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I am doing research about federated learning and I am exploring different options for hyperparameter tuning (i am using flower as FL framework and docker to simulate a cross-silo environment with 4 ...
Marc's user avatar
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72 views

I am utilizing PyTorch for federated experiments. As my experiments involves 50 datasets with models, so, I have to run multiple ML models experiments parallelly. The code for training ML model is ...
coderoid's user avatar
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158 views

I'm new to the federated learning systems and I'm trying to train a model using 2 supernodes (clients). I managed to start the superlink (server) succesfully and successfully connect the nodes to the ...
giorgoserm's user avatar
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1 answer
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I am using securefederatedai/openfl workflow api, I want to transfer some of collaborator details, general ones like class distribution, class ratio, data mean, median. How can I securely transfer ...
anjali rai's user avatar
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1 answer
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When I try to create my iterative process for training my federated models with Tensorflow, I encounter this error module 'tensorflow_federated.python.learning.algorithms' has no attribute '...
Dimitri Vercaigne's user avatar
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I am trying to deploy a Federated Learning server using Flower (flwr) on a Kubernetes cluster with a custom Docker image (fl-server:latest). The server needs to run on a specific port and host. My ...
tobeal's user avatar
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I am trying to run the code in the following link shaoxiongji/federated-learning using the following steps: 1- Clone the Repository: git clone https://github.com/shaoxiongji/federated-learning.git 2- ...
SH_IQ's user avatar
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I am trying to simulate the Online Federated Learning framework presented in the paper "Communication-Efficient Online Federated Learning Framework for Nonlinear Regression" by Gogineni et ...
Sunil Dhawan's user avatar
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1 answer
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I am experimenting with TensorFlow Federated, simulating a training process with the FedAvg algorithm. def model_fn(): # Wrap a Keras model for use with TensorFlow Federated keras_model = ...
Martina's user avatar
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I want to create a web application using React.js, Flask, and the Flower framework with Tensorflow for image classification. I am stuck and would appreciate any tips or resources. Can anyone help me? ...
chaima bouabd's user avatar
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71 views

In the federated Learning code below, I'm using Pysyft. the goal is to distribute the FashionMNIST dataset to different clients federated_train_loader = syft.FederatedDataLoader( datasets....
ghazalia's user avatar
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I'm developing a sort of federated learning environment and it contains a Server class and 10 instances of the Client classes. I train the various clients one after the other and I'd like to specify ...
Alessandro Masci's user avatar
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import pandas as pd import sklearn from sklearn.datasets import load_iris Loading data from a CSV file data = pd.read_csv('D:/Projects/FLGRU_Model/FLDataset/01-12/DrDoS_LDAP.csv') df = pd.read_csv(...
user24748686's user avatar
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I am implementing federated averaging on the IoT-23 dataset(lighter version) Omitting the preprocessing I am saving the data into a test set and 9 train sets as below: X_train, X_test, Y_train, Y_test ...
AdityaDN's user avatar
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228 views

I want to send extra parameters with model updates to server and then utilize those extra parameters in server for other purposes. I am using Flower and Tensorflow for this project. Before sending ...
Saim's user avatar
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1 answer
74 views

This is a loss function of a personalized federated learning framework. When lambda equals 0, all clients train locally. Otherwise they adjust their parameters based on the similarity to the global ...
raegan yang's user avatar
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1 vote
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53 views

I'm trying to implement federated learning to forecast solar photovoltaic generation using the LADPU dataset. After preprocessing the dataset, I partitioned it into segments to simulate a federated ...
kali's user avatar
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1 vote
1 answer
382 views

I am using flwr framework to send a random array from client to server and then server will merge the array and sends back to each of the clients. import numpy as np import flwr as fl from flwr.server....
coderoid's user avatar
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567 views

i am facing "AttributeError: module 'syft' has no attribute 'VirtualWorker'" for "# Create VirtualWorkers hook = syft.VirtualWorker(hook, id="hook") " Create ...
Avinash Chhetri's user avatar
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1 answer
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I am creating num_of_clients threads using the following code: sockets_thread = [] no_of_client = 1 all_data = b"" while True: try: for i in range(no_of_client): ...
coderoid's user avatar
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101 views

I have a federated server (flower framework) running in a docker container in the raspberry pi device in the same network as the client (My laptop). The client is not able to establish a connection ...
Karthik R's user avatar
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62 views

I am trying to implement the following algorithm . In step 18, the gradient of the loss with respect to alpha is being computed and when i try to access this .grad atribute for alpha, I get None, ...
aks's user avatar
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1 answer
125 views

In federated learning, I want to get weights of each local model every round, then I will cluster local clients based on their weights, but I can just use training_process.get_model_weights(...
baodvo's user avatar
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1 answer
257 views

I am trying to use shfl python library. When I import shfl, I get the error ModuleNotFoundError: No module named 'shfl', and apparently I cannot install it. I have used three following commands and ...
azLe's user avatar
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1 answer
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The problem of the given code is: line 25, in <module> privacy_engine = PrivacyEngine(model, batch_size=64, sample_size=60000, alphas=range(2,32), noise_multiplier=1.3, max_grad_norm=1.0) ...
Abdus Sahid's user avatar
  • 1
-1 votes
1 answer
103 views

What are the libraries we can use for federated learning process? what are the data encryption techniques used to protect datasets? I studied some articles and blogs but in health sector it's ...
irfanRala's user avatar
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1 answer
236 views

I'm working on federating a UNET semantic segmentation workflow using flower and Pytorch. As of right now I can load the data and run a centralized training but once I try to federate it I see that ...
Greasy Chicken's user avatar
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1 vote
1 answer
842 views

I am trying to implement Federated Learning using Flower framework in python. I get the following error when I start the process.Snapshot of the error Here is what I tried, NUM_CLIENTS = 10 #function ...
Yogitha Muthappa's user avatar
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1 answer
225 views

` import torch import torch.nn as nn import torch.optim as optim from torch.utils.data import DataLoader, Dataset import numpy as np from sklearn.datasets import load_breast_cancer from sklearn....
Mustakim Pallab's user avatar
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1 answer
164 views

I've been playing for some time with FL + DP for my thesis. I am using TFF in case someone is wondering. I load my data as: train_data = tff.simulation.datasets.ClientData.from_clients_and_fn( ...
Joaquín Delgado Fernández's user avatar
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1 vote
1 answer
2k views

Last week iam working with syft==0.2.9 and it was working great! but this week when i tried to install syft==0.2.9 i have this error "ERROR: Could not find a version that satisfies the ...
Nwadher's user avatar
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1 vote
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146 views

I am trying to work on a federated learning project and I am just at the beginning. I tried to import a class called "BaseDataset" from the pysyft library as shown in the following. import ...
Tomas 's user avatar
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1 vote
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248 views

I got a series of error messages, the last one being the one mentioned first in the title, while I was trying to run this Github repo on my local machine. I need that project as a boilerplate for my ...
1201 Mansoor's user avatar
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1 vote
0 answers
269 views

I have a PyTorch model that I am trying to integrate federated learning for. In order to do this, I need to send the model weights back and forth between a server and a client. When I get the size of ...
ditty's user avatar
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0 votes
2 answers
249 views

I have deep learning models (tensorflow in hdf5 format), which I want to upload to a PostgreSQL database. A single model may be up to 500 MBs, and the models need to be updated and uploaded/downloaded ...
Mr. Gulliver's user avatar
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0 votes
1 answer
169 views

I was wondering if in a Federated Learning approach I need to split the local dataset in a number of batches equal to the number of communication rounds. Otherwise I need to update locally on the ...
Novak's user avatar
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0 answers
55 views

I have two PCs that want to share tensorflow models "hdf5 format" in a federated learning manner via a PostgresSQL database. The models will be trained locally on both machines, and then ...
Mr. Gulliver's user avatar
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0 votes
0 answers
62 views

I got "module '0b1a516c7ccf3157373118bcf0f434168745c8a4' has no attribute 'entropy_decode_index' error after a clean intall of tensorflow federated (TFF) on Ubuntu 22.04. System: AMD 6900HS, ...
Egemen Isguder's user avatar
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0 votes
1 answer
807 views

I use Flower API for federated learning applications. Is there any way to run the server and clients on different machines for a real-world benchmark?
Mastour Ikhlass's user avatar
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0 answers
157 views

I want to try a simple federated learning example in python. For it, I need to import tensorflow_federated package. import tensorflow_federated as tff Here is the stack trace TypeError ...
HoOman's user avatar
  • 485
3 votes
1 answer
6k views

Trying to implement the reaserch paper: https://ieeexplore.ieee.org/document/9479786/ Training a Monotone Network with architechture: class Model(nn.Module): def __init__(self, q, s): self....
Geeky Coder's user avatar
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0 votes
1 answer
236 views

I would like to add different weights to clients in Federated learning, so in the aggregation stage, each client has a different impact on the global model. For example: Client_1 has 2X impact ...
shadow's user avatar
  • 53
0 votes
0 answers
166 views

In federated/ distributed learning, the server will send initially a global model to clients, and each client will train the model locally and then select the top k values, and send only these values ...
user18969005's user avatar
  • 87
1 vote
1 answer
295 views

I am planning to use Opacus to implement differential privacy in my federated learning model but I have a very basic doubt that I would love to have cleared before that. So as far as my understanding ...
Anirban Nath's user avatar
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3 votes
2 answers
782 views

I have just started using pysyft to implement federated-learning. While following one of the tutorials, I got stuck on an error: Code which I have used: import torch import torch.nn as nn import ...
onapte's user avatar
  • 267
0 votes
1 answer
245 views

I have two kinds of covid 19 datasets as two clients (the first one ST Scan images and the second is XRays images) and I use federated learning approch. The question is can I use those dataset as two ...
Madeleine Alabdah's user avatar
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1 vote
1 answer
215 views

I want to build a TFF model for speech recognition systems. For this, I use the CNN-GRU model architecture with a CTC loss function. but I got error when I wanted to build_federated_averaging_process ...
hamid ebrahimi's user avatar
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1 vote
0 answers
305 views

I am very interested in federated systems and i was trying one of the pre trained multilingual models such as this notebook Multi_Lingual_Training_and_models. I was looking for any tutorials using TFF ...
Kareem Shehata's user avatar
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1 answer
344 views

I am using the Flower code example to try POC of Federated Learning but I keep getting the error below when I run the client.py file: INFO flower 2022-07-04 15:27:37,301 | connection.py:102 | Opened ...
Frederico23's user avatar
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2 votes
0 answers
229 views

In federated averaging, does the client optimizer have to be 'SGD' only? In this paper ADAPTIVE FEDERATED OPTIMIZATION it states "One such method is FEDAVG (McMahan et al., 2017), in which ...
Dushi Fdz's user avatar
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