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_79104143 | stackoverflow | MACHINE_LEARNING | Low GPU utilization (0-5%) with high memory usage in model training | Low GPU utilization (0-5%) with high memory usage in model training
I'm working on a machine learning project using TensorFlow (version 2.10.1) to train a convolutional neural network (CNN) on sEMG signals. While my model utilizes nearly all of the GPU memory (10.8/12 GB), I've noticed that the GPU usage remains extre... | https://stackoverflow.com/questions/79104143/low-gpu-utilization-0-5-with-high-memory-usage-in-model-training | tensorflow, keras, deep-learning, gpu | 1,729,307,945 |
se_78254372 | stackoverflow | MACHINE_LEARNING | colab-error: subprocess-exited-with-error | colab-error: subprocess-exited-with-error
!pip install ecco
This error originates from a subprocess, and is likely not a problem with pip.
Downloading scikit-learn-0.23.2.tar.gz (7.2 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.2/7.2 MB 39.6 MB/s eta 0:00:00
error: subprocess-exited-with-error
× pip subprocess to in... | https://stackoverflow.com/questions/78254372/colab-error-subprocess-exited-with-error | python, deep-learning, artificial-intelligence, google-colaboratory | 1,711,959,840 |
se_79034907 | stackoverflow | MACHINE_LEARNING | Custom Encoder and Decoder Layers within Keras Model Show As Unbuilt | Custom Encoder and Decoder Layers within Keras Model Show As Unbuilt
I have a subclassed tensorflow.keras.Model Seq2Seq model with custom layers. However, when I try to run a test script to build and compile the model, running model.summary() gives:
Model: "retrosynthesis_seq2_seq_model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━... | https://stackoverflow.com/questions/79034907/custom-encoder-and-decoder-layers-within-keras-model-show-as-unbuilt | python, tensorflow, machine-learning, keras, deep-learning | 1,727,548,042 |
se_59563085 | stackoverflow | MACHINE_LEARNING | How to stop training when it hits a specific validation accuracy? | How to stop training when it hits a specific validation accuracy?
I am training a convolutional network and I want to stop training once the validation error hits 90%. I thought about using EarlyStopping and setting baseline to .90 but then it stops training whenever the validation accuracy is below that baseline for ... | https://stackoverflow.com/questions/59563085/how-to-stop-training-when-it-hits-a-specific-validation-accuracy | python, tensorflow, keras, deep-learning, conv-neural-network | 1,577,966,750 |
se_79185545 | stackoverflow | MACHINE_LEARNING | Multiclass classifier using Keras from 'Deep Learning with Python' yields very different accuracy compared to what's in the textbook | Multiclass classifier using Keras from 'Deep Learning with Python' yields very different accuracy compared to what's in the textbook
Below is the code for multi class classifier from Chapter 4 in 'Deep Learning with Python' by François Chollet. The textbook mentions this code will yield >95% training accur... | https://stackoverflow.com/questions/79185545/multiclass-classifier-using-keras-from-deep-learning-with-python-yields-very-d | python, tensorflow, machine-learning, keras, deep-learning | 1,731,511,190 |
se_79187633 | stackoverflow | MACHINE_LEARNING | How to modify the code of a method in a Python class at runtime | How to modify the code of a method in a Python class at runtime
I'm working on developing an acceleration framework for neural networks, using XLA to compile the computation graphs of models. However, since the code of the libraries used in models wasn't written by me, they often do not prioritize performance, which c... | https://stackoverflow.com/questions/79187633/how-to-modify-the-code-of-a-method-in-a-python-class-at-runtime | python, deep-learning | 1,731,566,533 |
se_78531347 | stackoverflow | MACHINE_LEARNING | How can I apply GridSearchCV where my data are images organised into folders? | How can I apply GridSearchCV where my data are images organised into folders?
I have a custom CNN being implemented and am now trying to apply GridSearch for hyperparater tuning. I've included parts of my script that may be helpful. Any help would be appreciated. I consider myself a beginner in python and deep learnin... | https://stackoverflow.com/questions/78531347/how-can-i-apply-gridsearchcv-where-my-data-are-images-organised-into-folders | deep-learning, conv-neural-network, hyperparameters, grid-search | 1,716,608,622 |
se_79032646 | stackoverflow | MACHINE_LEARNING | `TypeError: Unsupported integer size (0)` when attempted to save custom Keras model | `TypeError: Unsupported integer size (0)` when attempted to save custom Keras model
I have a subclassed tensorflow.keras.Model Seq2Seq model with custom layers. However when I try to save it via tensorflow.keras.Model.save() method, it throwing the following error:
File "/home/anaconda3/envs/aizynth-env/lib/python3.... | https://stackoverflow.com/questions/79032646/typeerror-unsupported-integer-size-0-when-attempted-to-save-custom-keras-mo | python, tensorflow, machine-learning, keras, deep-learning | 1,727,464,491 |
se_79182980 | stackoverflow | MACHINE_LEARNING | Numpy neural network not learning (stuck on 10% accuracy) - Python | Numpy neural network not learning (stuck on 10% accuracy) - Python
So I am trying to build a basic ANN using numpy. The thing is I keep getting an accuracy prediction of around 10% and I don't understand why that is. Here is all the code.
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
dat... | https://stackoverflow.com/questions/79182980/numpy-neural-network-not-learning-stuck-on-10-accuracy-python | python, numpy, deep-learning, neural-network | 1,731,452,842 |
se_78322502 | stackoverflow | MACHINE_LEARNING | Why does the .pt weight file size significantly decrease after training YOLOv8? | Why does the .pt weight file size significantly decrease after training YOLOv8?
After training a YOLOv8 model, I noticed that the size of the .pt weight file significantly decreased compared to its initial size. What techniques are utilized in YOLOv8 that result in this reduction of file size? Additionally, does this ... | https://stackoverflow.com/questions/78322502/why-does-the-pt-weight-file-size-significantly-decrease-after-training-yolov8 | deep-learning, yolov8, ultralytics | 1,713,060,892 |
se_78662784 | stackoverflow | MACHINE_LEARNING | Why does the Keras Embedding layer result in an "unbuilt" model in the summary? | Why does the Keras Embedding layer result in an "unbuilt" model in the summary?
In my model setup, despite specifying parameters for the Embedding layer, such as input dimension (input_dim), output dimension (output_dim), and input length (input_length), the summary output indicates that the Embedding layer ... | https://stackoverflow.com/questions/78662784/why-does-the-keras-embedding-layer-result-in-an-unbuilt-model-in-the-summary | keras, deep-learning, dataset | 1,719,235,645 |
se_79167574 | stackoverflow | MACHINE_LEARNING | Why are model_q4.onnx and model_q4f16.onnx not 4 times smaller than model.onnx? | Why are model_q4.onnx and model_q4f16.onnx not 4 times smaller than model.onnx?
I see on https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct/tree/main/onnx:
File Name
Size
model.onnx
654 MB
model_fp16.onnx
327 MB
model_q4.onnx
200 MB
model_q4f16.onnx
134 MB
I understand that:
model.onnx is the ... | https://stackoverflow.com/questions/79167574/why-are-model-q4-onnx-and-model-q4f16-onnx-not-4-times-smaller-than-model-onnx | deep-learning, large-language-model, huggingface, onnx, quantization | 1,731,001,957 |
se_61980349 | stackoverflow | MACHINE_LEARNING | tensorflow TypeError: cannot unpack non-iterable float object | tensorflow TypeError: cannot unpack non-iterable float object
I am using tensorflow V2.2 and run into TyepError when I do model.evaluate. Can someone advise what the issues may be? A screenshot of the execution and error message is shown below. | https://stackoverflow.com/questions/61980349/tensorflow-typeerror-cannot-unpack-non-iterable-float-object | python, tensorflow, machine-learning, keras, deep-learning | 1,590,281,430 |
se_79176888 | stackoverflow | MACHINE_LEARNING | Why do we divide by batch_size in the backward pass of Softmax with Cross-Entropy Loss? | Why do we divide by batch_size in the backward pass of Softmax with Cross-Entropy Loss?
In the implementation of the SoftmaxWithLoss layer, I noticed that the gradient in the backward pass is divided by batch_size. Here's the code for reference:
class SoftmaxWithLoss:
def __init__(self):
self.loss = None ... | https://stackoverflow.com/questions/79176888/why-do-we-divide-by-batch-size-in-the-backward-pass-of-softmax-with-cross-entrop | python, deep-learning, neural-network | 1,731,313,804 |
se_79172053 | stackoverflow | MACHINE_LEARNING | How to fix the error ValueError: Expected input batch_size (49) to match target batch_size (64) | How to fix the error ValueError: Expected input batch_size (49) to match target batch_size (64)
I keep modifying the dataloader side, but it still shows that error.
This is the preprocessing code:
import torch
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms
class ImageDataset(Data... | https://stackoverflow.com/questions/79172053/how-to-fix-the-error-valueerror-expected-input-batch-size-49-to-match-target | python, machine-learning, deep-learning, pytorch, neural-network | 1,731,122,683 |
se_40910857 | stackoverflow | MACHINE_LEARNING | How to interpret increase in both loss and accuracy | How to interpret increase in both loss and accuracy
I have run deep learning models(CNN's) using tensorflow. Many times during the epoch, i have observed that both loss and accuracy have increased, or both have decreased. My understanding was that both are always inversely related. What could be scenario where both in... | https://stackoverflow.com/questions/40910857/how-to-interpret-increase-in-both-loss-and-accuracy | tensorflow, deep-learning, loss | 1,480,595,724 |
se_38714959 | stackoverflow | MACHINE_LEARNING | Understanding Keras Long Short Term Memories (LSTMs) | Understanding Keras Long Short Term Memories (LSTMs)
While trying to reconcile my understanding of LSTMs pointed out here in this post by Christopher Olah implemented in Keras and following the blog written by Jason Brownlee for the Keras tutorial, I am confused about the following:
The reshaping of the data series i... | https://stackoverflow.com/questions/38714959/understanding-keras-long-short-term-memories-lstms | python, deep-learning, keras, lstm | 1,470,125,053 |
se_63825841 | stackoverflow | MACHINE_LEARNING | AttributeError : 'tuple' has no attribute 'to' | AttributeError : 'tuple' has no attribute 'to'
I am writing this Image Classifier and I have defined the loaders but getting this mistake and I have no clue about it.
I have defined the train loader, for a better explanation I tried this
for ina,lab in train_loader:
print(type(ina))
print(type(... | https://stackoverflow.com/questions/63825841/attributeerror-tuple-has-no-attribute-to | machine-learning, deep-learning, pytorch, kaggle | 1,599,726,872 |
se_79173890 | stackoverflow | MACHINE_LEARNING | Model Always Classifies Images as Cats with High Confidence Despite Hyperparameter Tuning | Model Always Classifies Images as Cats with High Confidence Despite Hyperparameter Tuning
I am trying to train a model on images using the code below. My directory structure is as follows:
The PetImages folder, which is approximately 1GB in size, is located next to my main.py script.
Inside the PetImages folder, ther... | https://stackoverflow.com/questions/79173890/model-always-classifies-images-as-cats-with-high-confidence-despite-hyperparamet | python, tensorflow, machine-learning, keras, deep-learning | 1,731,195,173 |
se_79168959 | stackoverflow | MACHINE_LEARNING | How to fix ValueError: Expected input batch_size (49) to match target batch_size (64) | How to fix ValueError: Expected input batch_size (49) to match target batch_size (64)
I'm keep modifying the dataloader side, but it still shows that error.
This is the preprocessing code:
import torch
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms
class ImageDataset(Dataset):
... | https://stackoverflow.com/questions/79168959/how-to-fix-valueerror-expected-input-batch-size-49-to-match-target-batch-size | python, machine-learning, deep-learning, pytorch, neural-network | 1,731,045,350 |
se_60881576 | stackoverflow | MACHINE_LEARNING | Understanding How YOLO is trained | Understanding How YOLO is trained
I'm trying to understand how YOLO (v2) is trained. To do so, I'm using this keras implementation https://github.com/experiencor/keras-yolo2 to train YOLO from scratch on VOC dataset (I'm open to other implementation, but I never worked with pytorch, so, keras implementation will be fi... | https://stackoverflow.com/questions/60881576/understanding-how-yolo-is-trained | machine-learning, keras, deep-learning, yolo | 1,585,294,029 |
se_50154019 | stackoverflow | MACHINE_LEARNING | Confused about Yolo | Confused about Yolo
I am a bit confused with how Yolo works.
In the paper, they say that:
The confidence prediction represents the IOU between the
predicted box and any ground truth box."
But how do we have the ground truth box? Let's say I use my Yolo network (already trained) on an image that is not labelled. What... | https://stackoverflow.com/questions/50154019/confused-about-yolo | deep-learning, object-recognition, yolo | 1,525,347,025 |
se_79167425 | stackoverflow | MACHINE_LEARNING | Deep RL problem: Loss decreases but agent doesn't learn | Deep RL problem: Loss decreases but agent doesn't learn
I hope somebody can help me. I'm implementing a basic Vanilla Policy Gradient algorithm for the CartPole-v1 gymnasium environment, and I don't know what I'm doing wrong.
No matter what I try, during the training loop the loss decreases (so the model is actual... | https://stackoverflow.com/questions/79167425/deep-rl-problem-loss-decreases-but-agent-doesnt-learn | python, deep-learning, reinforcement-learning, torch, policy-gradient-descent | 1,730,999,015 |
se_77477323 | stackoverflow | MACHINE_LEARNING | Hyperopt distributed parameter tuning with tensorflow datasets possible? | Hyperopt distributed parameter tuning with tensorflow datasets possible?
I’m trying to perform a slightly complex hyperparameter tuning operation in Databricks on a Tensorflow model (though the complexity comes from how many different tools we’re trying to make work together, not specifically anything about the model ... | https://stackoverflow.com/questions/77477323/hyperopt-distributed-parameter-tuning-with-tensorflow-datasets-possible | tensorflow, deep-learning, databricks, distributed-computing, hyperopt | 1,699,916,396 |
se_78071238 | stackoverflow | MACHINE_LEARNING | How to add feature extracted layer to a sequential model in Tensorflow? | How to add feature extracted layer to a sequential model in Tensorflow?
resnet_50 = "https://www.kaggle.com/models/tensorflow/resnet-50/frameworks/TensorFlow2/variations/classification/versions/1"
feature_extractor_model = resnet_50
import tensorflow_hub as hub
feature_extractor_layer = hub.KerasLayer(
feature_ext... | https://stackoverflow.com/questions/78071238/how-to-add-feature-extracted-layer-to-a-sequential-model-in-tensorflow | tensorflow, machine-learning, keras, deep-learning | 1,709,078,161 |
se_72313812 | stackoverflow | MACHINE_LEARNING | Tried to export a function which references 'untracked' resource Tensor("272554:0", shape=(), dtype=resource) | Tried to export a function which references 'untracked' resource Tensor("272554:0", shape=(), dtype=resource)
I'm currently using CoAtNet0 for this project, and I can't seem to save the model. Hope someone can guide me how to fix the error or is there another way to save the model? The error for the ... | https://stackoverflow.com/questions/72313812/tried-to-export-a-function-which-references-untracked-resource-tensor272554 | python, machine-learning, deep-learning, transformer-model, transfer-learning | 1,653,023,228 |
se_58249160 | stackoverflow | MACHINE_LEARNING | How to implement contractive autoencoder in Pytorch? | How to implement contractive autoencoder in Pytorch?
I'm trying to create a contractive autoencoder in Pytorch. I found this thread and tried according to that. This is the snippet I wrote based on the mentioned thread:
import datetime
import numpy as np
import torch
import torchvision
from torchvision import dataset... | https://stackoverflow.com/questions/58249160/how-to-implement-contractive-autoencoder-in-pytorch | python, deep-learning, pytorch, autoencoder, autograd | 1,570,284,909 |
se_78380728 | stackoverflow | MACHINE_LEARNING | Low Accuracy and High loss while training a neural network model | Low Accuracy and High loss while training a neural network model
I am working on an admission prediction system which uses ANN. I am having high loss while training my model. Below is the necessary information related to the dataset and model.
Dataset:
for col in data.columns:
print(col,":",len(data[col].unique()), 'l... | https://stackoverflow.com/questions/78380728/low-accuracy-and-high-loss-while-training-a-neural-network-model | tensorflow, keras, deep-learning, loss-function, multilabel-classification | 1,713,985,828 |
se_79162161 | stackoverflow | MACHINE_LEARNING | How to get a summary of a PyTorch model that uses dictionary as an input | How to get a summary of a PyTorch model that uses dictionary as an input
My model takes a dictionary as input, e.g. x = {'image': torch.tensor, 'number': torch.tensor}, the model looks like this:
class MyModel(nn.Module):
def __init__(self):
super(MyModel, self).__init__()
self.imgmodule = ImgModul... | https://stackoverflow.com/questions/79162161/how-to-get-a-summary-of-a-pytorch-model-that-uses-dictionary-as-an-input | python, machine-learning, deep-learning, pytorch | 1,730,888,523 |
se_58604120 | stackoverflow | MACHINE_LEARNING | How to convert FlatBuffer message from binary to human readable text format with Python? | How to convert FlatBuffer message from binary to human readable text format with Python?
I am writing a tool to dump our dedicated ML model from flatbuffers binary into human readable text format, is there any helper like text_format for protobuf? | https://stackoverflow.com/questions/58604120/how-to-convert-flatbuffer-message-from-binary-to-human-readable-text-format-with | python, deep-learning, flatbuffers | 1,572,339,600 |
se_72090770 | stackoverflow | MACHINE_LEARNING | Transfer an LSTM model from cpu to GPU | Transfer an LSTM model from cpu to GPU
I have a very simple LSTM model which I've built in tensorflow and it works on CPU. However, I want to use this model on GPU. For the pytorch, I've defined the device and etc, however for tensorflow, I don't have any idea why it can not work. Do you have any suggestion for me? Th... | https://stackoverflow.com/questions/72090770/transfer-an-lstm-model-from-cpu-to-gpu | python, tensorflow, deep-learning, gpu, lstm | 1,651,515,516 |
se_69458634 | stackoverflow | MACHINE_LEARNING | Error: "bitwise_and_cpu" not implemented for 'Float' | Error: "bitwise_and_cpu" not implemented for 'Float'
I am looking to generate Intersection over Union (IoU) score for ResNet50 (pretrained) model. Here is my function to calculate IoU score:
def IoU(predict: torch.Tensor, target: torch.Tensor):
i = (predict & target).double().sum()
u = (predict | ta... | https://stackoverflow.com/questions/69458634/error-bitwise-and-cpu-not-implemented-for-float | python, image-processing, deep-learning, pytorch, image-segmentation | 1,633,480,656 |
se_78843004 | stackoverflow | MACHINE_LEARNING | ModuleNotFoundError: No module named 'datachain.lib'; 'datachain' is not a package | ModuleNotFoundError: No module named 'datachain.lib'; 'datachain' is not a package
Why am I encountering the ModuleNotFoundError for the datachain.lib module?
Are there any additional steps I need to take to properly use the datachain package in my project?
I'm working on a Python project and I encoun... | https://stackoverflow.com/questions/78843004/modulenotfounderror-no-module-named-datachain-lib-datachain-is-not-a-packa | python, machine-learning, deep-learning, data-preprocessing | 1,723,024,387 |
se_79157138 | stackoverflow | MACHINE_LEARNING | What's the problems in my custom layernorm function? | What's the problems in my custom layernorm function?
import numpy as np
import torch
import torch.nn.functional as F
def layer_norm(x, weight, bias, eps=1e-6):
# x shape: [bs, h, w, c]
# Calculate mean and variance across the spatial dimensions (height, width)
mean = np.mean(x, axis=(1, 2), keepdims=T... | https://stackoverflow.com/questions/79157138/whats-the-problems-in-my-custom-layernorm-function | machine-learning, math, deep-learning, pytorch, computer-vision | 1,730,758,044 |
se_57457817 | stackoverflow | MACHINE_LEARNING | Adding batch normalization decreases the performance | Adding batch normalization decreases the performance
I'm using PyTorch to implement a classification network for skeleton-based action recognition. The model consists of three convolutional layers and two fully connected layers. This base model gave me an accuracy of around 70% in the NTU-RGB+D dataset. I wanted to le... | https://stackoverflow.com/questions/57457817/adding-batch-normalization-decreases-the-performance | python, deep-learning, pytorch, batch-normalization | 1,565,598,386 |
se_79141566 | stackoverflow | MACHINE_LEARNING | DQN performance swinging | DQN performance swinging
I'm using DDQN with experience replay just like in this tutorial https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html
except that I'm making the problem a little harder by obscuring x_dot and theta_t(cart velocity and angular velocity of the pole). I then calculate, conside... | https://stackoverflow.com/questions/79141566/dqn-performance-swinging | machine-learning, deep-learning, reinforcement-learning, q-learning, dqn | 1,730,298,988 |
se_79143377 | stackoverflow | MACHINE_LEARNING | How to load a Keras model without importing Keras in a Python desktop app? | How to load a Keras model without importing Keras in a Python desktop app?
I have a trained Keras model saved as model.h5, which I would normally load using keras.models.load_model("model.h5"). I'm currently developing a Python desktop application with a GUI and need to package it as a standalone .exe file.
The proble... | https://stackoverflow.com/questions/79143377/how-to-load-a-keras-model-without-importing-keras-in-a-python-desktop-app | python, tensorflow, machine-learning, keras, deep-learning | 1,730,344,074 |
se_78517505 | stackoverflow | MACHINE_LEARNING | Why is my model (using GATv2conv) stuck on its loss? (Predicting same value for every node) | Why is my model (using GATv2conv) stuck on its loss? (Predicting same value for every node)
I am trying to create a Geometric Deep Learning model using Pytorch. I have around 5000 graphs, which are split into a training set, validation set and test set. Every graph has one 'correct' node and is fully connected. There ... | https://stackoverflow.com/questions/78517505/why-is-my-model-using-gatv2conv-stuck-on-its-loss-predicting-same-value-for | python, deep-learning, pytorch, pytorch-geometric | 1,716,380,464 |
se_79147000 | stackoverflow | MACHINE_LEARNING | Classifying Table Headers from Column Data | Classifying Table Headers from Column Data
I have a large set CSVs with numeric and text data; here's a sample:
Company ID
Company Name
Group ID
Currency
Amount
...
8494494
Acme Inc
F942G
EUR
$1.56
...
9283422A
Walmart
XXH3F3
AUD
$5.64
...
...
...
...
...
...
...
I have a separate set of CSVs for which t... | https://stackoverflow.com/questions/79147000/classifying-table-headers-from-column-data | machine-learning, deep-learning, classification, prediction, word-embedding | 1,730,437,786 |
se_79140091 | stackoverflow | MACHINE_LEARNING | Inference error after training an IP-Adapter plus model | Inference error after training an IP-Adapter plus model
I downloaded packages from https://github.com/tencent-ailab/IP-Adapter
run the commands to train an IP-Adapter plus model (input: text + image, output: image):
accelerate launch --num_processes 2 --multi_gpu --mixed_precision "fp16" \
tutorial_train_plus.py \
... | https://stackoverflow.com/questions/79140091/inference-error-after-training-an-ip-adapter-plus-model | machine-learning, deep-learning, pytorch, transformer-model, stable-diffusion | 1,730,273,542 |
se_79146746 | stackoverflow | MACHINE_LEARNING | Clarifying batch size when using multiple GPU's | Clarifying batch size when using multiple GPU's
After observing this video enter link description here (timestap 00:25s - 1:20s only needed), I want to confirm the batch size that must be passed to the dataloader.
The video states the "effective batch size" = batch size * no gpus * no nodes. I want to confirm whet... | https://stackoverflow.com/questions/79146746/clarifying-batch-size-when-using-multiple-gpus | deep-learning, pytorch-lightning | 1,730,426,050 |
se_76865316 | stackoverflow | MACHINE_LEARNING | Real time object detection with Yolo model not working | Real time object detection with Yolo model not working
I have trained a custom yolo model to detect square slots on a board, and is working with more than 95 % accuracy on images.
But as soon as I switch to video detection it seems to not detect even a single thing
I am using the following code to run real time object... | https://stackoverflow.com/questions/76865316/real-time-object-detection-with-yolo-model-not-working | python, deep-learning, pytorch, conv-neural-network, yolo | 1,691,564,297 |
se_78134496 | stackoverflow | MACHINE_LEARNING | How do I turn a dataset with a matlab annotation file into a functioning image detection model compatible with YOLO in Python? | How do I turn a dataset with a matlab annotation file into a functioning image detection model compatible with YOLO in Python?
I am trying to create a parking assistance program that will use machine vision to map out which parking spots in a parking lot are open. To do this, I am using the YOLOv8 default image detect... | https://stackoverflow.com/questions/78134496/how-do-i-turn-a-dataset-with-a-matlab-annotation-file-into-a-functioning-image-d | python, deep-learning, computer-vision, object-detection, yolo | 1,710,036,050 |
se_79144629 | stackoverflow | MACHINE_LEARNING | Why to use combined loss function for segmentation and classification | Why to use combined loss function for segmentation and classification
I tried to modify the U-NET model for one-dimensional data by providing an additional branch, attached to the last encoding block, whose purpose is to classify data into eighteen areas of the cortex. (inspiration based on this paper: https://arxiv.o... | https://stackoverflow.com/questions/79144629/why-to-use-combined-loss-function-for-segmentation-and-classification | python-3.x, deep-learning, tf.keras, loss-function | 1,730,376,027 |
se_57605094 | stackoverflow | MACHINE_LEARNING | The training loss of vgg16 implemented in pytorch does not decrease | The training loss of vgg16 implemented in pytorch does not decrease
I want to try some toy examples in pytorch, but the training loss does not decrease in the training.
Some info is provided here:
The model is vgg16, consisted of 13 conv layers and 3 dense layers.
The data is cifar100 in pytorch.
I choose cross entro... | https://stackoverflow.com/questions/57605094/the-training-loss-of-vgg16-implemented-in-pytorch-does-not-decrease | machine-learning, deep-learning, pytorch, vgg-net | 1,566,462,473 |
se_43565003 | stackoverflow | MACHINE_LEARNING | State-of-art for sensor's anomaly detection | State-of-art for sensor's anomaly detection
I am working on anomaly detection problem. I have a sensor that records episodic time series data. For example, once in a while, the sensor activates for 10 seconds and records values at millisecond interval. My task is to identify whether the recorded pattern is not nor... | https://stackoverflow.com/questions/43565003/state-of-art-for-sensors-anomaly-detection | machine-learning, time-series, deep-learning, anomaly-detection | 1,492,897,692 |
se_43329935 | stackoverflow | MACHINE_LEARNING | Tensorflow returns same predictions | Tensorflow returns same predictions
I'm trying to make my first tensorflow model, however I have some issues. It seems that it makes the train correctly, but when it does a prediction it just returns (almost) always the same value. Here's the code:
n_classes = 2
tf.reset_default_graph()
x = tf.placeholder('float')
y... | https://stackoverflow.com/questions/43329935/tensorflow-returns-same-predictions | python, tensorflow, neural-network, deep-learning | 1,491,847,285 |
se_59116831 | stackoverflow | MACHINE_LEARNING | How can I do to evaluate mean and std for a dataset? | How can I do to evaluate mean and std for a dataset?
I am using pytorch and the dataset fashion MNIST but I do not know how can I do to evaluate the mean and the std for this dataset. Here is my code :
import torch
from torchvision import datasets, transforms
import torch.nn.functional as F
transform = transforms... | https://stackoverflow.com/questions/59116831/how-can-i-do-to-evaluate-mean-and-std-for-a-dataset | python, python-3.x, deep-learning, artificial-intelligence, pytorch | 1,575,122,067 |
se_77544604 | stackoverflow | MACHINE_LEARNING | Importing deepspeech error: Module not found | Importing deepspeech error: Module not found
I am trying to install DeepSearch library so that I can use the pretrained model to build the Speech to Text Project.
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-8-a1bcd52700aa> in <cell line: 1>()
----> 1 import deepspeech
... | https://stackoverflow.com/questions/77544604/importing-deepspeech-error-module-not-found | python, deep-learning, nlp, mozilla-deepspeech | 1,700,844,483 |
se_79142711 | stackoverflow | MACHINE_LEARNING | pytorch quantized linear function gives shape invalid error | pytorch quantized linear function gives shape invalid error
I am trying to implement write a simple quantized tensor linear multiplication. Assuming the weight matrix w3 of shape (14336, 4096) and the input tensor x of shape (2, 512, 4096) where first dim is batch size. When using normal linear function it works fine ... | https://stackoverflow.com/questions/79142711/pytorch-quantized-linear-function-gives-shape-invalid-error | deep-learning, pytorch, matrix-multiplication, transformer-model, quantization | 1,730,320,339 |
se_75268393 | stackoverflow | MACHINE_LEARNING | YOLOV8 how does it handle different image sizes | YOLOV8 how does it handle different image sizes
Yolov8 and I suspect Yolov5 handle non-square images well. I cannot see any evidence of cropping the input image, i.e. detections seem to go to the enge of the longest side. Does it resize to a square 640x604 which would change the aspect ratio of objects making them mor... | https://stackoverflow.com/questions/75268393/yolov8-how-does-it-handle-different-image-sizes | python, deep-learning, conv-neural-network, yolo | 1,674,916,423 |
se_63754645 | stackoverflow | MACHINE_LEARNING | Convert Conv2d to Linear | Convert Conv2d to Linear
I have a PyTorch Conv2d layer:
Conv2d(96, 1000, kernel_size=torch.Size([10, 10]), stride=(1, 1))
I know that a Conv2d layer is a special case of a Linear layer. How can I convert a Conv2d layer to Linear layer in PyTorch? | https://stackoverflow.com/questions/63754645/convert-conv2d-to-linear | deep-learning, pytorch | 1,599,313,830 |
se_67202194 | stackoverflow | MACHINE_LEARNING | ValueError: Layer expects 2 input(s), but it received 1 input tensors when training a CNN | ValueError: Layer expects 2 input(s), but it received 1 input tensors when training a CNN
I am trying to build a Siamese CNN similar to what's done in this guide.
My model is built using a base model, which is then fed twice with two different pictures that go through the same network.
This is the code for building th... | https://stackoverflow.com/questions/67202194/valueerror-layer-expects-2-inputs-but-it-received-1-input-tensors-when-train | python, tensorflow, keras, deep-learning, conv-neural-network | 1,619,032,670 |
se_73828831 | stackoverflow | MACHINE_LEARNING | Layer "3dcnn" expects 1 input(s), but it received 16 > input tensors | Layer "3dcnn" expects 1 input(s), but it received 16 > input tensors
I have programmed a custom data generator in Keras because I was running out of memory and I need to load x by x samples for training because I am using nifty images with a big size. I tried several solutions of this forum, but as they a... | https://stackoverflow.com/questions/73828831/layer-3dcnn-expects-1-inputs-but-it-received-16-input-tensors | tensorflow, keras, deep-learning | 1,663,941,265 |
se_79137676 | stackoverflow | MACHINE_LEARNING | How to Control Memory Growth When Using TensorFlow in Multi-Round Training? | How to Control Memory Growth When Using TensorFlow in Multi-Round Training?
I'm facing an issue related to memory growth when using TensorFlow for a multi-round training process. Specifically, I have a model training loop in which I generate training and evaluation data in each round, and my memory usage seems to keep... | https://stackoverflow.com/questions/79137676/how-to-control-memory-growth-when-using-tensorflow-in-multi-round-training | tensorflow, machine-learning, deep-learning | 1,730,212,573 |
se_78271449 | stackoverflow | MACHINE_LEARNING | Model-based reinforcement learning code training is too slow, only 3 epochs (3000 steps) in 12 hours | Model-based reinforcement learning code training is too slow, only 3 epochs (3000 steps) in 12 hours
I am a researcher of model-based reinforcement learning. I added the Normalizing flow model to my code to obtain better simulation samples through the flow. I integrated and debugged the two parts for a long time. Now ... | https://stackoverflow.com/questions/78271449/model-based-reinforcement-learning-code-training-is-too-slow-only-3-epochs-300 | performance, deep-learning, pytorch, model, artificial-intelligence | 1,712,200,046 |
se_60268647 | stackoverflow | MACHINE_LEARNING | Merged 1D-CNN and 2D-CNN | Merged 1D-CNN and 2D-CNN
I want to build a merged CNN model using 1D and 2D CNN but i tried many ways to build it but this one worked with me but i don't know why i get this error when using model_combined.summary().
I have attached two images which contain the summary of 1D & 2D CNN summary of 1D CNN ,
summary of 2D... | https://stackoverflow.com/questions/60268647/merged-1d-cnn-and-2d-cnn | python, tensorflow, keras, deep-learning, conv-neural-network | 1,581,964,986 |
se_78875648 | stackoverflow | MACHINE_LEARNING | Transfer Learning Pretrained Model | Transfer Learning Pretrained Model
I'm fitting transfer learning models on Google Colab. However, I've encountered a warning message with the code
Epoch 1/30
/usr/local/lib/python3.10/dist-packages/keras/src/trainers/data_adapters/py_dataset_adapter.py:121:
UserWarning: Your `PyDataset` class should call `super().__i... | https://stackoverflow.com/questions/78875648/transfer-learning-pretrained-model | python, machine-learning, keras, deep-learning, artificial-intelligence | 1,723,733,385 |
se_62262241 | stackoverflow | MACHINE_LEARNING | resnet50.to() function on a non-NVIDIA GPU | resnet50.to() function on a non-NVIDIA GPU
I am trying to convert the pretrained ResNet50 model to be used on GPU using the Pytorch function resnet50.to().
The problem is that I am using an Intel Iris Plus Graphics 655 1536 MB GPU on Mac, and I don't know what argument to pass to the function as I only found the one ... | https://stackoverflow.com/questions/62262241/resnet50-to-function-on-a-non-nvidia-gpu | python, deep-learning, pytorch, gpu, resnet | 1,591,619,846 |
se_61776353 | stackoverflow | MACHINE_LEARNING | Correlations of feature columns in TensorFlow | Correlations of feature columns in TensorFlow
I've recently started exploring features columns by TensorFlow.
If I understood documentation right, feature columns are just a 'frame' for further transformations just before fitting data to the model. So, if I want to use it, I define some feature columns, create DenseFe... | https://stackoverflow.com/questions/61776353/correlations-of-feature-columns-in-tensorflow | tensorflow, deep-learning, tensorflow2.0 | 1,589,377,609 |
se_79084869 | stackoverflow | MACHINE_LEARNING | summary() function not working in cnn (ValueError: Undefined shapes are not supported.) | summary() function not working in cnn (ValueError: Undefined shapes are not supported.)
I'm trying to make a classification network for IDing pictures from the cifar10 dataset.
When I try to use the summary() function, I keep getting this error.
ValueError Traceback (most recent call las... | https://stackoverflow.com/questions/79084869/summary-function-not-working-in-cnn-valueerror-undefined-shapes-are-not-supp | tensorflow, machine-learning, keras, deep-learning, vgg-net | 1,728,885,022 |
se_49011306 | stackoverflow | MACHINE_LEARNING | Developing Deep Learning image recognition system using Pre-trained models | Developing Deep Learning image recognition system using Pre-trained models
I want to use Pre-trained models such as Xception, VGG16, ResNet50, etc for my Deep Learning image recognition project to quick train the model on the training set with high accuracy. I am having trouble to find an exact code to implement my mo... | https://stackoverflow.com/questions/49011306/developing-deep-learning-image-recognition-system-using-pre-trained-models | python, tensorflow, machine-learning, deep-learning, keras | 1,519,742,538 |
se_65212386 | stackoverflow | MACHINE_LEARNING | Can you plot the accuracy graph of a pre-trained model? | Can you plot the accuracy graph of a pre-trained model?
I finished training a model that took 8 hours to run, but I forgot to plot the accuracy graph before closing the jupyter notebook.
I need to plot the graph, and I did save the model to my hard-disk. But how do I plot the accuracy graph of a pre-trained model? I s... | https://stackoverflow.com/questions/65212386/can-you-plot-the-accuracy-graph-of-a-pre-trained-model | python, tensorflow, matplotlib, machine-learning, deep-learning | 1,607,499,040 |
se_68707680 | stackoverflow | MACHINE_LEARNING | How to automatically judge whether the training process of the deep learning model is converged? | How to automatically judge whether the training process of the deep learning model is converged?
When training a deep learning model, I have to look at the loss curve and performance curve to judge whether the training process of the deep learning model is converged.
This has cost me a lot of time. Sometimes, the time... | https://stackoverflow.com/questions/68707680/how-to-automatically-judge-whether-the-training-process-of-the-deep-learning-mod | machine-learning, deep-learning | 1,628,490,479 |
se_62922324 | stackoverflow | MACHINE_LEARNING | Is it possible to use non-pytoch augmentation in transform.compose | Is it possible to use non-pytoch augmentation in transform.compose
I am working on a data classification problem that takes images as an input in Pytorch. I would like the use the imgaug library, but unfortunatly I keep on getting errors. Here is my code.
#import necessary libraries
from torch import nn
from torchvisi... | https://stackoverflow.com/questions/62922324/is-it-possible-to-use-non-pytoch-augmentation-in-transform-compose | python, deep-learning, pytorch, artificial-intelligence, data-augmentation | 1,594,840,766 |
se_79097169 | stackoverflow | MACHINE_LEARNING | OpenCV with OpenVINO Backend: Problem Whit Dynamic Batch Size | OpenCV with OpenVINO Backend: Problem Whit Dynamic Batch Size
I am using OpenCV (version 4.10.0) compiled with the OpenVINO (2023.0.1) backend to load and process a deep learning model. I have successfully converted a model from the Open Model Zoo to the OpenVINO IR format using both ovc and omz_downloader. The conver... | https://stackoverflow.com/questions/79097169/opencv-with-openvino-backend-problem-whit-dynamic-batch-size | c++, opencv, machine-learning, deep-learning, openvino | 1,729,153,354 |
se_77047181 | stackoverflow | MACHINE_LEARNING | JoypadSpace.reset() modification to solve "unexpected keyword argument 'seed'" leads to error: "too many values to unpack (expected 2)" | JoypadSpace.reset() modification to solve "unexpected keyword argument 'seed'" leads to error: "too many values to unpack (expected 2)"
I'm getting the same error as described here: TypeError: JoypadSpace.reset() got an unexpected keyword argument 'seed', when I run the following code, what... | https://stackoverflow.com/questions/77047181/joypadspace-reset-modification-to-solve-unexpected-keyword-argument-seed-l | deep-learning, openai-gym, joypad | 1,693,941,213 |
se_78596363 | stackoverflow | MACHINE_LEARNING | Running Teachable Machines Object Recognizer in PyCharm | Running Teachable Machines Object Recognizer in PyCharm
I am trying to use the Teachable Machines object recognizer from a script in PyCharm, but I keep getting an error. The purpose of this code is to take in an image, and then print what the object is with a confidence score, based on the model. I have downloaded th... | https://stackoverflow.com/questions/78596363/running-teachable-machines-object-recognizer-in-pycharm | python, machine-learning, keras, deep-learning, teachable-machine | 1,717,865,496 |
se_77328225 | stackoverflow | MACHINE_LEARNING | How to do super resolution image with onnx and opencv using c++? | How to do super resolution image with onnx and opencv using c++?
I have animesr.onnx for my super resolution ios/macos app so I need to convert my python codes to c++ codes. These is my python codes:
session = onnxruntime.InferenceSession('animesr.onnx')
img = cv2.imread('imgs/naruto.jpg')
ori_h, ori_w, _ = img.shape... | https://stackoverflow.com/questions/77328225/how-to-do-super-resolution-image-with-onnx-and-opencv-using-c | python, c++, opencv, machine-learning, deep-learning | 1,697,773,707 |
se_52731782 | stackoverflow | MACHINE_LEARNING | Get CUDA_HOME environment path PYTORCH | Get CUDA_HOME environment path PYTORCH
I have cuda installed via anaconda on my system which has 2 GPUs which is getting recognized by my python.
import torch
torch.cuda.is_available()
true
However when I try to run a model via its C API, I m getting following error:
~/anaconda3/lib/python3.6/site-packages/torch/... | https://stackoverflow.com/questions/52731782/get-cuda-home-environment-path-pytorch | python, deep-learning, anaconda, pytorch | 1,539,138,775 |
se_79116509 | stackoverflow | MACHINE_LEARNING | The training results of LeNet remain unchanged | The training results of LeNet remain unchanged
Problem
I wrote a program to train LeNet. However, the training results (train_l, train_acc and test_acc) remain unchanged. I've checked codes and I think they should be right. I don't know what's the problem and how to deal with it.
Code
import torch
import torchvision
f... | https://stackoverflow.com/questions/79116509/the-training-results-of-lenet-remain-unchanged | machine-learning, deep-learning, pytorch | 1,729,662,055 |
se_79115748 | stackoverflow | MACHINE_LEARNING | RuntimeError - Expected All Tensors on the Same Device (CUDA and CPU) | RuntimeError - Expected All Tensors on the Same Device (CUDA and CPU)
I am working on a script that runs an offsite prompt tuning model using a pre-trained Vicuna-7b model on GPU (CUDA). However, when I attempt to execute the code, I encounter the above error. It seems the tensors are not all being transferred to the ... | https://stackoverflow.com/questions/79115748/runtimeerror-expected-all-tensors-on-the-same-device-cuda-and-cpu | python, deep-learning, pytorch, runtime-error, large-language-model | 1,729,631,627 |
se_79111832 | stackoverflow | MACHINE_LEARNING | what does observation space mean in custom gym enviroment? | what does observation space mean in custom gym enviroment?
error -
AssertionError: The obs returned by the step()method length is not same as the observation space length, obs length: 1875, space length: 2
init function :-
def __init__(self,pcl,fcl,plb,ts):
...
self.observation_space = spaces.Tuple((... | https://stackoverflow.com/questions/79111832/what-does-observation-space-mean-in-custom-gym-enviroment | deep-learning, virtual, reinforcement-learning, dqn, gymnasium | 1,729,546,600 |
se_65498782 | stackoverflow | MACHINE_LEARNING | How to dump confusion matrix using TensorBoard logger in pytorch-lightning? | How to dump confusion matrix using TensorBoard logger in pytorch-lightning?
The official doc only states
>>> from pytorch_lightning.metrics import ConfusionMatrix
>>> target = torch.tensor([1, 1, 0, 0])
>>> preds = torch.tensor([0, 1, 0, 0])
>>> confmat = ConfusionMatrix(num_classes=2)
>>> confmat(preds, target)
This... | https://stackoverflow.com/questions/65498782/how-to-dump-confusion-matrix-using-tensorboard-logger-in-pytorch-lightning | python, deep-learning, pytorch, tensorboard, pytorch-lightning | 1,609,275,997 |
se_75886125 | stackoverflow | MACHINE_LEARNING | How should I use torch.compile properly? | How should I use torch.compile properly?
I'm currently trying to use pytorch 2.0 for boosting training performance with my project. And I've heard that torch.compile might be boost some models.
So my question (for now) is simple; how should I use torch.compile with large model?
Such as, should I use torch.model like t... | https://stackoverflow.com/questions/75886125/how-should-i-use-torch-compile-properly | python, machine-learning, optimization, deep-learning, pytorch | 1,680,166,747 |
se_79105307 | stackoverflow | MACHINE_LEARNING | Zero out loss for a certain pixel class in BCELossWithLogits | Zero out loss for a certain pixel class in BCELossWithLogits
I am performing binary semantic segmentation on a dataset of pets (dogs and cats) each pixel has a class. There are 3 classes, foreground(1.0), background(0.0) and unclassified pixels(0.5020). I only interested in how good the model predicts foreground and b... | https://stackoverflow.com/questions/79105307/zero-out-loss-for-a-certain-pixel-class-in-bcelosswithlogits | machine-learning, deep-learning, loss-function | 1,729,352,097 |
se_79102723 | stackoverflow | MACHINE_LEARNING | Using multiprocessing for training in pytorch | Using multiprocessing for training in pytorch
I want to try to finetine a model with images of arbitrary sizes.
Not so hard to write somthing like
...
y_pred = torch.cat([model(im) for im in imgs])
loss = loss_fn(y_pred, y)
...
but even simple model(batch) kinda cpu-bound, so this is even slower.
I tried somthing li... | https://stackoverflow.com/questions/79102723/using-multiprocessing-for-training-in-pytorch | python, deep-learning, pytorch, python-multiprocessing, dataparallel | 1,729,265,441 |
se_76797190 | stackoverflow | MACHINE_LEARNING | How to choose which internal precision of float32 matrix multiplications to use? | How to choose which internal precision of float32 matrix multiplications to use?
PyTorch 1.12 changed the default fp32 math to be "highest precision", and introduced the torch.set_float32_matmul_precision API, allowing users to specify which precision out of medium, high and highest to use for the internal precision o... | https://stackoverflow.com/questions/76797190/how-to-choose-which-internal-precision-of-float32-matrix-multiplications-to-use | deep-learning, pytorch, floating-point, gpu | 1,690,709,998 |
se_60039938 | stackoverflow | MACHINE_LEARNING | Where can I get Passport images dataset that contain passport of almost all countries in the world? | Where can I get Passport images dataset that contain passport of almost all countries in the world?
I am training an OCR model for recognizing MRZ from passport. To train my model for more accuracy, I need to train it with maximum pictures possible. I tried to find passport's dataset on KAGGLE but could not find it.
... | https://stackoverflow.com/questions/60039938/where-can-i-get-passport-images-dataset-that-contain-passport-of-almost-all-coun | machine-learning, deep-learning, computer-vision, dataset, ocr | 1,580,735,468 |
se_79097867 | stackoverflow | MACHINE_LEARNING | How to do backpropagation in PyTorch when training AlphaZero? | How to do backpropagation in PyTorch when training AlphaZero?
I'm trying to implement my version of AlphaZero for Connect Four. I have implemented a convolutional network using PyTorch and can get (random) value- and policy outputs from the model for given boardstates. Now I would like to simulate some games and train... | https://stackoverflow.com/questions/79097867/how-to-do-backpropagation-in-pytorch-when-training-alphazero | python, deep-learning, pytorch, reinforcement-learning, backpropagation | 1,729,164,675 |
se_79058487 | stackoverflow | MACHINE_LEARNING | Key Error when trying to extract layer activation in TensorFlow sequential model | Key Error when trying to extract layer activation in TensorFlow sequential model
I have a Sequential model that is trained on the MNIST dataset.
After training, I am trying to create a new model to output activations from the hidden ReLU (Dense) layer.
I reshaped the test image correctly but get an error when calling ... | https://stackoverflow.com/questions/79058487/key-error-when-trying-to-extract-layer-activation-in-tensorflow-sequential-model | tensorflow, keras, deep-learning, neural-network | 1,728,196,215 |
se_62427719 | stackoverflow | MACHINE_LEARNING | Decrease the maximum learning rate after every restart | Decrease the maximum learning rate after every restart
I'm training a neural network for a computer vision-based task. For the optimizer, I found out that it isn't ideal to use a single learning rate for the entire training, and what people do is that they use learning rate schedulers to decay the learning rate in a s... | https://stackoverflow.com/questions/62427719/decrease-the-maximum-learning-rate-after-every-restart | python, deep-learning, pytorch, gradient-descent, sgd | 1,592,392,685 |
se_58352326 | stackoverflow | MACHINE_LEARNING | Running the Tensorflow 2.0 code gives 'ValueError: tf.function-decorated function tried to create variables on non-first call'. What am I doing wrong? | Running the Tensorflow 2.0 code gives 'ValueError: tf.function-decorated function tried to create variables on non-first call'. What am I doing wrong?
error_giving_notebook
non_problematic_notebook
As it can be seen that I have used tf.function decorator in the 'error_giving_notebook' and it throws a ValueEr... | https://stackoverflow.com/questions/58352326/running-the-tensorflow-2-0-code-gives-valueerror-tf-function-decorated-functio | keras, deep-learning, keras-layer, tensorflow2.0, tf.keras | 1,570,869,147 |
se_73102927 | stackoverflow | MACHINE_LEARNING | Do I need to define metrics in model.compile in order to use them later? | Do I need to define metrics in model.compile in order to use them later?
I am trying to train a model and after it is train, I want to see TP TN FP FN, recall, precision, and Sensitivity.
Question 1: Do I need to define all these metrics when I compile the model like this?
metrics = [CategoricalAccuracy(),Precision(),... | https://stackoverflow.com/questions/73102927/do-i-need-to-define-metrics-in-model-compile-in-order-to-use-them-later | python, tensorflow, deep-learning | 1,658,707,349 |
se_54783521 | stackoverflow | MACHINE_LEARNING | Uber Ludwig Toolbox: export generated model to Google platform ML Engine | Uber Ludwig Toolbox: export generated model to Google platform ML Engine
In Uber Ludwig toolbox the training from the scratch produced the following 10 files:
checkpoint
model_hyperparameters.json
model_weights.data-00000-of-00001
model_weights.index
model_weights.meta
model_weights_progress.data-00000-of-00001
mode... | https://stackoverflow.com/questions/54783521/uber-ludwig-toolbox-export-generated-model-to-google-platform-ml-engine | tensorflow, deep-learning, model, ludwig | 1,550,656,728 |
se_79095135 | stackoverflow | MACHINE_LEARNING | How can I optimize a SLURM script to use more GPUs for large pre-trained networks and a model using PyTorch? | How can I optimize a SLURM script to use more GPUs for large pre-trained networks and a model using PyTorch?
Our school has a HPC with multiple GPUs and I am trying to figure out how to utilize more of them to run my code faster however I keep running into this error at batch size 128:
Traceback (most recent call last... | https://stackoverflow.com/questions/79095135/how-can-i-optimize-a-slurm-script-to-use-more-gpus-for-large-pre-trained-network | deep-learning, pytorch, neural-network, gpu, slurm | 1,729,098,794 |
se_78436209 | stackoverflow | MACHINE_LEARNING | YOLOv8 plotting labels issue, satellite imagery data | YOLOv8 plotting labels issue, satellite imagery data
I have an issue with the YOLOv8 training output (from ultralytics), specifically the drawing of the labels (not the predictions). I do have a dataset of satellite imagery, where there is (segmentation) polygons on building roof and we want the model to predict the s... | https://stackoverflow.com/questions/78436209/yolov8-plotting-labels-issue-satellite-imagery-data | deep-learning, image-segmentation, yolo, yolov8 | 1,714,993,840 |
se_77758605 | stackoverflow | MACHINE_LEARNING | Get full text from a LayoutLM | Get full text from a LayoutLM
I am using LayoutLM to read receipts and get text from the invoices. I am using this model from HuggingFace "philschmid/lilt-en-funsd". Given below is the code snippet:
def run_inference(image_path, model=model, processor=processor, output_image=True):
# Load image from the path
i... | https://stackoverflow.com/questions/77758605/get-full-text-from-a-layoutlm | python, deep-learning, ocr, huggingface-transformers, text-extraction | 1,704,374,591 |
se_79085165 | stackoverflow | MACHINE_LEARNING | Utilize Langchain for RAG + General Knowledge | Utilize Langchain for RAG + General Knowledge
I am trying to create a chatbot that takes past social media posts (only text) of users and is capable of generating new posts based on that. However, my ideal scenario here would be to use RAG but also leverage the inherent capabilities of an LLM. In my case, if I ask my ... | https://stackoverflow.com/questions/79085165/utilize-langchain-for-rag-general-knowledge | python, deep-learning, artificial-intelligence, large-language-model, py-langchain | 1,728,891,673 |
se_79081359 | stackoverflow | MACHINE_LEARNING | How to Create a Multilabel Confusion Matrix for 14 Disease Classes in PyTorch? | How to Create a Multilabel Confusion Matrix for 14 Disease Classes in PyTorch?
I’m working on a multilabel classification task with 14 different disease classes. I’ve trained my model, and I want to generate a single multilabel confusion matrix where both the x-axis and y-axis represent the 14 classes.
However, when I... | https://stackoverflow.com/questions/79081359/how-to-create-a-multilabel-confusion-matrix-for-14-disease-classes-in-pytorch | deep-learning, pytorch, confusion-matrix, multilabel-classification, multiclass-classification | 1,728,748,442 |
se_59384146 | stackoverflow | MACHINE_LEARNING | Why do Transformers in Natural Language Processing need a stack of encoders? | Why do Transformers in Natural Language Processing need a stack of encoders?
I am following this blog on transformers
http://jalammar.github.io/illustrated-transformer/
The only thing I don't understand is why there needs to be a stack of encoders or decoders. I understand that the multi-headed attention layers capt... | https://stackoverflow.com/questions/59384146/why-do-transformers-in-natural-language-processing-need-a-stack-of-encoders | machine-learning, deep-learning, nlp, transformer-model | 1,576,630,646 |
se_44475682 | stackoverflow | MACHINE_LEARNING | Cross validation in deep neural networks | Cross validation in deep neural networks
How do you perform cross-validation in a deep neural network? I know that to perform cross validation to will train it on all folds except one and test it on the excluded fold. Then do this for k fold times and average the accuries for each fold. How do you do this for each ite... | https://stackoverflow.com/questions/44475682/cross-validation-in-deep-neural-networks | tensorflow, deep-learning, cross-validation | 1,497,112,772 |
se_42132086 | stackoverflow | MACHINE_LEARNING | Pickle multy layer CNN in Theano, Lenet5 | Pickle multy layer CNN in Theano, Lenet5
I am using Theano for image recognition, and I want to create a prediction system using trained model.
I referenced LeNet5 Convolutional Neural Networks (LeNet) and trained my own data, now I want to use the trained model for predicting new images.
In Classifying MNIST digits u... | https://stackoverflow.com/questions/42132086/pickle-multy-layer-cnn-in-theano-lenet5 | deep-learning, theano, conv-neural-network, image-recognition | 1,486,630,549 |
se_57943425 | stackoverflow | MACHINE_LEARNING | CNN architecture: classifying "good" and "bad" images | CNN architecture: classifying "good" and "bad" images
I'm researching the possibility of implementing a CNN in order to classify images as "good" or "bad" but am having no luck with my current architecture.
Characteristics that denote a "bad" image:
Overexposure
Oversaturation
Incorrect white bala... | https://stackoverflow.com/questions/57943425/cnn-architecture-classifying-good-and-bad-images | python, machine-learning, keras, deep-learning, conv-neural-network | 1,568,544,829 |
se_54438994 | stackoverflow | MACHINE_LEARNING | Feed Deep Features to Machine learning Classifiers (Random forest ) | Feed Deep Features to Machine learning Classifiers (Random forest )
I want to feed my CNN deep features to the traditional classifier i.e random forest. I dont wanna use MLP (Multi-layer-perceptron) to classify my problem but need other classifier. I have data of images. We cannot feed unstructured data to Machine Lea... | https://stackoverflow.com/questions/54438994/feed-deep-features-to-machine-learning-classifiers-random-forest | python, machine-learning, keras, deep-learning, classification | 1,548,846,006 |
se_79078145 | stackoverflow | MACHINE_LEARNING | Jamo dependency UnicodeDecode error while cloning coqui ai/TTS repo | Jamo dependency UnicodeDecode error while cloning coqui ai/TTS repo
INFO: pip is looking at multiple versions of nltk to determine which version is compatible with other requirements. This could take a while.
Collecting nltk
Downloading nltk-3.9-py3-none-any.whl (1.5 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━... | https://stackoverflow.com/questions/79078145/jamo-dependency-unicodedecode-error-while-cloning-coqui-ai-tts-repo | python, deep-learning, text-to-speech | 1,728,648,376 |
se_62686942 | stackoverflow | MACHINE_LEARNING | OSError: [WinError 126] The specified module could not be found? | OSError: [WinError 126] The specified module could not be found?
Firstly sorry, my grammer might be bad. And if I missed any solutions in here, you can give me url, but I did not find any proper one for this case.
I'm taking a course about deep learning, and they provide us to this code. However there was an error whi... | https://stackoverflow.com/questions/62686942/oserror-winerror-126-the-specified-module-could-not-be-found | python, deep-learning | 1,593,647,819 |
se_65651051 | stackoverflow | MACHINE_LEARNING | trainable parameters of vgg16 model get changed after adding my own dense layer | trainable parameters of vgg16 model get changed after adding my own dense layer
vgg16_model = tf.keras.applications.vgg16.VGG16()
model= Sequential()
for layer in vgg16_model.layers[:-1]:
model.add(layer)
model.summary() #The last dense layer is removed till now
for layer in model.layers:
... | https://stackoverflow.com/questions/65651051/trainable-parameters-of-vgg16-model-get-changed-after-adding-my-own-dense-layer | machine-learning, deep-learning, neural-network, conv-neural-network, vgg-net | 1,610,264,359 |
se_74772411 | stackoverflow | MACHINE_LEARNING | TTS Voice Cloning | TTS Voice Cloning
I have used coqui's open-source repository to build a voice clone model. It makes use of different tts_models trained using LJSpeech datasets. I used the multilingual model to use the sample that I have provided. However, I have been getting this error:
ValueError: [!] Look like you use a multi-ling... | https://stackoverflow.com/questions/74772411/tts-voice-cloning | python, linux, deep-learning, nlp, text-to-speech | 1,670,854,464 |
se_79061201 | stackoverflow | MACHINE_LEARNING | While inferencing through saved RT-DETR model weights, KeyError: 263 | While inferencing through saved RT-DETR model weights, KeyError: 263
I have trained RT-DETR model (taken from ultralytics) for the object detection task. I am using the following code for inferencing using the saved weights:
from ultralytics import YOLO
import cv2
# Load your trained model
model = YOLO(r"/content/dri... | https://stackoverflow.com/questions/79061201/while-inferencing-through-saved-rt-detr-model-weights-keyerror-263 | deep-learning, pytorch, yolo, ultralytics | 1,728,290,053 |
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