Questions tagged [tensorflow]
For questions related to Google's open-source library for machine learning and machine intelligence. However, note that programming questions are off-topic here.
371 questions
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Is this neural network architecture appropriate for CIFAR-10? [closed]
I have a CNN architecture for CIFAR-10 dataset which is as follows:
Convolutions: 64, 64, pool
Fully Connected Layers: 256, 256, 10
Batch size: 60
Optimizer: ...
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I need to select the image from a predefined dataset that are the closest to the input, is this possible or do I even need to use ML/AI?
So as the title states, I have a set of images and I want to process input images and need to select the image that "looks" the most like the input image.
I know I've seen something similar where the ...
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How do I make my LSTM model more sensitive to changes in the sequence?
I have a many to one LSTM model for multiclass classification. For reference, this is the architecture of the model
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Is there a reason to use TensorFlow over PyTorch for research purposes?
I've been using PyTorch to do research for a while and it seems to be quite easy to implement new things with. Also, it is easy to learn and I didn't have any problem with following other researchers ...
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Error when using tensorflow HMC to marginalise GPR hyperparameters
I originally posted on SO (original post) but was suggested to post here.
I would like to use tensorflow (version 2) to use gaussian process regression to fit some data and I found the google colab ...
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How to handle set-like size agnostic input format
Let's set up some hypothetical simplified scenario: Each instance $i$ of my imaginary dataset $D=\{i_{1}, \ldots, i_{MAX}\}$ has different number $k_{i}$ of $n$-dimensional vectors as input into my ...
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Is there a way to use RNN (in tensorflow) to do something like a batch Kalman with the weight dynamics specified in the loss?
Or would you simply do this as a time series of models.
Basically I think you can think of time series of weights as the hidden states and the dynamics driving the weight time series as the RNN ...
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Why do CNN's sometimes make highly confident mistakes, and how can one combat this problem?
I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I'm feeding in a bunch of handwritten digits, and non-digits from a document.
I want the CNN to report errors, so I ...
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TensorFlow fit() and GradientTape - number of epochs are different
if I define the architecture of a neural network using only dense fully connected layers and train them such that there are two models which are trained using model.fit() and GradientTape. Both the ...
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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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What are the differences between TensorFlow and PyTorch? [closed]
What are the differences between TensorFlow and PyTorch, both in terms of performance and functionality?
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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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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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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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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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Why don't people always use TensorFlow Lite, if it doesn't decrease the accuracy of the models?
I have been exploring edge computation for AI, and I came across multiple libraries or frameworks, which can help to convert the model into a lite format, which is suitable for edge devices.
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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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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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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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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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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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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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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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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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Multi label Classification using Keras [closed]
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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83
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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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Is there has any method to train Tensorflow AI/ML that I focus on detecting background of image more than common objects? [closed]
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 ...
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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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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 ...
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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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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 ...
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TensorFlow 2.0 - Normalizing input to DNN (on structured data) [closed]
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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The best way of classifying a dataset including classes with high similarity? [closed]
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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480
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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 ...
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How can we print weights per iteration in a simple feed forward MLP for an specific class?
im working on a project in which I have to make a multi-layer perceptron with two hidden layers with 3 nodes in each. The target value in my data contains 8 unique values/classes. One of the tasks ...
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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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How to implement loss function of H-GAN model
I was trying to implement the loss function of H-GAN. Here is my code . But it seem somethings wrong, maybe is recognition loss on z (EQ 9). I used the EQ 5 on MISO to calculate it. Here is my code:
...
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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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TF Keras: How to turn this probability-based classifier into single-output-neuron label-based classifier
Here's a simple image classifier implemented in TensorFlow Keras (right click to open in new tab): https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/...
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Trying to separate spiral data with neural network, learning tensorflow
I am learning how to use tensorflow without keras, just to make sure I understand tensorflow directly.
I created a spiral-looking datasets with 100 points of each class (200 total), and I created a ...
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428
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Why is embedding important in NLP, and how does autoencoder work?
People say embedding is necessary in NLP because if using just the word indices, the efficiency is not high as similar words are supposed to be related to each other. However, I still don't truly get ...
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How can I reduce the GPU memory usage with large images?
I am trying to train a CNN-LSTM model. The size of my images is 640x640. I have a GTX 1080 ti 11GB. I am using Keras with the TensorFlow backend.
Here is the model.
...
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What is the relationship between the size of the hidden layer and the size of the cell state layer in an LSTM?
I was following some examples to get familiar with TensorFlow's LSTM API, but noticed that all LSTM initialization functions require only the num_units parameter, ...
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How to change this RNN text classification code to become text generation code?
I can do text classification with RNN, in which the last output of RNN (rnn_outputs[-1]) is used to matmul with output layer weight and plus bias. That is getting a word (class name) after the last T ...
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Neural network does not give out the required out put?
Made a neural network using tensor flows that was supposed matches an Ip to one of the 7 type of vulnerabilities and gives out what type of vulnerability that IP has.
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LSTM network doesn't converge, what should be changed? [closed]
I'm testing out TensorFlow LSTM layer text generation task, not classification task; but something is wrong with my code, it doesn't converge. What changes should be done?
Source code:
...
- 1,318
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How to map X to Y for TensorFlow RNN training data
Usually for DNN, I have the training data of matching X (2D) to Y (2D), for example, XOR data:
X = [[0,0],[0,1],[1,0],[1,1]];
Y = [[0], [1], [1], [0] ];
...
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Why isn't my Neural Network based calculator working?
I am playing around with neural networks in Tensorflow and I figured an interesting test would be whether I can write a calculator using a Tensorflow Neural Network.
I started with simple addition ...
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Network doesn't converge with ReLU or Leaky ReLU, but works well with sigmoid/tanh
I have these training data to separate, the classes are rather randomly scattered:
My first attempt was using tf.nn.relu activation function, but output was stuck ...
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Generate credit cards dataset for locating number region
Currently I'm working on a project for scanning credit card and text extraction from cards. So first of all I decided to preprocess my images with some filters like thresholding, dilation and some ...
