and I couldn't find anything that ...
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22 views

How can I train a Deep Learning model using degraded photos and their clean version to correct photos

I have 5000 degraded pictures ( pixelated, blurry, too much luminosity ... ) and their clean versions, and I would like to train a model so that it can predict how to correct future pictures. I've ...
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1answer
29 views

Multiple GPUs one expensive GPU, which gpu to buy for real time processing (not training)

I am trying to decide what GPU or GPUs to buy to run tf-pose pose detection and yolo3 object detection on several cameras. I need to keep an acceptable frame rate too. what kind of GPU configuration ...
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32 views

Do the variables contain the old state when a tensorflow optimizer is interrupted? [closed]

I noticed in the GPT-2 training code, that it saves on keyboard interrupt, with the iteration number of the optimization step that was interrupted, but without printing the loss. See https://github....
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3answers
323 views

How to reproduce neural network training with keras

I want to see the effects of changing some training parameters (batch size, learning rate, optimizer...) to the accuracy obtained. The problem is that with the same parameters I get significantlly ...
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2answers
426 views

Effect of batch size and number of GPUs on model accuracy

I have a data set which was split using a fixed random seed and I am going to use 80% of data for training and rest on validation. Here are my GPU and batch size configurations use ...
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1answer
55 views

Tensorflow Lite model vs Tensorflow Model

I have explored edge computation for AI and I came across multiple library or framework which can help to convert model into lite format which is suitable for edge devices. ...
4
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1answer
758 views

How do you handle multiple categorical values in a single column for wide_deep model in tensorflow?

To start, let me just say that I am very new to tensorflow and Machine Learning in general. But, as part of my learning project I am trying to adapt the tensorflow wide and deep model to generate ...
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1answer
53 views

Are there ensemble methods for regression?

I have heard of ensemble methods, such as XGBoost, for binary or categorical machine learning models. However, does this exist for regression? If so, how are the weights for each model in the process ...
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1answer
43 views

Why do we average gradients and not loss in distributed training?

I'm running some distributed trainings in Tensorflow with Horovod. It runs training separately on multiple workers, each of which uses the same weights and does forward pass on unique data. Computed ...
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0answers
19 views

Reasoning behind $Zero$ validation accuracy in the following ResNet50 model for classification

I have written this code to classify Cats and dogs using Resnet50. Actually while studying I came to the conclusion that Transfer learning gives very good accuracy for deep learning models, but I ...
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23 views

Can anyone explain the pixelwise accuracy metric used in this paper? Also a question to the KL Divergence Loss

So I am making a project based on this paper: https://arxiv.org/ftp/arxiv/papers/1901/1901.07761.pdf In this paper, a U-Net is used to generate optimized mechanical structures. I am trying to ...
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1answer
71 views

Is there a simple way of classifying images of size differing from the input of existing image classifiers?

Most image classifiers like Inception-v3 accept images of about size 299 x 299 x 3 as input. In this particular case, I cannot resize the image and lose resolution. Is there an easy solution of ...
2
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1answer
40 views

Why does the denoising autoencoder always returns the same output?

I am trying to implement a denoising autoencoder (DAE) to remove noise from 1024-point FFT spectra. I am using two types of spectra: (1) that contain a distinctive high amplitude spectral peak and (2) ...
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0answers
20 views

How are batch statistics computed in Recurrent Batch Normalization?

I'm implementing recurrent BN per this paper in Keras, but looking at it and those citing it, a detail remains unclear to me: how are batch statistics computed? Authors omit explicit clarification, ...
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0answers
20 views

Can't figure out what's going wrong with my dataset construction for multivariate regression

TL;DR: I can't figure out why my neural network wont give me a sensible output. I assume it's something to do with how I'm presenting the input data to it but I have no idea how to fix it. Background:...
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1answer
26 views

Is a trained model in keras is saved with the weights for max accuracy?

Does a model trained in keras (tensorflow backend) saves the weights with max accuracy and minimum losses or does it simply saves the weights from the last epoch? If it is the latter then how do I ...
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26 views

What is the correct input shape for my LSTM network?

My professor gave us a workshop where we have to do classification of a dataset of ECG signals between healthy and unhealthy types using LSTM. Each signal consists of 1,285 time steps. What my prof ...
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0answers
33 views

How to perform regression with multiple numeric (positive and negative) inputs and one numeric output?

I have a dataset with different types of numerical values (both negative and positive numerical values) for the inputs (for example, -40, -35, 1, 25, 39, etc., that is, multiple inputs) and single ...
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36 views

Is there an audio dataset with the corresponding phonemes in the audio?

I am looking for a dataset of clear audio, a corresponding transcript (optional), and most importantly a list of all the phonemes said in the audio, with the length of each phoneme and a mention of ...
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2answers
93 views

How can I find what does an specific neuron do in neural network?

How can I know what each neuron does in NN? Consider the Playground from Tensorflow, there are some hidden layers with some neurons in each. Each of them shows a line(horizontal or vertical or ...). ...
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8answers
29k views

Why is Python such a popular language in the AI field?

First of all, I'm a beginner studying AI and this is not an opinion oriented question or one to compare programming languages. I'm not implying that Python is the best language. But the fact is that ...
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2answers
43 views

TensorFlow 2.0 - Normalizing input to DNN (on structured data)

I have a structured dataset of around 100 gigs, and I am using DNN for classification in TF 2.0. Because of this huge dataset, I cannot load entire data in memory for training. So, I'll be reading ...
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1answer
70 views

Which model can I use for this problem with multiple inputs and outputs?

Which model is the most appropriate for this problem with multiple inputs and outputs? The data set is A1, A2, A3, A4, A5, A6, B1, B2, B3, B4 where ...
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1answer
68 views

Is there a place where I can read or watch to get an accurate TensorFlow code wise explanation?

I have a piece of code and I don't seem to really understand it but I'd love to get a source/link/material that would help me understand the basic functions in TensorFlow. Are there any recommended ...
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1answer
32 views

How to reduce variance of the model loss during training?

I know that stochastic gradient descent always gives different results. What are the best practices to reduce this variance today? I tried to predict simple function with two different approaches and ...
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0answers
19 views

What are examples of models for traffic sign detection that can be easily implemented?

I'm working on a college project about traffic sign detection and I have to choose a paper to implement it, but I have basic knowledge of TensorFlow and I'm afraid of choosing a paper that I can't ...
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28 views

How can we make sure, how well the reinforcement learning works?

I read a paper which is about Deep Reinforcement Learning and it tries to use this method on stock data set. It has been showed that it reach the maximum return(profit). It has been implemented in ...
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1answer
44 views

Do we have anything like accuracy and loss in RNN models?

I have a paper about trading which has been implemented with RNN on Tensorflow. We have about 2 years of data from trading. Here are some samples : Date, Open, High, Low, Last, Close, Total Trade ...
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20 views

Is this TensorFlow implementation of partial derivative of the cost with respect to the bias correct?

I have a neural network for MNIST classification which I am hard coding using TensorFlow 2.0. The neural network has an input layer consisting of 784 neurons (28 * 28), one hidden layer having "...
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1answer
38 views

Multi label Classification using Keras

I am trying to build a Multi label classification model, having dataset with different input numerical values and specific label... Eg: Value Label 35 X 35.8 X 29 Y 29.8 Y 39 AA 41 CB ...
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0answers
10 views

Can mobilenet in some cases perform better than inception_v3 and inception_resnet_v2?

I have implemented a multi-label image classification model where I can choose which model to use, I was surprised to find out that in my case mobilenet_v1_224 performed much better (95% Accuracy) ...
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1answer
56 views

Is there has any method to train Tensorflow AI/ML that I focus on detecting background of image more than common objects?

Is there has any method to train Tensorflow AI/ML that I focus on detecting background of image more than common objects? I'm newbie to ML field, but was assigned to do job that make an application ...
2
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2answers
66 views

What could be the problem when a neural network with four hidden layers with the sigmoid activation function is not learning?

I have a large set of data points describing mappings of binary vectors to real-valued outputs. I am using TensorFlow, and would like to train a model to predict these relationships. I used four ...
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0answers
28 views

How should I make output layer of my neural network so that I can get outputs ranging from [-20,-1]

I am trying to make a neural network which takes in 0 and 1 as it's input and should give me output ranging from [-20,-1].I am using three layers with sigmoid as the activation function .How should I ...
2
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1answer
56 views

What is the fastest way to train a CNN with billions of examples?

I have a CNN model that I need to train for a large scale genomics application. It is working well with a subset of my training data. I have scaled up to a subset of about 130 million examples and ...
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1answer
75 views

Can you explain to me this code written in Tensorflow? [closed]

I have found this part of code, but I do not actually know how it works. Because I am new to Tensorflow, I do not know it. Can anybody help me and explain it to me? ...
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0answers
64 views

How can I increase the speed and performance of my implementation of an AI for Reversi?

I made an AI for Reversi, aka Othello (8×8), like Alpha Zero, using this book. This book is written in Japanese. The source code of the AI I implemented can be found in this Github repository. There ...
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0answers
38 views

Training with many CPU cores doesn't improve performance

I ran my job on a computing cluster: first with 4 cores, then with 32 cores (2 nodes). But the training time is pretty much exactly the same for both of them: ~67 seconds per step. I am trying to ...
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2answers
585 views

How to implement word2vec using Tensorflow 2.0 keras API?

Since Keras API as defined as layers, how would it be used to implement the word2vec?
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1answer
33 views

Why feeding the correct output as input during training of seq2seq models?

So, I've read about seq2seq for time-series and it seemed really promising, but when I went to implement it, all the tutorial I've found use the correct output as input to the decoder phase during ...
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0answers
10 views

How to set loss weight to zero for an output dimension in keras?

Suppose I am training a model to detect facial keypoints that allow occlusions to be present. The input is an image of a face, and the model has to predict the x,y coordinate of both eyes and mouth. ...
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1answer
74 views

Indoor positioning with variable number of distance measurements in tensorflow

Currently I have a setup where I'm determining the position of a transmitter using the RSSI of 4 receivers. Its a simple feed-forward network with some hidden layers, where the input is the RSSI ...
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0answers
19 views

How to implement CNN with variable number of images in tensorflow or keras?

Suppose I have a problem where I want to classify the color of LEDs seen in the image. I can use OpenCV to pinpoint the exact location of these LEDs but I do not know their color for sure because the ...
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0answers
29 views

How could I locate certain words or numbers in a financial statement?

I would like to code a script that could locate a specific word or number in a financial statement. Financial statements roughly contain the same information, they are however not identical and ...
2
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1answer
22 views

The best way of classifying a dataset including classes with high similarity?

I have a dataset which has two very similar classes (men wrestling, women wrestling). I've used InceptionV3 as a classifier to solve the problem of classifying this dataset. Unfortunately, the ...
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0answers
18 views

How to use TPU for real-time low-latency inference?

I use Google's Cloud TPU hardware extensively using Tensorflow for training models and inference, however, when I run inference I do it in large batches. The TPU takes about 3 minutes to warm up ...