id stringlengths 7 11 | source stringclasses 1
value | category stringclasses 11
values | title stringlengths 15 214 | text stringlengths 70 30.5k | url stringlengths 57 160 | tags stringlengths 3 113 | created_at int64 1.22B 1.79B |
|---|---|---|---|---|---|---|---|
se_79709893 | stackoverflow | MACHINE_LEARNING | DQN fails to learn good policy for Atari Pong | DQN fails to learn good policy for Atari Pong
I'm trying to implement the findings from this DeepMind DQN paper (2015) from scratch in PyTorch using the Atari Pong environment.
I've tested my Deep Q-Network on a simple test environment, where episodes last only 5 time steps and the maximum achievable reward is 4.1. My... | https://stackoverflow.com/questions/79709893/dqn-fails-to-learn-good-policy-for-atari-pong | python, deep-learning, pytorch, reinforcement-learning | 1,753,159,942 |
se_38888398 | stackoverflow | MACHINE_LEARNING | semantic segmentation and object detection | semantic segmentation and object detection
This thread discusses the comparison of different computer vision concepts. Fully Convolutional Networks for Semantic Segmentation
is a very popular deep learning approach for semantic segmentation. What are the popular or state-of-the-art deep learning approaches for object... | https://stackoverflow.com/questions/38888398/semantic-segmentation-and-object-detection | machine-learning, deep-learning, neural-network, computer-vision, image-segmentation | 1,470,895,482 |
se_79641780 | stackoverflow | MACHINE_LEARNING | YOLOv8 Custom Model Fails to Detect Card Elements — What Am I Doing Wrong? | YOLOv8 Custom Model Fails to Detect Card Elements — What Am I Doing Wrong?
I’m working on a card verification system where the goal is to detect fixed visual elements on a card (e.g., logo, photo, chip, signature) using computer vision.
Given a photo of a card, I want to detect whether certain key elements are present... | https://stackoverflow.com/questions/79641780/yolov8-custom-model-fails-to-detect-card-elements-what-am-i-doing-wrong | python, machine-learning, deep-learning, yolov8, ultralytics | 1,748,420,130 |
se_59853676 | stackoverflow | MACHINE_LEARNING | What is sub-pixel convolution? | What is sub-pixel convolution?
I am working on a super-resolution project. And for now, I am using Transposed Convolution for upsampling the image. But I have heard a lot that sub-pixel convolutions do it better. So what is subpixel convolution and the math behind it? And Why it is better than transposed convolution? ... | https://stackoverflow.com/questions/59853676/what-is-sub-pixel-convolution | image-processing, deep-learning, neural-network, conv-neural-network, convolution | 1,579,673,864 |
se_76192675 | stackoverflow | MACHINE_LEARNING | ImportError: cannot import name 'YOLO' from 'ultralytics' (unknown location) | ImportError: cannot import name 'YOLO' from 'ultralytics' (unknown location)
I am trying to build a YOLOv8 model, and I have built it using cloning github repo of YOLOv8.
https://github.com/ultralytics/ultralytics
For training the yolov8 docs say that I need to start as follows
from ultralytics import ... | https://stackoverflow.com/questions/76192675/importerror-cannot-import-name-yolo-from-ultralytics-unknown-location | python, deep-learning, importerror, yolo, yolov8 | 1,683,444,647 |
se_78002007 | stackoverflow | MACHINE_LEARNING | Fréchet inception distance (FID) Score for same vectors is not zero | Fréchet inception distance (FID) Score for same vectors is not zero
I was trying to use the implementation of FID score from this resource: https://machinelearningmastery.com/how-to-implement-the-frechet-inception-distance-fid-from-scratch/ but when I run the FID score for the same vectors (act1) I expected the F... | https://stackoverflow.com/questions/78002007/fr%c3%a9chet-inception-distance-fid-score-for-same-vectors-is-not-zero | python, numpy, deep-learning, computer-vision, generative-adversarial-network | 1,708,010,973 |
se_72291650 | stackoverflow | MACHINE_LEARNING | Contextual Tokenizer that depends on the context in Transformer NLP | Contextual Tokenizer that depends on the context in Transformer NLP
I would like to create a tokenizer that tokenizes words in a sentence depending on its surroundings. So one word could have different tokens depending on its neighbor words. For example, if I have these two sentences: "Soccer is fun" and "She plays so... | https://stackoverflow.com/questions/72291650/contextual-tokenizer-that-depends-on-the-context-in-transformer-nlp | deep-learning, nlp, token, huggingface-transformers | 1,652,886,294 |
se_79653043 | stackoverflow | MACHINE_LEARNING | TPU for Pix-to-Pix possible? | TPU for Pix-to-Pix possible?
I have model Pix-to-Pix. Not segmentation. Transfer from texture to texture. Loss = 'mse'.
And it works properly with GPU. But if i try to use TPU i get loss = 'nan'
I simplified the model by cutting off pieces step by step with same result: loss = 'nan' at 42th epoch. Even with precision ... | https://stackoverflow.com/questions/79653043/tpu-for-pix-to-pix-possible | deep-learning, neural-network, tpu, unet-neural-network, float32 | 1,749,049,620 |
se_74191935 | stackoverflow | MACHINE_LEARNING | gym env.render() on Nth step | gym env.render() on Nth step
I am using gym==0.26.0 and I am trying to make my environment render only on each Nth step. So that my nn is learning fast but that I can also see some of the progress as the image and not just rewards in my terminal. With the newer versions of gym, it seems like I need to specify the rend... | https://stackoverflow.com/questions/74191935/gym-env-render-on-nth-step | python, machine-learning, deep-learning, reinforcement-learning, openai-gym | 1,666,690,342 |
se_78994162 | stackoverflow | MACHINE_LEARNING | How can I just calculate a part of grad using make_functional in PyTorch? | How can I just calculate a part of grad using make_functional in PyTorch?
func_model, func_params = make_functional(self.model)
def fm(x, func_params):
fx = func_model(func_params, x)
return fx.squeeze(0).squeeze(0)
def floss(func_params,input):
fx = fm(input... | https://stackoverflow.com/questions/78994162/how-can-i-just-calculate-a-part-of-grad-using-make-functional-in-pytorch | python, network-programming, deep-learning, pytorch, gradient-descent | 1,726,577,824 |
se_79695214 | stackoverflow | MACHINE_LEARNING | i want to custmize data.yaml file for train yolo11x.pt model by ultralytics? | i want to custmize data.yaml file for train yolo11x.pt model by ultralytics?
class_id x_center y_center width height behavior_id
eg.txt file data 6 0.260313 0.739167 0.131875 0.038333 1
6 0.580313 0.821250 0.290625 0.245834 0
6 0.821562 0.775416 0.230625 0.179167 0
6 0.914062 0.800416 0.170625 0.215833 1
data.yaml fi... | https://stackoverflow.com/questions/79695214/i-want-to-custmize-data-yaml-file-for-train-yolo11x-pt-model-by-ultralytics | machine-learning, deep-learning, yolov8, ultralytics | 1,752,044,923 |
se_44255411 | stackoverflow | MACHINE_LEARNING | Which is best for object localization among R-CNN, fast R-CNN, faster R-CNN and YOLO | Which is best for object localization among R-CNN, fast R-CNN, faster R-CNN and YOLO
what is the difference between R-CNN, fast R-CNN, faster R-CNN and YOLO in terms of the following:
(1) Precision on same image set
(2) Given SAME IMAGE SIZE, the run time
(3) Support for android porting
Considering these three criter... | https://stackoverflow.com/questions/44255411/which-is-best-for-object-localization-among-r-cnn-fast-r-cnn-faster-r-cnn-and | deep-learning, deeplearning4j | 1,496,127,083 |
se_79698151 | stackoverflow | MACHINE_LEARNING | GradientTape won't calculate gradients after restoring a model from ModelCheckpoint | GradientTape won't calculate gradients after restoring a model from ModelCheckpoint
I'm training a CNN on Tensorflow for binary classification and executing my code in Google Colab.
CNN_model = tf.keras.Sequential([
tf.keras.layers.Input(shape=(IMAGE_SIZE, IMAGE_SIZE, 3)),
tf.keras.layers.Conv2D(filters=32... | https://stackoverflow.com/questions/79698151/gradienttape-wont-calculate-gradients-after-restoring-a-model-from-modelcheckpo | python, tensorflow, deep-learning, conv-neural-network, google-colaboratory | 1,752,228,041 |
se_79496906 | stackoverflow | MACHINE_LEARNING | Why does setting torch.backends.cudnn.deterministic = True make my TCN model extremely slow in PyTorch? | Why does setting torch.backends.cudnn.deterministic = True make my TCN model extremely slow in PyTorch?
I encountered a very interesting issue when training a deep learning model using Python and PyTorch. I designed a simple TCN as follows:
import torch
import torch.nn as nn
class TCN(nn.Module):
def __init__... | https://stackoverflow.com/questions/79496906/why-does-setting-torch-backends-cudnn-deterministic-true-make-my-tcn-model-ext | python, deep-learning, conv-neural-network, torch | 1,741,575,045 |
se_79695755 | stackoverflow | MACHINE_LEARNING | How to get the KL divergence between two datasets (say ImageNet1k and FGVC-Aircraft) | How to get the KL divergence between two datasets (say ImageNet1k and FGVC-Aircraft)
I want to find out the KL divergence between 2 datasets, so for that I am extracting the features from ResNet50 for both of them, but if I calculate the same for ImageNet1k (say 20% of val set) and FGVC-Aircraft test set, I get a very... | https://stackoverflow.com/questions/79695755/how-to-get-the-kl-divergence-between-two-datasets-say-imagenet1k-and-fgvc-aircr | python, deep-learning, pytorch | 1,752,069,680 |
se_53580088 | stackoverflow | MACHINE_LEARNING | Calculate the output size in convolution layer | Calculate the output size in convolution layer
How do I calculate the output size in a convolution layer?
For example, I have a 2D convolution layer that takes a 3x128x128 input and has 40 filters of size 5x5. | https://stackoverflow.com/questions/53580088/calculate-the-output-size-in-convolution-layer | machine-learning, deep-learning, pytorch, conv-neural-network | 1,543,752,568 |
se_79680627 | stackoverflow | MACHINE_LEARNING | ValueError: The layer sequential_4 has never been called and thus has no defined input | ValueError: The layer sequential_4 has never been called and thus has no defined input
I have built a CNN model with the following layers:
def build_trainable_cnn(input_shape, num_classes):
"""
Create a CNN model for feature extraction
Parameters:
input_shape: shape of input features (e.g., (500, ... | https://stackoverflow.com/questions/79680627/valueerror-the-layer-sequential-4-has-never-been-called-and-thus-has-no-defined | python, tensorflow, keras, deep-learning, conv-neural-network | 1,750,945,934 |
se_79695488 | stackoverflow | MACHINE_LEARNING | Trained Huggingface EncoderDecoderModel.generate() produces only bos-tokens | Trained Huggingface EncoderDecoderModel.generate() produces only bos-tokens
I am working on a Huggingface transformers EncoderDecoderModel consisting of a frozen BERT-Encoder (answerdotai-ModernBERT-base) and a trainable GPT2-Decoder. Due to the different architectures for Encoder and Decoder, both come with different... | https://stackoverflow.com/questions/79695488/trained-huggingface-encoderdecodermodel-generate-produces-only-bos-tokens | python, deep-learning, pytorch, huggingface-transformers, large-language-model | 1,752,058,070 |
se_77297891 | stackoverflow | MACHINE_LEARNING | Speed up the real time face-detection using CV2 and DeepFace | Speed up the real time face-detection using CV2 and DeepFace
I am trying to build a real-time face detector that should meet these requirements:
Fast
As much accurate as possible even in darker conditions of the enviroment
I can easly add a face recognition model after its detection
These requirements led me to buil... | https://stackoverflow.com/questions/77297891/speed-up-the-real-time-face-detection-using-cv2-and-deepface | deep-learning, computer-vision, face-recognition, face-detection, deepface | 1,697,393,051 |
se_59134865 | stackoverflow | MACHINE_LEARNING | Tensorflow : How to optimize trained model size? | Tensorflow : How to optimize trained model size?
I am building a simple TensorFlow model where I am fine-tuning the Elmo model using Tf-Hub module.
I am getting a good result but the problem is when I am saving the model, It's very large where the same time I built the same model in Keras and it's in Kb.
My input da... | https://stackoverflow.com/questions/59134865/tensorflow-how-to-optimize-trained-model-size | python, tensorflow, machine-learning, keras, deep-learning | 1,575,274,424 |
se_55917959 | stackoverflow | MACHINE_LEARNING | Simple vanilla RNN doesn't pass gradient check | Simple vanilla RNN doesn't pass gradient check
I recently tried to implement a vanilla RNN from scratch. I implemented everything and even ran a seemingly OK example! yet I noticed the gradient check is not successful! and only some parts (specifically weight and bias for the output) pass the gradient check while ... | https://stackoverflow.com/questions/55917959/simple-vanilla-rnn-doesnt-pass-gradient-check | python-3.x, deep-learning, recurrent-neural-network | 1,556,616,825 |
se_79406168 | stackoverflow | MACHINE_LEARNING | Code higher efficientnet models based on B0 model | Code higher efficientnet models based on B0 model
I wanted to utilize EfficientNet models for my study. However, while I was able to construct EfficientNet-B0, I'm stuck on the part on expanding it to it's higher models - B1, B2, so on..
Here is my implementation of my code for B0:
import torch
import torch.nn as nn
... | https://stackoverflow.com/questions/79406168/code-higher-efficientnet-models-based-on-b0-model | deep-learning, pytorch, efficientnet | 1,738,478,736 |
se_79667798 | stackoverflow | MACHINE_LEARNING | Keras AUC metric breaking on a multi-class problem | Keras AUC metric breaking on a multi-class problem
I'm attempting to train a multi-class image classification model based on standardised 128x128 images. When I use "accuracy" alone as a metric, I have no issues. When I introduce AUC, I can't train the model.
model = tf.keras.Sequential([
tf.keras.layers.Rescaling... | https://stackoverflow.com/questions/79667798/keras-auc-metric-breaking-on-a-multi-class-problem | python, tensorflow, keras, deep-learning, roc | 1,750,084,552 |
se_69970319 | stackoverflow | MACHINE_LEARNING | ValueError: Exception encountered when calling layer "sequential_5" (type Sequential) | ValueError: Exception encountered when calling layer "sequential_5" (type Sequential)
I am following this course :
TensorFlow Developer Certificate in 2022: Zero to Mastery
This is the following code :
# Set random seed
tf.random.set_seed(42)
# Create some regression data
X_regression = np.arange(0, 1000, ... | https://stackoverflow.com/questions/69970319/valueerror-exception-encountered-when-calling-layer-sequential-5-type-sequen | python, tensorflow, machine-learning, keras, deep-learning | 1,636,958,653 |
se_76839159 | stackoverflow | MACHINE_LEARNING | Transport endpoint is not connected in Colab Pro+ | Transport endpoint is not connected in Colab Pro+
I am a google colab pro+ user. I am trying to train a DL model and getting an error of "Transport endpoint is not connected", while training the model. I ve been using the pro version previously and faced the same error so I thought of upgrading but it didnt help as we... | https://stackoverflow.com/questions/76839159/transport-endpoint-is-not-connected-in-colab-pro | python, tensorflow, deep-learning, google-colaboratory | 1,691,184,140 |
se_79691807 | stackoverflow | MACHINE_LEARNING | How to find MSE when using a batch loader? | How to find MSE when using a batch loader?
I'm working on a regression task using deep learning models. While calculating the MSE, I have divided by the length of the dataset. However, ChatGPT is suggesting me to divide it by the length of the loader. What is the correct way to calculate MSE in this case?
Also, I want... | https://stackoverflow.com/questions/79691807/how-to-find-mse-when-using-a-batch-loader | python, deep-learning, pytorch, eval, mse | 1,751,810,199 |
se_74968093 | stackoverflow | MACHINE_LEARNING | Most efficient way to use a large image dataset with Google Colab -- getting drive timeout + memory errors | Most efficient way to use a large image dataset with Google Colab -- getting drive timeout + memory errors
I'm using Google Colab to a classifier in PyTorch and my training dataset has ~30,000 JPEG images which I have stored in my Google Drive. Efficiently using this large amount of data with Colab and Drive has been ... | https://stackoverflow.com/questions/74968093/most-efficient-way-to-use-a-large-image-dataset-with-google-colab-getting-dri | python, machine-learning, deep-learning, pytorch, google-colaboratory | 1,672,471,083 |
se_79684232 | stackoverflow | MACHINE_LEARNING | Hyperparameter tuning using Wandb or Keras Tuner - 10 fold Cross Validation | Hyperparameter tuning using Wandb or Keras Tuner - 10 fold Cross Validation
If I am using stratified 10-folds for classification/regression tasks, where do I need to define the logic for hyperparameter tuning using Scikit or Wandb?
Should it be inside the loop or outside?
I am currently unsure where to add that logic ... | https://stackoverflow.com/questions/79684232/hyperparameter-tuning-using-wandb-or-keras-tuner-10-fold-cross-validation | deep-learning, classification, hyperparameters, fine-tuning, optimizer-deeplearning | 1,751,255,586 |
se_79687024 | stackoverflow | MACHINE_LEARNING | Neural Network built from scratch using numpy isn't learning | Neural Network built from scratch using numpy isn't learning
I'm building a neural network from scratch using only Python and numpy, It's meant for classifying the MNIST data set, I got everything to work but the network isn't really learning, at epoch 0 it's accuracy is about 12% after 20 epochs, it increases to ... | https://stackoverflow.com/questions/79687024/neural-network-built-from-scratch-using-numpy-isnt-learning | python, numpy, machine-learning, deep-learning, neural-network | 1,751,441,876 |
se_79685782 | stackoverflow | MACHINE_LEARNING | softmax functions always outputing garbage numbers that don't add up to one | softmax functions always outputing garbage numbers that don't add up to one
I am creating a simple NN from scratch that can classify MNIST digits, It only has 1 hidden layer:-
Loading the data:
import numpy as np
import matplotlib.pyplot as plt
from keras.datasets import mnist
(x_train, y_train), (x_test, y_test)... | https://stackoverflow.com/questions/79685782/softmax-functions-always-outputing-garbage-numbers-that-dont-add-up-to-one | python, numpy, machine-learning, deep-learning, artificial-intelligence | 1,751,360,619 |
se_58692476 | stackoverflow | MACHINE_LEARNING | What is Adaptive Average Pooling and how does it work? | What is Adaptive Average Pooling and how does it work?
I recently came across a method in Pytorch when I try to implement AlexNet.
I don't understand how it works. Please explain the idea behind it (with some examples) and how it is different from Max Pooling or Average Pooling in terms of Neural Network functionality... | https://stackoverflow.com/questions/58692476/what-is-adaptive-average-pooling-and-how-does-it-work | python, math, neural-network, deep-learning, pytorch | 1,572,866,793 |
se_59149138 | stackoverflow | MACHINE_LEARNING | How do you invert a tensor of boolean values in Pytorch? | How do you invert a tensor of boolean values in Pytorch?
With NumPy, you can do it with np.invert(array), but there's no invert function in Pytorch. Let's say I have a 2D tensor of boolean values:
import torch
ts = torch.rand((10, 4)) < .5
tensor([[ True, True, False, True],
[ True, True, True, True],
... | https://stackoverflow.com/questions/59149138/how-do-you-invert-a-tensor-of-boolean-values-in-pytorch | python, python-3.x, machine-learning, deep-learning, pytorch | 1,575,338,009 |
se_71481711 | stackoverflow | MACHINE_LEARNING | OSError for huggingface model | OSError for huggingface model
I am trying to use a huggingface model (CamelBERT), but I am getting an error when loading the tokenizer:
Code:
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-ca")
model = AutoModelForMaskedLM.fr... | https://stackoverflow.com/questions/71481711/oserror-for-huggingface-model | python, deep-learning, nlp, huggingface-transformers, bert-language-model | 1,647,344,879 |
se_79674850 | stackoverflow | MACHINE_LEARNING | How can I create a Streamlit app to predict based on my MLP model? | How can I create a Streamlit app to predict based on my MLP model?
I am trying to create a Streamlit application that predicts hypertension risk based on patient input data using the MLP (Multilayer Perceptron) model I trained. Below is my Keras model code:
from tensorflow.keras.models import Sequential
from tensorflo... | https://stackoverflow.com/questions/79674850/how-can-i-create-a-streamlit-app-to-predict-based-on-my-mlp-model | python, deep-learning, streamlit, multiclass-classification, mlp | 1,750,559,743 |
se_79641155 | stackoverflow | MACHINE_LEARNING | CNN predicts constant values for sparse amplitude regression — can't learn true pixel values | CNN predicts constant values for sparse amplitude regression — can't learn true pixel values
I’m training a small CNN (code below) to predict sparse amplitude maps from binary masks.
Input: 60×60 image with exactly 15 pixels set to 1, rest are 0.
Target: Same size, 0 everywhere except those 15 pixels, which have... | https://stackoverflow.com/questions/79641155/cnn-predicts-constant-values-for-sparse-amplitude-regression-cant-learn-true | tensorflow, machine-learning, deep-learning, pytorch, conv-neural-network | 1,748,377,627 |
se_79656139 | stackoverflow | MACHINE_LEARNING | tf.keras: Why my UNet with final layer Conv3D with sigmoid activation gives probabilities less than 0 and more than 1 | tf.keras: Why my UNet with final layer Conv3D with sigmoid activation gives probabilities less than 0 and more than 1
I am really confused because this should never happen according to common sense and to all things that I found on the internet.
In short. My UNet with sigmoid activation as last layer gives probabiliti... | https://stackoverflow.com/questions/79656139/tf-keras-why-my-unet-with-final-layer-conv3d-with-sigmoid-activation-gives-prob | python, tensorflow, keras, deep-learning | 1,749,223,643 |
se_79618223 | stackoverflow | MACHINE_LEARNING | PyTorch3D Build Fails with "Cannot open include file: 'thrust/detail/cstdint.h'" | PyTorch3D Build Fails with "Cannot open include file: 'thrust/detail/cstdint.h'"
I'm trying to build PyTorch3D from source on Windows 11 using CUDA 12.8, but the build fails with the following error during the compilation of CUDA extensions:
FAILED: D:/Project/3D_Reconstruction/src/pytorch3d/build/te... | https://stackoverflow.com/questions/79618223/pytorch3d-build-fails-with-cannot-open-include-file-thrust-detail-cstdint-h | python, machine-learning, deep-learning, pytorch, computer-vision | 1,747,065,151 |
se_79663362 | stackoverflow | MACHINE_LEARNING | SFTTrainer: The specified `eos_token` ('<EOS_TOKEN>') is not found in the vocabulary of the given `processing_class` (Qwen2TokenizerFast) | SFTTrainer: The specified `eos_token` ('<EOS_TOKEN>') is not found in the vocabulary of the given `processing_class` (Qwen2TokenizerFast)
I upgraded my Python trl package to version 0.18.1. I use the SFTTrainer of the package to finetune a Qwen2.5 LLM neural net. Previously, I used the TrainingArgument c... | https://stackoverflow.com/questions/79663362/sfttrainer-the-specified-eos-token-eos-token-is-not-found-in-the-vocabu | python, deep-learning, neural-network, huggingface-transformers, huggingface | 1,749,724,543 |
se_56188112 | stackoverflow | MACHINE_LEARNING | Table Detection Task (TableBank & Detectron ) : UnicodeDecodeError: 'ascii' codec can't decode byte 0x80 in position 0: ordinal not in range(128) | Table Detection Task (TableBank & Detectron ) : UnicodeDecodeError: 'ascii' codec can't decode byte 0x80 in position 0: ordinal not in range(128)
I have been trying to run a python script to test a pretrained model (ResNeXt-101) and visualize the performance of a Table Detection task proposed by TableB... | https://stackoverflow.com/questions/56188112/table-detection-task-tablebank-detectron-unicodedecodeerror-ascii-code | python, machine-learning, deep-learning, object-detection, faster-rcnn | 1,558,101,992 |
se_60667134 | stackoverflow | MACHINE_LEARNING | How to visualize 3d joints of a SMPL model based on pose params | How to visualize 3d joints of a SMPL model based on pose params
I am trying to use demo.py in nkolot
/
GraphCMR | GitHub. I am interested in obtaining joints from the inferred SMPL image and visualize it similar to described in README of this project: gulvarol
/
smplpytorch | GitHub.
I also posted the issue here: http... | https://stackoverflow.com/questions/60667134/how-to-visualize-3d-joints-of-a-smpl-model-based-on-pose-params | deep-learning, computer-vision, pytorch | 1,584,088,157 |
se_79666183 | stackoverflow | MACHINE_LEARNING | Error forming mini-batch for network input | Error forming mini-batch for network input
I am trying to predict vehicle trajectory, using t-30 data sequence to predict until t+30 trajectory. The data I have created is an neighbour occupancy matrix for each frames for each cars, this data is 13x3x1x30x138634 where 13x3 the grid, 1 is the channel, 30 is sequence le... | https://stackoverflow.com/questions/79666183/error-forming-mini-batch-for-network-input | matlab, deep-learning, neural-network, lstm, bilstm | 1,749,938,004 |
se_72725944 | stackoverflow | MACHINE_LEARNING | Create custom connection/ non-fully connected layers in Pytorch | Create custom connection/ non-fully connected layers in Pytorch
As shown in the figure, it is a 3 layer with NN, namely input layer, hidden layer and output layer. I want to design the NN(in PyTorch, just the arch) where the input to hidden layer is fully-connected. However, from hidden layer to output, the first two ... | https://stackoverflow.com/questions/72725944/create-custom-connection-non-fully-connected-layers-in-pytorch | python, machine-learning, deep-learning, neural-network, pytorch | 1,655,968,201 |
se_73439716 | stackoverflow | MACHINE_LEARNING | How to use val.py to calculate mAP on custom testing dataset of YOLOv5? | How to use val.py to calculate mAP on custom testing dataset of YOLOv5?
I am trying to calculate mAP on my testing dataset using this:
!python val.py --task test
I am using a custom data.yaml file. But I don't know how to point to that data.yaml. And when I use the following code:
val.py --data= /content/data.yaml -... | https://stackoverflow.com/questions/73439716/how-to-use-val-py-to-calculate-map-on-custom-testing-dataset-of-yolov5 | deep-learning, neural-network, computer-vision, conv-neural-network, yolov5 | 1,661,136,224 |
se_79662912 | stackoverflow | MACHINE_LEARNING | How can I improve the accuracy of my Transformer-based text classification model (news headlines)? | How can I improve the accuracy of my Transformer-based text classification model (news headlines)?
I'm training a Transformer-based text classification model from scratch using PyTorch. The goal is to classify news articles (headline + short description) into 15 classes. I'm achieving about 72–75% validation accuracy,... | https://stackoverflow.com/questions/79662912/how-can-i-improve-the-accuracy-of-my-transformer-based-text-classification-model | machine-learning, deep-learning, artificial-intelligence | 1,749,702,650 |
se_79648131 | stackoverflow | MACHINE_LEARNING | filedescriptor out of range in select() | filedescriptor out of range in select()
I am running a training job using MLflow and an MLflow recipe. In the recipe.train step, the training starts an experiment and runs for 350 epochs. After the 350 epochs are completed and I try to log the artifacts, the process gets stuck for a long time and I keep getting this e... | https://stackoverflow.com/questions/79648131/filedescriptor-out-of-range-in-select | machine-learning, deep-learning, databricks, mlflow | 1,748,833,712 |
se_77444485 | stackoverflow | MACHINE_LEARNING | Using positional encoding in pytorch | Using positional encoding in pytorch
Is there any built-in positional encoding in pytorch? Basically, I want to be able to specify the dimension of the encoding, and then be able to get the i'th encoding for every i. | https://stackoverflow.com/questions/77444485/using-positional-encoding-in-pytorch | python, deep-learning, pytorch, transformer-model | 1,699,437,475 |
se_70816481 | stackoverflow | MACHINE_LEARNING | IndexError: index 89 is out of bounds for axis 0 with size 89 | IndexError: index 89 is out of bounds for axis 0 with size 89
I am getting this error but I don't understand how to solve it, can anyone please help?
I am trying to run a pre-implemented project on my own text dataset. I am using CUB 200-2011 bird dataset which had initially 11788 birds images and author model has bee... | https://stackoverflow.com/questions/70816481/indexerror-index-89-is-out-of-bounds-for-axis-0-with-size-89 | python, machine-learning, deep-learning, pytorch | 1,642,880,417 |
se_79597119 | stackoverflow | MACHINE_LEARNING | How to reduce GPU memory usage when running Stable Diffusion with HuggingFace Diffusers? | How to reduce GPU memory usage when running Stable Diffusion with HuggingFace Diffusers?
I'm trying to run Stable Diffusion using HuggingFace's diffusers library, but I keep getting CUDA out of memory errors on my RTX 3060 (12GB VRAM). I'm using the standard StableDiffusionPipeline from the "CompVis/stable-diffusion-v... | https://stackoverflow.com/questions/79597119/how-to-reduce-gpu-memory-usage-when-running-stable-diffusion-with-huggingface-di | python, machine-learning, deep-learning, pytorch, stable-diffusion | 1,745,866,176 |
se_55411921 | stackoverflow | MACHINE_LEARNING | Is there a pytorch method to check the number of cpus? | Is there a pytorch method to check the number of cpus?
I can use this torch.cuda.device_count() to check the number of GPUs. I was wondering if there was something equivalent to check the number of CPUs. | https://stackoverflow.com/questions/55411921/is-there-a-pytorch-method-to-check-the-number-of-cpus | python, neural-network, deep-learning, pytorch | 1,553,842,208 |
se_79655975 | stackoverflow | MACHINE_LEARNING | Fourier Neural Operator in tensorflow nearly good | Fourier Neural Operator in tensorflow nearly good
I try to implement in tensorflow a Fourier Neural Operator from this paper in 2D. As simple example, i have a single layer that learns to perform a gaussian blur.
However, there are littles errors especialy on horizontal lines (right image). I dont know why.
Many thank... | https://stackoverflow.com/questions/79655975/fourier-neural-operator-in-tensorflow-nearly-good | python, tensorflow, deep-learning, fft | 1,749,215,060 |
se_79652372 | stackoverflow | MACHINE_LEARNING | I'm training a image captioning model and getting Nan in my loss | I'm training a image captioning model and getting Nan in my loss
I'm training a image caption model using TensorFlow. I'm using Flickr 8K dataset and I have used ResNet50 to get the encoding of all my images shaped as (m,49,2048) and stored them for training. I have used GloVe 6B 300d vectors for my vocab and embe... | https://stackoverflow.com/questions/79652372/im-training-a-image-captioning-model-and-getting-nan-in-my-loss | image, tensorflow, deep-learning, nan, loss | 1,749,025,145 |
se_79655017 | stackoverflow | MACHINE_LEARNING | Confused about r-torch syntax | Confused about r-torch syntax
I have been trying to tackle a regression problem by training a neural network to predict a continuous variable using r-torch. My question pertains to the syntax used to achieve this.
When initializing the dataset for torch, I have to declare what 'x' and 'y' are. I understand that 'y' is... | https://stackoverflow.com/questions/79655017/confused-about-r-torch-syntax | r, machine-learning, deep-learning, neural-network, torch | 1,749,147,688 |
se_79430117 | stackoverflow | MACHINE_LEARNING | How to extract tables from a PDF and convert them into structured HTML (<table>, <tr>, <td>) while maintaining the original layout and formatting? | How to extract tables from a PDF and convert them into structured HTML (<table>, <tr>, <td>) while maintaining the original layout and formatting?
1]Original page of Doc1 contain 4 tables
1]Output .html page of Doc1 not detecting table properly,sometimes extracting text from table as plain text
2]Ori... | https://stackoverflow.com/questions/79430117/how-to-extract-tables-from-a-pdf-and-convert-them-into-structured-html-table | python, machine-learning, deep-learning, langchain, large-language-model | 1,739,280,110 |
se_70965317 | stackoverflow | MACHINE_LEARNING | How to fit column wise ordinal encoding | How to fit column wise ordinal encoding
I have a dataframe like as shown below
tdf = pd.DataFrame({'grade': np.random.choice(list('AAAD'),size=(5)),
'dash': np.random.choice(list('PPPS'),size=(5)),
'dumeel': np.random.choice(list('QWRR'),size=(5)),
'dumma': np.r... | https://stackoverflow.com/questions/70965317/how-to-fit-column-wise-ordinal-encoding | python, pandas, machine-learning, scikit-learn, deep-learning | 1,643,856,067 |
se_57532679 | stackoverflow | MACHINE_LEARNING | Why "GELU" activation function is used instead of ReLu in BERT? | Why "GELU" activation function is used instead of ReLu in BERT?
The activation function Gaussian Error Linear Units(GELUs) is used in the popular NLP model BERT. Is there any solid reason ? | https://stackoverflow.com/questions/57532679/why-gelu-activation-function-is-used-instead-of-relu-in-bert | deep-learning, nlp | 1,566,005,661 |
se_79647350 | stackoverflow | MACHINE_LEARNING | Looking for an efficent JAX function to reconstruct an image from patches | Looking for an efficent JAX function to reconstruct an image from patches
I have a set of images in (c, h, w) jax arrays. These arrays have been converted to (patch_index, patch_dim) arrays where patch_dim == c * h * w.
I am trying to reconstruct the original images from the patches. Here is vanilla python code that w... | https://stackoverflow.com/questions/79647350/looking-for-an-efficent-jax-function-to-reconstruct-an-image-from-patches | python, machine-learning, deep-learning, computer-vision, jax | 1,748,767,774 |
se_79645357 | stackoverflow | MACHINE_LEARNING | Problem in fine tuning DeepLabV3Plus using keras_cv for Semantic Segmentation | Problem in fine tuning DeepLabV3Plus using keras_cv for Semantic Segmentation
I'm using open-images-v7 dataset (accessing via fiftyone lib) and keras_cv lib to fine tune DeepLabV3Plus with mobilenet_v3_small backbone, but the accuracy doesn't improve with epochs at all, and I'm getting shape warning.
Dataset Preparati... | https://stackoverflow.com/questions/79645357/problem-in-fine-tuning-deeplabv3plus-using-keras-cv-for-semantic-segmentation | python, machine-learning, keras, deep-learning, semantic-segmentation | 1,748,603,651 |
se_55705749 | stackoverflow | MACHINE_LEARNING | Should Test and Dev Set have different distribution from Training Set an Dev Set | Should Test and Dev Set have different distribution from Training Set an Dev Set
Suppose I am building a network to localize an object. My training data consists of images captured at 5 different locations, and its a small data set ( each location has around 2k images ). Should I add all the images, shuffle them and t... | https://stackoverflow.com/questions/55705749/should-test-and-dev-set-have-different-distribution-from-training-set-an-dev-set | machine-learning, neural-network, deep-learning, conv-neural-network | 1,555,409,618 |
se_73471929 | stackoverflow | MACHINE_LEARNING | How to use OneCycleLR? | How to use OneCycleLR?
I want to train on CIFAR-10, suppose for 200 epochs.
This is my optimizer:
optimizer = optim.Adam([x for x in model.parameters() if x.requires_grad], lr=0.001)
I want to use OneCycleLR as scheduler. Now, according to the documentation, these are the parameters of OneCycleLR:
torch.optim.lr_sched... | https://stackoverflow.com/questions/73471929/how-to-use-onecyclelr | optimization, deep-learning, neural-network, pytorch, learning-rate | 1,661,338,702 |
se_57977880 | stackoverflow | MACHINE_LEARNING | Testing that I've installed PyTorch correctly | Testing that I've installed PyTorch correctly
I have installed the PyTorch. How can I test in my Python script whether the installation is correct, e.g., whether it can enable CUDA or not, etc? | https://stackoverflow.com/questions/57977880/testing-that-ive-installed-pytorch-correctly | deep-learning, pytorch | 1,568,735,406 |
se_70906050 | stackoverflow | MACHINE_LEARNING | How many num_workers in DataLoader? | How many num_workers in DataLoader?
I have a machine with 1500 Gb of ram and 112 cores but no GPU. I would like to know how to calculate suitable number of num_workers in DataLoader and batch size.
I have to make the inference with Inception-v3(pytorch) on 80,000,000 images.
I tried with a batch size of 30k and num_wo... | https://stackoverflow.com/questions/70906050/how-many-num-workers-in-dataloader | python, machine-learning, deep-learning, pytorch | 1,643,463,981 |
se_73874287 | stackoverflow | MACHINE_LEARNING | How do I resolve the error: Attempting to use a delegate that only supports static-sized tensors with a graph that has dynamic-sized tensors? | How do I resolve the error: Attempting to use a delegate that only supports static-sized tensors with a graph that has dynamic-sized tensors?
I am trying to compile an image segmentation (U-net) model to run it on edge TPU (Coral Board). I have converted and quantized the model into .tflite and I am getting the follow... | https://stackoverflow.com/questions/73874287/how-do-i-resolve-the-error-attempting-to-use-a-delegate-that-only-supports-stat | python, tensorflow, deep-learning, tflite, edge-tpu | 1,664,316,884 |
se_63006575 | stackoverflow | MACHINE_LEARNING | What is the difference between MaxPool and MaxPooling layers in Keras? | What is the difference between MaxPool and MaxPooling layers in Keras?
I just started working with keras and noticed that there are two layers with very similar names for max-pooling: MaxPool and MaxPooling. I was surprised that I couldn't find the difference between these two on Google; so I am wondering what the dif... | https://stackoverflow.com/questions/63006575/what-is-the-difference-between-maxpool-and-maxpooling-layers-in-keras | python, tensorflow, machine-learning, keras, deep-learning | 1,595,299,480 |
se_70097798 | stackoverflow | MACHINE_LEARNING | Does number of parameters and FLOPS change when converting a model from PyTorch to ONNX or TensorRT format? | Does number of parameters and FLOPS change when converting a model from PyTorch to ONNX or TensorRT format?
Does number of parameters and FLOPS (float operations per second) change when converting a model from PyTorch to ONNX or TensorRT format? | https://stackoverflow.com/questions/70097798/does-number-of-parameters-and-flops-change-when-converting-a-model-from-pytorch | deep-learning, pytorch, onnx, tensorrt | 1,637,763,821 |
se_79597666 | stackoverflow | MACHINE_LEARNING | RuntimeError: mat1 and mat2 shapes cannot be multiplied when using gradcam | RuntimeError: mat1 and mat2 shapes cannot be multiplied when using gradcam
I made a cnn model like this and trained the batch dataset.
My data preprocessing code was this
train_dir = r'C:\Users\roobe\BACH\norm\train\patches\train' # 훈련 데이터 폴더
val_dir = r'C:\Users\roobe\BACH\norm\train\patches\val' # 검증 데이터 폴더
# 데이터... | https://stackoverflow.com/questions/79597666/runtimeerror-mat1-and-mat2-shapes-cannot-be-multiplied-when-using-gradcam | python, tensorflow, machine-learning, deep-learning | 1,745,904,934 |
se_53972159 | stackoverflow | MACHINE_LEARNING | How does Pytorch's "Fold" and "Unfold" work? | How does Pytorch's "Fold" and "Unfold" work?
I've gone through the official doc. I'm having a hard time understanding what this function is used for and how it works. Can someone explain this in layman's terms? | https://stackoverflow.com/questions/53972159/how-does-pytorchs-fold-and-unfold-work | python, machine-learning, deep-learning, computer-vision, pytorch | 1,546,107,254 |
se_42480111 | stackoverflow | MACHINE_LEARNING | How do I print the model summary in PyTorch? | How do I print the model summary in PyTorch?
How do I print the summary of a model in PyTorch like what model.summary() does in Keras:
Model Summary:
____________________________________________________________________________________________________
Layer (type) Output Shape Param # C... | https://stackoverflow.com/questions/42480111/how-do-i-print-the-model-summary-in-pytorch | python, machine-learning, deep-learning, pytorch | 1,488,180,942 |
se_61598771 | stackoverflow | MACHINE_LEARNING | `squeeze()` vs `unsqueeze()` in PyTorch | `squeeze()` vs `unsqueeze()` in PyTorch
I don't understand what squeeze() and unsqueeze() do to a tensor, even after looking at the docs and related questions.
I tried to understand it by exploring it myself in python. I first created a random tensor with
x = torch.rand(3,2,dtype=torch.float)
>>> x
tensor([[0.3703, 0.... | https://stackoverflow.com/questions/61598771/squeeze-vs-unsqueeze-in-pytorch | python, machine-learning, deep-learning, pytorch, tensor | 1,588,615,598 |
se_54307225 | stackoverflow | MACHINE_LEARNING | `stack()` vs `cat()` in PyTorch | `stack()` vs `cat()` in PyTorch
OpenAI's REINFORCE and actor-critic example for reinforcement learning has the following code:
REINFORCE:
policy_loss = torch.cat(policy_loss).sum()
actor-critic:
loss = torch.stack(policy_losses).sum() + torch.stack(value_losses).sum()
One is using torch.cat, the other uses torch.sta... | https://stackoverflow.com/questions/54307225/stack-vs-cat-in-pytorch | python, machine-learning, deep-learning, pytorch, concatenation | 1,548,156,287 |
se_66488807 | stackoverflow | MACHINE_LEARNING | PyTorch model input shape | PyTorch model input shape
I loaded a custom PyTorch model and I want to find out its input shape. Something like this:
model.input_shape
Is it possible to get this information?
Update: print() and summary() don't show this model's input shape, so they are not what I'm looking for. | https://stackoverflow.com/questions/66488807/pytorch-model-input-shape | python, machine-learning, deep-learning, pytorch, conv-neural-network | 1,614,931,192 |
se_57234095 | stackoverflow | MACHINE_LEARNING | What is the difference between .flatten() and .view(-1) in PyTorch? | What is the difference between .flatten() and .view(-1) in PyTorch?
Both .flatten() and .view(-1) flatten a tensor in PyTorch. What's the difference?
Does .flatten() copy the data of the tensor?
Is .view(-1) faster?
Is there any situation that .flatten() doesn't work? | https://stackoverflow.com/questions/57234095/what-is-the-difference-between-flatten-and-view-1-in-pytorch | python, machine-learning, deep-learning, pytorch | 1,564,245,319 |
se_57237352 | stackoverflow | MACHINE_LEARNING | What does "unsqueeze" do in Pytorch? | What does "unsqueeze" do in Pytorch?
The PyTorch documentation says:
Returns a new tensor with a dimension of size one inserted at the specified position. [...]
>>> x = torch.tensor([1, 2, 3, 4])
>>> torch.unsqueeze(x, 0)
tensor([[ 1, 2, 3, 4]])
>>> torch.unsqueeze(x, 1)
tensor([[ 1],
[ 2],
... | https://stackoverflow.com/questions/57237352/what-does-unsqueeze-do-in-pytorch | python, numpy, machine-learning, deep-learning, pytorch | 1,564,278,223 |
se_77418680 | stackoverflow | MACHINE_LEARNING | Should the shuffle=True argument be used during training in torch.utils.data.DataLoader() when we have time series data? | Should the shuffle=True argument be used during training in torch.utils.data.DataLoader() when we have time series data?
I am confused regarding whether the shuffle=True argument should be used in the pytorch torch.utils.data.DataLoader() during training when the training data are time series data. I believe that shuf... | https://stackoverflow.com/questions/77418680/should-the-shuffle-true-argument-be-used-during-training-in-torch-utils-data-dat | python, deep-learning, pytorch, time-series, pytorch-dataloader | 1,699,033,125 |
se_33962226 | stackoverflow | MACHINE_LEARNING | Common causes of nans during training of neural networks | Common causes of nans during training of neural networks
I've noticed that a frequent occurrence during training is NANs being introduced.
Often times it seems to be introduced by weights in inner-product/fully-connected or convolution layers blowing up.
Is this occurring because the gradient computation is blowing ... | https://stackoverflow.com/questions/33962226/common-causes-of-nans-during-training-of-neural-networks | machine-learning, neural-network, deep-learning, caffe, gradient-descent | 1,448,645,010 |
se_76644106 | stackoverflow | MACHINE_LEARNING | How to resolve runtime error in CNN model related to mismatch input size? | How to resolve runtime error in CNN model related to mismatch input size?
I am trying to run a CNN model on a synthetic dataset consisting of 4000 sample of semi simple random points with 2 features and 1 cluster per class and input data size x is [4000,2] and corresponding labels size is [4000].
I understand that as ... | https://stackoverflow.com/questions/76644106/how-to-resolve-runtime-error-in-cnn-model-related-to-mismatch-input-size | machine-learning, deep-learning, pytorch, neural-network, conv-neural-network | 1,688,836,447 |
se_79611606 | stackoverflow | MACHINE_LEARNING | Is it safe to save preprocessed features with numpy in one Python environment and load them in another for model training? | Is it safe to save preprocessed features with numpy in one Python environment and load them in another for model training?
I'm working on a deepfake detection project using TensorFlow 2.6.2 on Windows. Due to package version conflicts (e.g. tensorflow==2.6.2 requires flatbuffers==1.12, but mediapipe requires flatbuffe... | https://stackoverflow.com/questions/79611606/is-it-safe-to-save-preprocessed-features-with-numpy-in-one-python-environment-an | python, tensorflow, deep-learning | 1,746,668,140 |
se_78975293 | stackoverflow | MACHINE_LEARNING | Linear FFNN Model achieving 100% accuracy in predicting sums | Linear FFNN Model achieving 100% accuracy in predicting sums
I have a model that adds numbers between -10 to positive 10. The task is simply to predict the sum of those numbers. However the train accuracy quickly reaches 100%.
I am not sure if the model is just quickly training, or if there is something wrong and it i... | https://stackoverflow.com/questions/78975293/linear-ffnn-model-achieving-100-accuracy-in-predicting-sums | python, machine-learning, deep-learning, pytorch, perceptron | 1,726,080,228 |
se_79609919 | stackoverflow | MACHINE_LEARNING | How to make NN really find optimal solution during training? | How to make NN really find optimal solution during training?
Imagine a simple problem: make a function that gets a month index as input (zero-based: 0=Jan, 1=Feb, etc) and outputs number of days in this month (leap year ignored).
Of course, using NN for that task is an overkill, but I wondered, can NN actually be trai... | https://stackoverflow.com/questions/79609919/how-to-make-nn-really-find-optimal-solution-during-training | machine-learning, deep-learning, pytorch, artificial-intelligence | 1,746,600,444 |
se_79607852 | stackoverflow | MACHINE_LEARNING | GNN Loss NaN after first training example? | GNN Loss NaN after first training example?
I am trying to train a GNN but am getting a NaN loss function immediately after the first training example. Below I have included all of the pertinent code. My input is 385 points in 3D space confined to a box with periodic boundary conditions. My model takes 5 inputs:
a 385... | https://stackoverflow.com/questions/79607852/gnn-loss-nan-after-first-training-example | python, tensorflow, keras, deep-learning | 1,746,496,141 |
se_64488034 | stackoverflow | MACHINE_LEARNING | InceptionResnetV2 STEM block keras implementation mismatch the one in the original paper? | InceptionResnetV2 STEM block keras implementation mismatch the one in the original paper?
I've been trying to compare the InceptionResnetV2 model summary from Keras implementation with the one specified in their paper, and it doesn't seem to show much resemblance when it comes to the filter_concat block.
The first lin... | https://stackoverflow.com/questions/64488034/inceptionresnetv2-stem-block-keras-implementation-mismatch-the-one-in-the-origin | keras, deep-learning, neural-network, conv-neural-network | 1,603,389,756 |
se_49643603 | stackoverflow | MACHINE_LEARNING | Spark deep learning Import error | Spark deep learning Import error
I am trying to replicate a deep learning project from https://medium.com/linagora-engineering/making-image-classification-simple-with-spark-deep-learning-f654a8b876b8 . I am working on spark version 1.6.3. I have installed keras and tensorflow. But everytime i try to import from sparkd... | https://stackoverflow.com/questions/49643603/spark-deep-learning-import-error | apache-spark, pyspark, deep-learning | 1,522,820,574 |
se_79603047 | stackoverflow | MACHINE_LEARNING | ray.tune: Tracked actor is not managed | ray.tune: Tracked actor is not managed
from ray import tune
from ray.tune.search.optuna import OptunaSearch
from ray.tune.integration.pytorch_lightning import TuneReportCheckpointCallback
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import EarlyStopping
from data_module import D... | https://stackoverflow.com/questions/79603047/ray-tune-tracked-actor-is-not-managed | python, machine-learning, deep-learning, neural-network, ray | 1,746,175,215 |
se_79603121 | stackoverflow | MACHINE_LEARNING | ComfyUI LHM Node: "LHM stack expects a non-empty TensorList" errors when running workflow | ComfyUI LHM Node: "LHM stack expects a non-empty TensorList" errors when running workflow
I'm trying to use the LHM ComfyUI Node from this GitHub repository.
I followed all the installation steps provided in the repo. However, I encountered several issues:
The provided workflow JSON couldn't be opened at fi... | https://stackoverflow.com/questions/79603121/comfyui-lhm-node-lhm-stack-expects-a-non-empty-tensorlist-errors-when-running | deep-learning, artificial-intelligence, stable-diffusion | 1,746,177,991 |
se_70871980 | stackoverflow | MACHINE_LEARNING | Is there an annotation tool for instance segmentation on Ipad? | Is there an annotation tool for instance segmentation on Ipad?
Is there an annotation tool to produce multi layer (for overlapping objects within the image) and pixel exact image annotations on IPad?
Background to my question:
There a lot of annotation tools for Linux and Windows
(e.g. the ones listed here: https://ww... | https://stackoverflow.com/questions/70871980/is-there-an-annotation-tool-for-instance-segmentation-on-ipad | ipad, deep-learning, pytorch, image-annotations | 1,643,244,001 |
se_79495211 | stackoverflow | MACHINE_LEARNING | OSError when importing PyTorch: "Error loading torch_python.dll or one of its dependencies" | OSError when importing PyTorch: "Error loading torch_python.dll or one of its dependencies"
I installed PyTorch using pip install torch, but when I try to import it, I get the following error:
OSError Traceback (most recent call last)
Cell In[1], line 1
----> 1 import to... | https://stackoverflow.com/questions/79495211/oserror-when-importing-pytorch-error-loading-torch-python-dll-or-one-of-its-de | machine-learning, deep-learning, pytorch | 1,741,478,612 |
se_79600027 | stackoverflow | MACHINE_LEARNING | How to implement support for multiple dynamic model responses in deep-chat Angular? | How to implement support for multiple dynamic model responses in deep-chat Angular?
enter image description hereI am working with the deep-chat library and am trying to support multiple models in my setup. Specifically, I want to handle multiple models inside the onMessage event by making manual fetch requests to dyna... | https://stackoverflow.com/questions/79600027/how-to-implement-support-for-multiple-dynamic-model-responses-in-deep-chat-angul | javascript, angular, deep-learning, chat-gpt-4 | 1,746,005,691 |
se_68058974 | stackoverflow | MACHINE_LEARNING | How to do batch inferenece for Hugging face models? | How to do batch inferenece for Hugging face models?
I want to do batch inference on MarianMT model. Here's the code:
from transformers import MarianTokenizer
tokenizer = MarianTokenizer.from_pretrained('Helsinki-NLP/opus-mt-en-de')
src_texts = [ "I am a small frog.", "Tom asked his teacher for advice."]
tgt_texts = ["... | https://stackoverflow.com/questions/68058974/how-to-do-batch-inferenece-for-hugging-face-models | machine-learning, deep-learning, nlp, huggingface-transformers, machine-translation | 1,624,214,150 |
se_77792137 | stackoverflow | MACHINE_LEARNING | How to fix the learning-rate for Huggingface´s Trainer? | How to fix the learning-rate for Huggingface´s Trainer?
I'm training model with the following parameters:
Seq2SeqTrainingArguments(
output_dir = "./out",
overwrite_output_dir = True,
do_train = True,
do_eval = True,
per_d... | https://stackoverflow.com/questions/77792137/how-to-fix-the-learning-rate-for-huggingface%c2%b4s-trainer | machine-learning, deep-learning, huggingface-transformers, huggingface-trainer, learning-rate | 1,704,878,066 |
se_79419018 | stackoverflow | MACHINE_LEARNING | YOLOv8 Final Detection Head Still Outputs (1, 7, 8400) Instead of (1, 8, 8400) for 3 Classes | YOLOv8 Final Detection Head Still Outputs (1, 7, 8400) Instead of (1, 8, 8400) for 3 Classes
I trained a YOLOv8 detection model with 3 classes, but the raw forward pass still shows a final detect output of (1, 7, 8400) instead of (1, 8, 8400).
What I’ve Done:
Checked my data.yaml:
train: path/to/train/images
val: path... | https://stackoverflow.com/questions/79419018/yolov8-final-detection-head-still-outputs-1-7-8400-instead-of-1-8-8400-f | machine-learning, deep-learning, pytorch, yolov8, ultralytics | 1,738,867,161 |
se_79590419 | stackoverflow | MACHINE_LEARNING | Trouble loading tensorflow when running cloned repo | Trouble loading tensorflow when running cloned repo
So, I'm trying to get the code from this repo https://github.com/amin20/GBM_WSSM working but I'm running into a persistent error.
Using TensorFlow backend.
Traceback (most recent call last):
File "C:\Users\trans\source\repos\GBM_WSSM\.venv\lib\site-packages\tensorf... | https://stackoverflow.com/questions/79590419/trouble-loading-tensorflow-when-running-cloned-repo | python, tensorflow, keras, deep-learning | 1,745,492,847 |
se_77842203 | stackoverflow | MACHINE_LEARNING | ValidationError: 2 validation errors for LLMChain | ValidationError: 2 validation errors for LLMChain
This is my complete code:
!pip install -q transformers einops accelerate langchain bitsandbytes sentence_transformers faiss-cpu pypdf sentencepiece
from langchain import HuggingFacePipeline
from transformers import AutoTokenizer
from langchain.embeddings impo... | https://stackoverflow.com/questions/77842203/validationerror-2-validation-errors-for-llmchain | python, machine-learning, deep-learning, langchain, large-language-model | 1,705,609,248 |
se_79583654 | stackoverflow | MACHINE_LEARNING | Logits Don't Change in a Custom Reimplementation of a CLIP model [PyTorch] | Logits Don't Change in a Custom Reimplementation of a CLIP model [PyTorch]
The problem
The similarity scores are almost the same for texts that describe both a photo of a cat and a dog (the photo is of a cat).
Cat similarity: tensor([[-3.5724]], grad_fn=<MulBackward0>)
Dog similarity: tensor([[-3.4155]], grad_fn=<... | https://stackoverflow.com/questions/79583654/logits-dont-change-in-a-custom-reimplementation-of-a-clip-model-pytorch | python, deep-learning, pytorch, artificial-intelligence, transformer-model | 1,745,174,763 |
se_79584724 | stackoverflow | MACHINE_LEARNING | Is there a way to update weights of an nnx.Module in Flax's NNX using the lax.scan function? | Is there a way to update weights of an nnx.Module in Flax's NNX using the lax.scan function?
I have a neural network (nnx.Module) written in Flax's NNX. I want to train this network efficiently using lax.scan instead of a for loop. However, as scan doesn't allow in place changes, how can I update the weights of my... | https://stackoverflow.com/questions/79584724/is-there-a-way-to-update-weights-of-an-nnx-module-in-flaxs-nnx-using-the-lax-sc | deep-learning, jax, flax | 1,745,242,153 |
se_74411789 | stackoverflow | MACHINE_LEARNING | How to use early terminate in wandb sweep? | How to use early terminate in wandb sweep?
I am trying to use wandb sweep to tune the hyperparameter in a model, and also try to use the hyperband early terminate method to accelerate it.
However, I don't understand how this mechanism works by looking up the docs https://docs.wandb.ai/guides/sweeps/define-sweep-config... | https://stackoverflow.com/questions/74411789/how-to-use-early-terminate-in-wandb-sweep | deep-learning, hyperparameters, wandb | 1,668,245,466 |
se_79582481 | stackoverflow | MACHINE_LEARNING | Torch gradient estimates disagreeing with analytic and perturbation approximated gradients | Torch gradient estimates disagreeing with analytic and perturbation approximated gradients
I'm faced with a problem where as the title says I'm having trouble with the torch package's built in automatic differentiation algorithms (or my usage?). I think it was meant to be used on mini-batches in my assignment but it s... | https://stackoverflow.com/questions/79582481/torch-gradient-estimates-disagreeing-with-analytic-and-perturbation-approximated | deep-learning, pytorch, neural-network, gradient-descent | 1,745,071,934 |
se_79559377 | stackoverflow | MACHINE_LEARNING | How to handle outputs of variable length when predicting with a Feed Forward Neural Network? | How to handle outputs of variable length when predicting with a Feed Forward Neural Network?
I am working on a regression problem where, given an input X of fixed size, the output Y can be a sequence of values of variable length.
Both input and output are normalised float values. Thus, we are talking about a regressio... | https://stackoverflow.com/questions/79559377/how-to-handle-outputs-of-variable-length-when-predicting-with-a-feed-forward-neu | machine-learning, deep-learning, neural-network | 1,744,013,634 |
se_65616825 | stackoverflow | MACHINE_LEARNING | DCgAN generates only noises | DCgAN generates only noises
I'm new to GANs and I have trouble in training DCGAN on mnist, when I was working with GAN with linear layers everything was fine and the generator generates pretty good images. But when I started working with Convolutional GAN, the generator generators only noise. Does anybody know how to ... | https://stackoverflow.com/questions/65616825/dcgan-generates-only-noises | machine-learning, deep-learning, neural-network, generative-adversarial-network, dcgan | 1,610,039,116 |
se_79354623 | stackoverflow | MACHINE_LEARNING | Low accuracy using vision transformers for Image classification | Low accuracy using vision transformers for Image classification
I'be been learning workings of an Vision transformer, I couldn't get it to run at first(building the ViT from scratch). But somehow I managed to scramble up a code that shows very low accuracy(3%).
Tried chatgpting myself through it, couldn't seem to figu... | https://stackoverflow.com/questions/79354623/low-accuracy-using-vision-transformers-for-image-classification | python, machine-learning, deep-learning, computer-vision, transformer-model | 1,736,849,235 |
se_79429910 | stackoverflow | MACHINE_LEARNING | Using tf.keras.utils.image_dataset_from_directory mismatches labels on the images | Using tf.keras.utils.image_dataset_from_directory mismatches labels on the images
Here's the code
train_dset = image_dataset_from_directory(
directory = data_path,
batch_size = 32,
image_size = (256,256),
label_mode = "int",
shuffle = True
)
in data_path, I have
-> dataset
|-> train
|-> ... | https://stackoverflow.com/questions/79429910/using-tf-keras-utils-image-dataset-from-directory-mismatches-labels-on-the-image | python, tensorflow, keras, deep-learning, conv-neural-network | 1,739,275,721 |
se_79571227 | stackoverflow | MACHINE_LEARNING | DIfference in variable values in jax non-jit runtime and jit transformed runtime | DIfference in variable values in jax non-jit runtime and jit transformed runtime
I have a deep learning mode which I am running in the jit transformed manner by:
my_function_checked = checkify.checkify(model.apply)
model_jitted = jax.jit(my_function_checked)
err, pred = model_jitted({"params": params}, batch, ... | https://stackoverflow.com/questions/79571227/difference-in-variable-values-in-jax-non-jit-runtime-and-jit-transformed-runtime | python, deep-learning, pytorch, artificial-intelligence, jax | 1,744,522,432 |
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