Questions tagged [implementation]

For questions about implementation of software/algorithms related to Artificial Intelligence.

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33 views

What does it mean by "lazy mean" here?

Consider the following paragraph, taken from 3.4: Named Tensors of the textbook named Deep Learning with PyTorch by Eli Stevens et al., regarding the calculation of the mean for RGB channels of an RGB ...
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0answers
21 views

Which kind of RNNs are mostly used in applications: hidden-hidden or actual output-hidden?

I came across two types of RNN while reading the chapter titled Sequence Modeling: Recurrent and Recursive Nets of the textbook named Deep Learning by Ian Goodfellow et al. First type: Recurrent ...
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1answer
47 views

How to code an $\epsilon$-soft policy for on-policy Monte Carlo control?

I was trying to code the on-policy Monte Carlo control method. The initial policy chosen needs to be an $\epsilon$-soft policy. Can someone tell me how to code an $\epsilon$-soft policy? I know how to ...
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1answer
36 views

How do graph neural networks adapt to different number of nodes and connections of different graphs?

I have recently been studying GNN, and the fundamental idea seems to be the aggregation and transfer of information from a node's neighborhood to update the node's internal state. However, there are ...
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21 views

Are there standardized forms of the Turing Test?

Most computer science instructors will tell you that the Turing Test is more a theoretical or conceptual thought experiment than an actual exam that someone (or something!) can formally sit and ...
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39 views

Different equations for Yolov3 in courses/ articles and Darknet GitHub code?

I am confused by the equations for bounding boxes I find online. Some articles say that box_width = anchor_width * exp(residual_value_of_box_width)) and the ...
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0answers
27 views

Why isn't my perceptron having the expected costs?

I want to implement a single perceptron for linear regression using the following formulas: The input data for the first case is one column (x(392, 1); y(392, 1)) ...
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2answers
38 views

In mini-batch gradient descent, do we pass each input in the batch individually or all inputs at the same time through the layer?

In the stochastic gradient descent algorithm, the weight update happens for every training sample. In the mini-batch gradient descent algorithm, the weight update happens for every batch of training ...
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29 views

Is this a good implementation of this LSTM architecture?

I had been looking at some OCR problems and came across this presentation. I implemented it. In the presentation, there is the LSTM-Stack (diagram and algorithm, slide 32): Here is a visualization of ...
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1answer
28 views

Why using negative integers (as dimensions?) in tensor shapes rather than natural numbers?

Consider the following paragraph from A.1 MULTI-MNIST AND CLEVR of A IMPLEMENTATION DETAILS from the research paper titled ...
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1answer
31 views

Does increase in the number of epochs can lead to complete breakdown?

Recently, I ran a code on my system that involves deep neural networks. The number of epochs provided by the designers are 301. I tried to increase the number of epochs to 501. To my shock, the model ...
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1answer
90 views

Which of the following two implementations of a Least Squares classifier in Python is correct?

I am trying to solve a classification problem by implementing the Least Squares algorithm in Python. To solve this problem, I am implementing the linear algebra formula to train the classifier, which ...
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1answer
33 views

What is the high-level algorithm followed by contemporary packages for the calculation of gradient?

Most of the neural network models in contemporary deep learning packages are trained based on gradients. Let $f: \mathbb{R}^m \rightarrow \mathbb{R}^n$ be a function for which we want to find a ...
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2answers
24 views

Why not undefined expression is different from numerical underflow?

Consider an architecture or programming language that uses $n$ bits for storing a floating point number in a particular format. Then each and every floating point number it can store should be in a ...
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29 views

DDPG or PPO don't work well with my custom non gym environment

I have a project to control a robot with right and left wheel speeds, and my step time is not constant. Because my outputs are continuous (right wheel speed, left wheel speed, and time step), I try to ...
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1answer
48 views

How is this statement from a TensorFlow implementation of a certain KL-divergence formula related to the corresponding formula?

I am trying to understand a certain KL-divergence formula (which can be found on page 6 of the paper Evidential Deep Learning to Quantify Classification Uncertainty) and found a TensorFlow ...
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1answer
36 views

What are the (key) purposes of unsqueezing operation on tensors?

The unsqeeze operation is used in several deep learning algorithms. However, I only found this operation in the code/implementation of the algorithms presented in the papers, which do not mention it. ...
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1answer
42 views

How to calculate the gradient penalty proposed in "Improved Training of Wasserstein GANs"?

The research paper titled Improved Training of Wasserstein GANs proposed a gradient penalty in order to avoid undesired behavior due to weight clipping of the discriminator. We now propose an ...
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1answer
61 views

Why people always say the Transformer is parallelizable while the self-attention layer still depends on outputs of all time steps to calculate?

When compared to an RNN seq-to-seq model, people always say the Transformer is parallelizable. In the original Attention Is All You Need paper, it also said that Recurrent models typically factor ...
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0answers
108 views

Is there any gain by lazy initialization of weights, biases and number of input channels for a convolution operation?

The basic layers for performing convolution operations 1,2,3 in PyTorch are ...
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1answer
135 views

What exactly is an XPU?

I know about CPU, GPU and TPU. But, it is the first time for me to read about XPU from PyTorch documentation about MODULE. ...
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1answer
61 views

What are the applications in which the precision of the neural network's weights is unimportant?

While reading about Module in PyTorch, I came across a new data type called half datatype. half() method when calls on a Module ...
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0answers
16 views

Is it possible to use (infinite cardinal) random variables during implementation?

Random variables can be broadly classified into three types: random variables whose range is finite, random variable whose range is countably infinite and random variables whose range is uncountable. ...
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0answers
39 views

How to implement a (3 + 2)-dimensional convolutional layer where the 2d space is "internal"?

I am trying to train a CNN to learn 5D (kind of) data. The data is structured as follows. It has three spatial dimensions [x, y, z], but it also has two "...
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1answer
50 views

In practice, are perceptrons typically implemented as objects?

I'm fairly new to ANNs. I know the general structure, the math, and the algorithms behind them. I figured the logical next step on my journey to fully understanding them would to be implement one ...
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1answer
73 views

Why is the logarithm of the standard deviation used in this implementation of proximal policy optimization?

I am currently writing my bachelor thesis, which is an implementation of proximal policy optimization. Sometimes, I hit a wall because of the gaps in my mathematical knowledge. However, implementing ...
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0answers
48 views

Off-policy Bellman Operators: Writing Operator and Weight Update Function for a 2-State System

I am studying for RL on my own and was trying to solve this question I came across. Write an operator function $T(w, \pi, \mu, l, g)$ that takes weights $w$, a target policy $\pi$, a behaviour policy ...
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1answer
81 views

Why does my neural network to solve the XOR problem always output 0.5?

I'm trying to create a neural network to simulate an XOR gate. Here's my dataset: ...
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3answers
79 views

How can I model any structure for a neural network?

Hello I am currently doing research on the effect of altering a neural network's structure. Particularly I am investigating what affect would putting a random DAG (directed acyclic graph) in the ...
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2answers
161 views

How is the AI in 3d games implemented?

A few days ago, I started looking a bit more into AI and learning about the way it works, and it is very interesting, but I can't find a clear answer on how the artificial intelligence is implemented ...
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1answer
123 views

What to do with a GAN that trained well but got worse over time?

I am training a WGAN-GP network based on the following paper, though I am using a different dataset. Now, for the first ~ 60-70 epochs, my network trained really well, which I could see in the loss ...
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1answer
110 views

Is there a convention on the order of multiplication of the weights with the inputs in neural nets?

Is there a convention on how the input data and the weights are multiplied? The input data can be anything, including the result from the previous layers. There are two options: Option 1: $$\begin{...
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1answer
76 views

How should I implement the state transition when it is a Gaussian distribution?

I am reading this paper Anxiety, Avoidance and Sequential Evaluation and is confused about the implementation of a specific lab study. Namely, the authors model what is called the Balloon task using a ...
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0answers
100 views

Can someone explain to me this implementation of Tile Coding using Hash Tables?

The code below is adapted from this implementation. ...
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1answer
76 views

How do you pass the image from one convolutional layer to another in a CNN?

I am currently trying to write a CNN from scratch, but I don't understand how to feed the information from a max-pooling layer to the next convolutional layer. Specifically, I don't know what to do ...
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300 views

Wasserstein GAN: Implemention of Critic Loss Correct?

The WGAN paper concretely proposes Algorithm 1 (cf. page 8). Now, they also state what their loss for the critic and the generator is. When implementing the critic loss (so lines 5 and 6 of Algorithm ...
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0answers
17 views

Would it make sense to share the layers (except the last one) of the neural networks in Double DQN?

Context: Double Q-learning was introduced to prevent the maximization bias from q-learning. Instead of learning a single Q-network, we can learn two (or in general $K > 1$) and our Q-estimate would ...
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1answer
268 views

How are continuous actions sampled (or generated) from the policy network in PPO?

I am trying to understand and reproduce the Proximal Policy Optimization (PPO) algorithm in detail. One thing that I find missing in the paper introducing the algorithm is how exactly actions $a_t$ ...
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1answer
54 views

Is average pooling equivalent to a strided convolution with a specific constant kernel?

It seems to me that average pooling can be replaced by a strided convolution with a constant kernel. For instance, a 3x3 pooling would be equivalent to a strided convolution (of stride $3$) with a $3 \...
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0answers
52 views

How am I supposed to code equation 4.57 from the book "Machine Learning: An Algorithmic Perspective"?

Consider the equation 4.57 (p. 108) from section 4.6 of the Book Machine Learning: An Algorithmic Perspective, where the derivative of the softmax function is explained $$\delta_o(\kappa) = (y_\kappa -...
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0answers
32 views

What is the difference between step_model and train_model in the OpenAI implementation of the A2C algorithm?

I'm struggling a little with understanding the OpenAI implementation of A2C in the baselines (version 2.9.0) package. From my understanding, one ...
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2answers
610 views

What are some alternatives to "Papers with Code"?

There are lots of research papers available that are worth reading. We can read papers easily, but the associated code (not necessarily the official one developed by the authors of the paper) is often ...
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1answer
183 views

What are the variables that need to be saved and loaded, so that a DQN model starts where it left off?

TensorFlow allows users to save the weights and the model architecture, however, that will be insufficient unless the values of certain other variables are also stored. For instance, in DQN, if $\...
3
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1answer
59 views

How can I create an embedding layer to convert words to a vector space from scratch?

For an upcoming project, I am trying to build a neural network for classifying text from scratch, without the use of libraries. This requires an embedding layer, or a way to convert words to some ...
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0answers
24 views

What is the score used to visualize attention in this paper?

I'm reading this paper Global-Locally Self-Attentive Dialogue State Tracker and follow through the implementation published in GLAD. I was wondering if someone can clarify what variable or score is ...
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1answer
341 views

What is a RAM state in the gym's breakout-ram environment?

I have encountered the gym environment and decided to create AI that plays breakout. Here is the link: https://gym.openai.com/envs/Breakout-ram-v0/. The documentation says that the state is ...
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1answer
86 views

Is there a general file type associated with AI projects?

This is a general question. Is there a general file type associated with AI projects? Photoshop = .psd Excel = csv Artificial Intelligence = ?
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1answer
397 views

What made your DDPG implementation on your environment work?

I am working on scheduling problem that has inherent randomness. The dimensions of action and state spaces are 1 and 5 respectively. I am using DDPG, but it seems extremely unstable, and so far it ...
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1answer
55 views

Is there a good and easy paper to code policy gradient algorithms (REINFORCE) from scratch?

I am interested in learning about policy gradient algorithms and REINFORCE. Can you suggest a good and easy paper that I can use to code them from scratch?
3
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1answer
100 views

How is the convolution layer is usually implemented in practice?

Following an earlier question, I'm interested in understanding the basics of Conv2d and especially how the kernel is applied, summed, and the propagated. I ...