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 |
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se_79860536 | stackoverflow | MACHINE_LEARNING | Keras to_categorical results in different memory allocation error every re-run | Keras to_categorical results in different memory allocation error every re-run
I'm working on a semantic segmentation model through U-net for classifying 11 categories. After splitting my image and label data into training and testing arrays, I turn the arrays into Unsigned Integer 8 so I have
labels = labels.astype(n... | https://stackoverflow.com/questions/79860536/keras-to-categorical-results-in-different-memory-allocation-error-every-re-run | python, numpy, keras, deep-learning, semantic-segmentation | 1,767,595,231 |
se_79857308 | stackoverflow | MACHINE_LEARNING | What are the advance steps required in model training and how can i do does? | What are the advance steps required in model training and how can i do does?
I am training a model using pytorch using a NVIDIA GPU. The time taken to run and evaluate a single epoch is about 1 hour, what should i do about this, and simillarly, what are the further steps i need to do to completly develop the model lik... | https://stackoverflow.com/questions/79857308/what-are-the-advance-steps-required-in-model-training-and-how-can-i-do-does | optimization, deep-learning, pytorch, gpu | 1,767,078,396 |
se_79856699 | stackoverflow | MACHINE_LEARNING | How to preprocess and train a binary classifier on cat/dog images using logistic regression in PyTorch? | How to preprocess and train a binary classifier on cat/dog images using logistic regression in PyTorch?
Body:
I'm trying to build a binary image classifier (cat vs dog) using logistic regression in PyTorch.
Background:
I previously implemented softmax classification on MNIST: https://github.com/jeehoo0507/Mnist-softm... | https://stackoverflow.com/questions/79856699/how-to-preprocess-and-train-a-binary-classifier-on-cat-dog-images-using-logistic | python, deep-learning, pytorch | 1,767,003,733 |
se_79855982 | stackoverflow | MACHINE_LEARNING | Is my use of tf.distribute.MirroredStrategy and strategy.scope() correct and safe for multi-GPU training in Keras? | Is my use of tf.distribute.MirroredStrategy and strategy.scope() correct and safe for multi-GPU training in Keras?
I am training a model using Keras + TensorFlow with tf.distribute.MirroredStrategy on a multi-GPU setup. I would like to verify that I am using strategy.scope() correctly.
import time
import logging
impo... | https://stackoverflow.com/questions/79855982/is-my-use-of-tf-distribute-mirroredstrategy-and-strategy-scope-correct-and-saf | python, tensorflow, keras, deep-learning | 1,766,874,442 |
se_79855418 | stackoverflow | MACHINE_LEARNING | I am confused, when to use tensorflow and pytorch | I am confused, when to use tensorflow and pytorch
I am always confused between tensorflow and pytorch when to use which, because both are used for same task but when to use tensorflow and pytorch, like situation oriented. Some people's said suggested me if doing any research or something use pytorch, it is best for th... | https://stackoverflow.com/questions/79855418/i-am-confused-when-to-use-tensorflow-and-pytorch | machine-learning, deep-learning, computer-vision, artificial-intelligence, software-distribution | 1,766,767,960 |
se_73266516 | stackoverflow | MACHINE_LEARNING | Pytorch equivalent of `register_buffer` in flax/jax | Pytorch equivalent of `register_buffer` in flax/jax
I'm searching a way to write the equivalent of the following Pytorch module in Flax but I haven't found a way to do it. The important thing is that the constant should be loadable and saveable upon checkpoint.
class SillyModule(nn.Module):
def __init__(self, ):
... | https://stackoverflow.com/questions/73266516/pytorch-equivalent-of-register-buffer-in-flax-jax | python, deep-learning, pytorch, jax, flax | 1,659,866,291 |
se_48001598 | stackoverflow | MACHINE_LEARNING | Why do we need to call zero_grad() in PyTorch? | Why do we need to call zero_grad() in PyTorch?
Why does zero_grad() need to be called during training?
| zero_grad(self)
| Sets gradients of all model parameters to zero. | https://stackoverflow.com/questions/48001598/why-do-we-need-to-call-zero-grad-in-pytorch | python, neural-network, deep-learning, pytorch, gradient-descent | 1,514,435,500 |
se_79852884 | stackoverflow | MACHINE_LEARNING | How to dynamically estimate maximum number of cameras my GPU can handle for YOLOv8 inference? | How to dynamically estimate maximum number of cameras my GPU can handle for YOLOv8 inference?
I’m trying to simulate multiple camera streams feeding into a YOLOv8l model on a single GPU and monitor real-time hardware utilization. My setup:
Single GPU (48GB VRAM, CUDA-enabled)
YOLOv8l model
Simulating N cameras with... | https://stackoverflow.com/questions/79852884/how-to-dynamically-estimate-maximum-number-of-cameras-my-gpu-can-handle-for-yolo | python, tensorflow, deep-learning, pytorch, nvidia | 1,766,406,199 |
se_60609585 | stackoverflow | MACHINE_LEARNING | Good performance with Accuracy but not with Dice loss in Image Segmentation | Good performance with Accuracy but not with Dice loss in Image Segmentation
I'm doing image segmentation with U-Net like architecture on Tensorflow w/Keras but I'm new in Deep Learning.
I've got this dataset with the following set shapes:
Train : X : (175250, 30, 30, 6) Y: (175250, 30, 30)
Validation: X: (29200, 30,... | https://stackoverflow.com/questions/60609585/good-performance-with-accuracy-but-not-with-dice-loss-in-image-segmentation | python, tensorflow, deep-learning, conv-neural-network, tf.keras | 1,583,795,952 |
se_47488598 | stackoverflow | MACHINE_LEARNING | AttributeError: 'CrossEntropyLoss' object has no attribute 'backward' | AttributeError: 'CrossEntropyLoss' object has no attribute 'backward'
i am trying to train a very basic CNN on CIFAR10 data set and getting the following error :
AttributeError: 'CrossEntropyLoss' object has no attribute 'backward'
criterion =nn.CrossEntropyLoss
optimizer=optim.SGD(net.parameters(),lr... | https://stackoverflow.com/questions/47488598/attributeerror-crossentropyloss-object-has-no-attribute-backward | python, neural-network, deep-learning, conv-neural-network, pytorch | 1,511,630,107 |
se_41455101 | stackoverflow | MACHINE_LEARNING | What is the meaning of the word logits in TensorFlow? | What is the meaning of the word logits in TensorFlow?
In the following TensorFlow function, we must feed the activation of artificial neurons in the final layer. That I understand. But I don't understand why it is called logits? Isn't that a mathematical function?
loss_function = tf.nn.softmax_cross_entropy_with_log... | https://stackoverflow.com/questions/41455101/what-is-the-meaning-of-the-word-logits-in-tensorflow | tensorflow, machine-learning, neural-network, deep-learning, cross-entropy | 1,483,495,351 |
se_79841874 | stackoverflow | MACHINE_LEARNING | Apply Quantization on a CNN | Apply Quantization on a CNN
I want to apply a quantization function to a deep CNN. This CNN is used for an image classification(in 4 classes) task, and my data consists of 224×224 images. When I run this code, I get an error. How can I solve this issue? I want to apply compression technique to reduce the model size an... | https://stackoverflow.com/questions/79841874/apply-quantization-on-a-cnn | tensorflow, deep-learning, compression, quantization, quantization-aware-training | 1,765,280,166 |
se_58419436 | stackoverflow | MACHINE_LEARNING | Extracting attention weights of each token at each layer of transformer in python | Extracting attention weights of each token at each layer of transformer in python
I am doing some NLP and I am interested in extracting attention weights of individual test token at each layer of transformer via Python (PyTorch, TensorFlow, etc.)
Is coding up a Transformer (any transformers like Transformer-XL, OpenA... | https://stackoverflow.com/questions/58419436/extracting-attention-weights-of-each-token-at-each-layer-of-transformer-in-pytho | tensorflow, keras, deep-learning, nlp, pytorch | 1,571,249,871 |
se_48029542 | stackoverflow | MACHINE_LEARNING | Data augmentation in test/validation set? | Data augmentation in test/validation set?
It is common practice to augment data (add samples programmatically, such as random crops, etc. in the case of a dataset consisting of images) on both training and test set, or just the training data set? | https://stackoverflow.com/questions/48029542/data-augmentation-in-test-validation-set | machine-learning, deep-learning | 1,514,590,316 |
se_44021214 | stackoverflow | MACHINE_LEARNING | How can I use NumPy functions on a Keras tensor in the loss function? | How can I use NumPy functions on a Keras tensor in the loss function?
I'm using Keras with a TensorFlow backend to build and run a neural network. I need to use a NumPy function on my output tensor in the loss function.
More specifically, my loss function involves finding nearest neighbors, and I need to use the Keras... | https://stackoverflow.com/questions/44021214/how-can-i-use-numpy-functions-on-a-keras-tensor-in-the-loss-function | python, numpy, tensorflow, keras, deep-learning | 1,495,014,275 |
se_79826360 | stackoverflow | MACHINE_LEARNING | Python library recommendation for the implementation of a neural network modification algorithm | Python library recommendation for the implementation of a neural network modification algorithm
I want to implement in python some algorithms from a paper that allow for a pre-trained neural network to be modified (adding or removing neurons or layers) conserving (theoretically) the outputs of the network over the tra... | https://stackoverflow.com/questions/79826360/python-library-recommendation-for-the-implementation-of-a-neural-network-modific | python, algorithm, deep-learning, neural-network | 1,763,718,621 |
se_79834752 | stackoverflow | MACHINE_LEARNING | Repetitive generation on instruction tuning for raw language model | Repetitive generation on instruction tuning for raw language model
I have used the following code to do sft:
base_model = "google/gemma-3-270m"
it_model = "google/gemma-3-270m-it"
checkpoint_dir = "checkpoint"
learning_rate = 5e-5 #@param {type:"number"}
from datasets import Dataset
from transformers import pipeline
f... | https://stackoverflow.com/questions/79834752/repetitive-generation-on-instruction-tuning-for-raw-language-model | machine-learning, deep-learning, huggingface-transformers, large-language-model, fine-tuning | 1,764,588,837 |
se_59129812 | stackoverflow | MACHINE_LEARNING | How to avoid "CUDA out of memory" in PyTorch | How to avoid "CUDA out of memory" in PyTorch
I think it's a pretty common message for PyTorch users with low GPU memory:
RuntimeError: CUDA out of memory. Tried to allocate X MiB (GPU X; X GiB total capacity; X GiB already allocated; X MiB free; X cached)
I tried to process an image by loading each layer to... | https://stackoverflow.com/questions/59129812/how-to-avoid-cuda-out-of-memory-in-pytorch | python, deep-learning, pytorch, object-detection, low-memory | 1,575,233,173 |
se_79836456 | stackoverflow | MACHINE_LEARNING | Get image paths from tfds food101 | Get image paths from tfds food101
I'm working on food101 tensorflow dataset and want to know the most wrong predictions of my efficientnet model, for that purpose I'd need to get image paths of test data, but I don't know how I can get the paths as the dataset is from tfds, not my own data (or downloaded in my compute... | https://stackoverflow.com/questions/79836456/get-image-paths-from-tfds-food101 | tensorflow, deep-learning, tensorflow-datasets, image-classification | 1,764,727,484 |
se_79783011 | stackoverflow | MACHINE_LEARNING | Kohya-SS SDXL LoRA Training Resets Steps Despite Successful State Loading | Kohya-SS SDXL LoRA Training Resets Steps Despite Successful State Loading
I am running SDXL LoRA training using Kohya's sd-scripts and accelerate. I have enabled --save_state and am trying to resume training, but the training steps always reset to 0, even though the log indicates the state files are loaded.
I need the... | https://stackoverflow.com/questions/79783011/kohya-ss-sdxl-lora-training-resets-steps-despite-successful-state-loading | python, deep-learning, stable-diffusion, resuming-training | 1,759,672,913 |
se_72926254 | stackoverflow | MACHINE_LEARNING | Avoid Division by Zero in Sigmoid function | Avoid Division by Zero in Sigmoid function
With : https://nbviewer.org/github/ImadDabbura/blog-posts/blob/master/notebooks/Coding-Neural-Network-Forwad-Back-Propagation.ipynb as reference
I am trying to build a Vanila Deep Learning Code.
I wonder how is division by zero avoided in the sigmoid funtion.
def sigmoid(Z):
... | https://stackoverflow.com/questions/72926254/avoid-division-by-zero-in-sigmoid-function | python, deep-learning | 1,657,429,432 |
se_71044014 | stackoverflow | MACHINE_LEARNING | Recurrent Neural Networks for Drawing Classification tutorial code doesn't run on tensorflow 2 | Recurrent Neural Networks for Drawing Classification tutorial code doesn't run on tensorflow 2
I'm a beginner in deep leaerning and Tensorflow.
I tried to run the tutorial code for Recurrent Neural Networks for Drawing Classification on my computer following the directions written there. But the provided tutorial ... | https://stackoverflow.com/questions/71044014/recurrent-neural-networks-for-drawing-classification-tutorial-code-doesnt-run-o | python, tensorflow, deep-learning, neural-network | 1,644,380,936 |
se_75583410 | stackoverflow | MACHINE_LEARNING | module.save() Error 'TypeError: this __dict__ descriptor does not support '_DictWrapper' objects' | module.save() Error 'TypeError: this __dict__ descriptor does not support '_DictWrapper' objects'
I'm following a tutorial on Youtube for image classification with machine learning. I keep getting the error as shown in the title from trying to save a deep learning module with tensorflow.
I'm using PyCh... | https://stackoverflow.com/questions/75583410/module-save-error-typeerror-this-dict-descriptor-does-not-support-dict | python, tensorflow, deep-learning, pycharm | 1,677,517,260 |
se_79832402 | stackoverflow | MACHINE_LEARNING | How to read a large Python project (for example, a project of Deep Learning or Reinforcement Learning) | How to read a large Python project (for example, a project of Deep Learning or Reinforcement Learning)
I've downloaded many Python projects about Reinforcement Learning from Github, but each takes me too much time to read.
It's easy to comprehend a simple Python project with only a few *.py files, but how to read a pr... | https://stackoverflow.com/questions/79832402/how-to-read-a-large-python-project-for-example-a-project-of-deep-learning-or-r | python, github, deep-learning, artificial-intelligence, reinforcement-learning | 1,764,320,950 |
se_48324152 | stackoverflow | MACHINE_LEARNING | How to change the learning rate of an optimizer at any given moment (no LR schedule)? | How to change the learning rate of an optimizer at any given moment (no LR schedule)?
Is it possible in PyTorch to change the learning rate of the optimizer in the middle of training dynamically (I don't want to define a learning rate schedule beforehand)?
So let's say I have an optimizer:
optim = torch.optim.SGD(mo... | https://stackoverflow.com/questions/48324152/how-to-change-the-learning-rate-of-an-optimizer-at-any-given-moment-no-lr-sched | python, optimization, neural-network, deep-learning, pytorch | 1,516,287,352 |
se_79295498 | stackoverflow | MACHINE_LEARNING | UserWarning: Mutation on a buffer in the model is detected. ExecuTorch assumes buffers that are mutated in the graph have a meaningless initial state | UserWarning: Mutation on a buffer in the model is detected. ExecuTorch assumes buffers that are mutated in the graph have a meaningless initial state
I have exported model to Executorch program, and the file is saved correctly in directory. But I enountered warning like this
# To see more debug info, please use `graph... | https://stackoverflow.com/questions/79295498/userwarning-mutation-on-a-buffer-in-the-model-is-detected-executorch-assumes-b | python, deep-learning, pytorch, conv-neural-network | 1,734,639,166 |
se_10565868 | stackoverflow | MACHINE_LEARNING | multi-layer perceptron (MLP) architecture: criteria for choosing number of hidden layers and size of the hidden layer? | multi-layer perceptron (MLP) architecture: criteria for choosing number of hidden layers and size of the hidden layer?
If we have 10 eigenvectors then we can have 10 neural nodes in input layer.If we have 5 output classes then we can have 5 nodes in output layer.But what is the criteria for choosing number of hidden l... | https://stackoverflow.com/questions/10565868/multi-layer-perceptron-mlp-architecture-criteria-for-choosing-number-of-hidde | machine-learning, neural-network, deep-learning, perceptron | 1,336,843,088 |
se_78376085 | stackoverflow | MACHINE_LEARNING | RuntimeError: Default process group has not been initialized, please make sure to call init_process_group | RuntimeError: Default process group has not been initialized, please make sure to call init_process_group
I am using CoDi which is multimodal Latent diffusion model. I am trying to remove the modules on images and video from CoDi and fine tune it with text-music pair data.
The training script (train.py) for generating... | https://stackoverflow.com/questions/78376085/runtimeerror-default-process-group-has-not-been-initialized-please-make-sure-t | python, machine-learning, deep-learning, pytorch, artificial-intelligence | 1,713,935,111 |
se_79771693 | stackoverflow | MACHINE_LEARNING | !pip install mediapipe opencv-python error | !pip install mediapipe opencv-python error
I am getting this below error for when I try to install mediapipe on Kaggle.
The same command works on the Google Collab fine but not on Kaggle.
WARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionEr... | https://stackoverflow.com/questions/79771693/pip-install-mediapipe-opencv-python-error | deep-learning, mediapipe | 1,758,548,913 |
se_71809044 | stackoverflow | MACHINE_LEARNING | metric learning and contrastive learning difference | metric learning and contrastive learning difference
I researched some materials，and know that the goal of contrastive learning and metric learning are both to learn such an embedding space in which similar sample pairs stay close to each other while dissimilar ones are far apart. But what is the difference of metric l... | https://stackoverflow.com/questions/71809044/metric-learning-and-contrastive-learning-difference | machine-learning, deep-learning, embedding, supervised-learning, self-supervised-learning | 1,649,515,242 |
se_79749577 | stackoverflow | MACHINE_LEARNING | Getting different results across different machines while training RL | Getting different results across different machines while training RL
While training my RL algorithm using SBX, I am getting different results across my HPC cluster and PC. However, I did find that results consistently are same within the same machine. They just diverge across machines. I am limiting all computation t... | https://stackoverflow.com/questions/79749577/getting-different-results-across-different-machines-while-training-rl | deep-learning, reinforcement-learning, jax, stable-baselines | 1,756,413,774 |
se_62272056 | stackoverflow | MACHINE_LEARNING | What are the differences between contextual embedding and word embedding | What are the differences between contextual embedding and word embedding
I am trying to understand the concept of embedding for the deep learning models.
I understand how employing word2vec can address the limitations of using the one-hot vectors.
However, recently I see a plethora of blog posts stating ELMo, BERT, ... | https://stackoverflow.com/questions/62272056/what-are-the-differences-between-contextual-embedding-and-word-embedding | machine-learning, deep-learning, nlp, artificial-intelligence, word-embedding | 1,591,654,630 |
se_76965920 | stackoverflow | MACHINE_LEARNING | Yolo v8 slow fps in real time | Yolo v8 slow fps in real time
I had been training a yolo v8 nano model with 1.5k images with the size of 640x640 and I decided to make it live with this code:
from ultralytics import YOLO
from ultralytics.yolo.v8.detect.predict import DetectionPredictor
import cv2
model = YOLO("Model/best.pt")
model.predict(source="0"... | https://stackoverflow.com/questions/76965920/yolo-v8-slow-fps-in-real-time | python, deep-learning, object-detection, yolo, yolov8 | 1,692,844,466 |
se_79464030 | stackoverflow | MACHINE_LEARNING | None Gradients for a model with 2 outputs | None Gradients for a model with 2 outputs
I have a model that has a GRU implementation inside and process audio samples. In each forward path I process a single sample of an audio file. To imitate the GRU behavior correctly, I have returned the output of my GRU implementation in each forward pass and pass that data al... | https://stackoverflow.com/questions/79464030/none-gradients-for-a-model-with-2-outputs | tensorflow, deep-learning, audio-processing, gradienttape, gru | 1,740,410,150 |
se_78303940 | stackoverflow | MACHINE_LEARNING | Deeplearning4j - creating a model for strings employee, worker, associate etc | Deeplearning4j - creating a model for strings employee, worker, associate etc
I wanted to build a model / train the model using deeplearning4j.
This model should understand all the employee related jargon for example, it should understand the words Employee, Worker, Associate as same words.
I was using below code snip... | https://stackoverflow.com/questions/78303940/deeplearning4j-creating-a-model-for-strings-employee-worker-associate-etc | machine-learning, deep-learning, deeplearning4j | 1,712,746,896 |
se_79784559 | stackoverflow | MACHINE_LEARNING | Avoid overlap of bipartite network nodes in ggraph | Avoid overlap of bipartite network nodes in ggraph
I'm plotting a bipartite (two-mode) network using igraph and ggraph.
But the nodes are overlapping a lot, even though there is still space in the graphic window.
I would like to plot this using ggraph, and I know it's possible to plot with other packages, such as igra... | https://stackoverflow.com/questions/79784559/avoid-overlap-of-bipartite-network-nodes-in-ggraph | r, deep-learning, igraph, ggraph | 1,759,841,492 |
se_79807844 | stackoverflow | MACHINE_LEARNING | Will tf.keras.Sequential containing multiple custom layers be correctly fully serializable and deserializable in my case? | Will tf.keras.Sequential containing multiple custom layers be correctly fully serializable and deserializable in my case?
I am implementing a U-Net variant in TensorFlow/Keras with custom layers. In one of my layers custom layers UPDoubleConv, I have a Sequential self.blocks containing a repeated pattern of UpSampling... | https://stackoverflow.com/questions/79807844/will-tf-keras-sequential-containing-multiple-custom-layers-be-correctly-fully-se | python, tensorflow, keras, deep-learning, tf.keras | 1,762,171,259 |
se_61399871 | stackoverflow | MACHINE_LEARNING | Interpretation of RNN/LSTM cell | Interpretation of RNN/LSTM cell
I am learning RNN, especially LSTM networks. I have read a lot of topics, including this one and I still have some misunderstandings.
The image below is from this article and it represents single RNN cell unfolded in time.
1. Do I understand correctly, that RNN cell is not a single neu... | https://stackoverflow.com/questions/61399871/interpretation-of-rnn-lstm-cell | machine-learning, deep-learning, lstm, recurrent-neural-network | 1,587,693,781 |
se_79803908 | stackoverflow | MACHINE_LEARNING | Decoder only model AI making repetitive responses | Decoder only model AI making repetitive responses
I am making a Decoder only transformer using Pytorch and my dataset of choice is the fullEnglish dataset from kaggle Plaintext Wikipedia (full English).
The problem is that my model output is repetitive:
print(generate(model=model, prompt="what is anarchism", tokenizer... | https://stackoverflow.com/questions/79803908/decoder-only-model-ai-making-repetitive-responses | python, deep-learning, pytorch | 1,761,748,358 |
se_71514834 | stackoverflow | MACHINE_LEARNING | Unable to train CNN Model | Unable to train CNN Model
Original dataset shape is (343889, 80) and last column is of Labels. The training and testing set split is done
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.30, random_state=10)
shape of - training dataset (240722, 80)
shape of - training Labels (240722,)
shape of -... | https://stackoverflow.com/questions/71514834/unable-to-train-cnn-model | python, tensorflow, keras, deep-learning, conv-neural-network | 1,647,530,468 |
se_69933910 | stackoverflow | MACHINE_LEARNING | Getting error when training the CNN model | Getting error when training the CNN model
I am getting errors when training my CNN model which is for checking what a person is telling in sign language. I am working with keras, tensorflow.
This is my code:
import tensorflow as tf ;importing libraries
from tensorflow.keras import datasets,layers,models
import numpy ... | https://stackoverflow.com/questions/69933910/getting-error-when-training-the-cnn-model | python, tensorflow, keras, deep-learning, conv-neural-network | 1,636,659,169 |
se_43204194 | stackoverflow | MACHINE_LEARNING | CNN is not learning at all | CNN is not learning at all
I just created my own CNN which reads data from the disk and tries to learn.
But the weights don't seem to learn at all, they all stay randomized.
The biases change only a bit. I already tried to use grayscale images, without success. I also tired to reduce my dataset to only 2 classes which... | https://stackoverflow.com/questions/43204194/cnn-is-not-learning-at-all | python, tensorflow, machine-learning, deep-learning, conv-neural-network | 1,491,300,494 |
se_74792455 | stackoverflow | MACHINE_LEARNING | module 'keras.layers' has no attribute 'experimental' | module 'keras.layers' has no attribute 'experimental'
hello so I was trying to resize and rescale my dataset as shown below l but I encountered this error:
AttributeError: module 'keras.layers' has no attribute 'experimental'
resize_and_rescale= tf.keras.Sequential([
layers.experimental.preprocess... | https://stackoverflow.com/questions/74792455/module-keras-layers-has-no-attribute-experimental | python, tensorflow, machine-learning, deep-learning, dataset | 1,670,978,629 |
se_79801643 | stackoverflow | MACHINE_LEARNING | AttributeError: 'NoneType' object has no attribute 'blocks' when running Cache-DiT example with Wan2.2 model | AttributeError: 'NoneType' object has no attribute 'blocks' when running Cache-DiT example with Wan2.2 model
I’m trying to use
Cache-DiT
to accelerate inference for the Wan2.2 model.
However, when I run the example script,
python run_wan_2.2_i2v.py --steps 28 --cache
I get the following error.
Namespa... | https://stackoverflow.com/questions/79801643/attributeerror-nonetype-object-has-no-attribute-blocks-when-running-cache-d | deep-learning, pytorch, artificial-intelligence | 1,761,556,882 |
se_79778907 | stackoverflow | MACHINE_LEARNING | ValueError: Only instances of keras.Layer can be added to a Sequential model when using TensorFlow Hub KerasLayer | ValueError: Only instances of keras.Layer can be added to a Sequential model when using TensorFlow Hub KerasLayer
I’m trying to build a Keras Sequential model using a feature extractor from TensorFlow Hub, but I’m running into this error:
ValueError: Only instances of `keras.Layer` can be added to a Sequential model. ... | https://stackoverflow.com/questions/79778907/valueerror-only-instances-of-keras-layer-can-be-added-to-a-sequential-model-whe | python, tensorflow, keras, deep-learning | 1,759,222,955 |
se_78137767 | stackoverflow | MACHINE_LEARNING | Selection of minibatch size for PPO Reinforcement Learning algorithm | Selection of minibatch size for PPO Reinforcement Learning algorithm
PPO algorithm in Deep Reinforcement Learning requires to set the dimension of minibatches.
In case of "standard" Deep Learning, a lot of references are available as a guide to the optimal selection, and in general "small" minibatches (up to 32 sample... | https://stackoverflow.com/questions/78137767/selection-of-minibatch-size-for-ppo-reinforcement-learning-algorithm | deep-learning, reinforcement-learning, mini-batch | 1,710,111,648 |
se_79795060 | stackoverflow | MACHINE_LEARNING | Pretrained ESRGAN (.pb) gives reddish or purple image — is this a preprocessing issue or model issue? | Pretrained ESRGAN (.pb) gives reddish or purple image — is this a preprocessing issue or model issue?
I'm trying to use a pretrained ESRGAN model that I downloaded in .pb format.
The model runs without errors, but the output image has a noticeable reddish/purple tint instead of the correct colors.
import tensorflow as... | https://stackoverflow.com/questions/79795060/pretrained-esrgan-pb-gives-reddish-or-purple-image-is-this-a-preprocessing | python, tensorflow, image-processing, deep-learning | 1,760,975,644 |
se_72268859 | stackoverflow | MACHINE_LEARNING | Externally add a Variable to a model in TensorFlow | Externally add a Variable to a model in TensorFlow
I have an existing TensorFlow model, and I want to add a new "parameter" (a tf.Variable) to the model's list of parameters (such that it's trainable) and add it externally to the model's list of parameters / computational graph.
One approach that I tried, is to append... | https://stackoverflow.com/questions/72268859/externally-add-a-variable-to-a-model-in-tensorflow | python, tensorflow, deep-learning, neural-network, pytorch | 1,652,767,207 |
se_79788392 | stackoverflow | MACHINE_LEARNING | Torch Conv2d results in both dimensions convolved | Torch Conv2d results in both dimensions convolved
I have input shape to a convolution (50, 1, 7617, 10). Here, 7617 is word vectors as rows, and 10 is the number of words in columns. I want to convolve column-wise and obtain (2631, 1, 7617, 1), 1 sentence vector obtained by convolving all word vectors through a series... | https://stackoverflow.com/questions/79788392/torch-conv2d-results-in-both-dimensions-convolved | deep-learning, pytorch, neural-network, conv-neural-network, convolution | 1,760,247,295 |
se_79791269 | stackoverflow | MACHINE_LEARNING | Utilizing GPU with RNN models which takes it's output as input [torch] | Utilizing GPU with RNN models which takes it's output as input [torch]
I have a machine-translation model. In this model, I calculate a vector for a given sentence and I take this vector, aggregate with each generated output of RNN and put it into RNN again for calculating next hidden state and generating next out... | https://stackoverflow.com/questions/79791269/utilizing-gpu-with-rnn-models-which-takes-its-output-as-input-torch | deep-learning, nlp, gpu, torch, multi-gpu | 1,760,538,024 |
se_79777399 | stackoverflow | MACHINE_LEARNING | Preventing GPU memory leak due to a custom neural network layer | Preventing GPU memory leak due to a custom neural network layer
I am using the MixStyle methodology for domain adaptation, and it involves using a custom layer that is inserted after every encoder stage. However, it is causing VRAM to grow linearly, which causes an OOM error.
No memory leak occurs on disabling the lay... | https://stackoverflow.com/questions/79777399/preventing-gpu-memory-leak-due-to-a-custom-neural-network-layer | deep-learning, pytorch, neural-network, computer-vision, semantic-segmentation | 1,759,071,642 |
se_79791036 | stackoverflow | MACHINE_LEARNING | Why does the same YOLOv8n-pose model with different weights have significantly different inference speeds? | Why does the same YOLOv8n-pose model with different weights have significantly different inference speeds?
I’m testing YOLOv8n-pose models that share the exact same architecture, input size, hardware (GPU), framework, batch size, and precision settings. The only difference between them is the trained weights.
However,... | https://stackoverflow.com/questions/79791036/why-does-the-same-yolov8n-pose-model-with-different-weights-have-significantly-d | performance, deep-learning, inference, yolov8, pose-estimation | 1,760,523,344 |
se_60018578 | stackoverflow | MACHINE_LEARNING | What does model.eval() do in pytorch? | What does model.eval() do in pytorch?
When should I use .eval()? I understand it is supposed to allow me to "evaluate my model". How do I turn it back off for training?
Example training code using .eval(). | https://stackoverflow.com/questions/60018578/what-does-model-eval-do-in-pytorch | python, machine-learning, deep-learning, pytorch | 1,580,572,695 |
se_58127059 | stackoverflow | MACHINE_LEARNING | How to understand masked multi-head attention in transformer | How to understand masked multi-head attention in transformer
I'm currently studying the code of transformer, but I can not understand the masked multi-head of decoder. The paper said that it was to prevent you from seeing the generating word, but I can not understand if the words after generating word have not been ge... | https://stackoverflow.com/questions/58127059/how-to-understand-masked-multi-head-attention-in-transformer | tensorflow, machine-learning, deep-learning, transformer-model, attention-model | 1,569,552,048 |
se_75970695 | stackoverflow | MACHINE_LEARNING | How to Stacking ML models correctly - Sklearn | How to Stacking ML models correctly - Sklearn
I need some help to understand how to build the stack correctly.
I started building a Stack right now from only two models: RandomForestRegressor, XGBRegressor.
Each model is essentially an independent object.
But it is also possible to create a Stack object that consists ... | https://stackoverflow.com/questions/75970695/how-to-stacking-ml-models-correctly-sklearn | python, machine-learning, scikit-learn, deep-learning | 1,681,045,680 |
se_68580717 | stackoverflow | MACHINE_LEARNING | How can I solve this issue? input must have 3 dimensions, got 4 | How can I solve this issue? input must have 3 dimensions, got 4
The Below is data which I passed to the Data Loader,
train_path='/content/drive/MyDrive/Dataset_manual_pytorch/train'
test_path='/content/drive/MyDrive/Dataset_manual_pytorch/test'
train = torchvision.datasets.ImageFolder(train_path,transform=transformat... | https://stackoverflow.com/questions/68580717/how-can-i-solve-this-issue-input-must-have-3-dimensions-got-4 | python-3.x, deep-learning, pytorch | 1,627,580,930 |
se_39460436 | stackoverflow | MACHINE_LEARNING | How to create TFRecords file from png images | How to create TFRecords file from png images
I'm just started working with TensorFlow a week ago, and I have some basic problems.
The major one is that I didn't find a way to create a TFRecords that contains all my data. I understood that this process is necessary in order to train my own network with few millions 32x... | https://stackoverflow.com/questions/39460436/how-to-create-tfrecords-file-from-png-images | database, tensorflow, deep-learning, convolution, tensorflow-serving | 1,473,725,206 |
se_56429967 | stackoverflow | MACHINE_LEARNING | How to find prediction probability in given CNN in tensor flow? | How to find prediction probability in given CNN in tensor flow?
I am very new to TensorFlow. Let us assume that I already have a trained convolutional neural network, now I give one new data to this CNN, and I want to see what's the prediction probability in each class. (e.g, the CNN is for handwriting 0-2, now I give... | https://stackoverflow.com/questions/56429967/how-to-find-prediction-probability-in-given-cnn-in-tensor-flow | python, tensorflow, deep-learning, conv-neural-network, prediction | 1,559,574,050 |
se_79776858 | stackoverflow | MACHINE_LEARNING | Multimodel for image captioning with CNN and LSTM over flickr30k does not learn. How to fuse image features and word embeddings? | Multimodel for image captioning with CNN and LSTM over flickr30k does not learn. How to fuse image features and word embeddings?
I'm working on an image captioning project using a simple CNN + LSTM architecture, as required by the course I'm studying. The full code is available here on GitHub (note: some parts are mem... | https://stackoverflow.com/questions/79776858/multimodel-for-image-captioning-with-cnn-and-lstm-over-flickr30k-does-not-learn | python, tensorflow, keras, deep-learning, lstm | 1,758,987,253 |
se_79774394 | stackoverflow | MACHINE_LEARNING | Can I visualize a neural network’s loss landscape to see if it’s stuck in a bad minimum? Any code example for this? | Can I visualize a neural network’s loss landscape to see if it’s stuck in a bad minimum? Any code example for this?
So, I’m trying to understand why sometimes neural networks get stuck during training. I heard people talk about ‘local minima’ and ‘saddle points,’ but I can’t really picture them. I want to actually see... | https://stackoverflow.com/questions/79774394/can-i-visualize-a-neural-network-s-loss-landscape-to-see-if-it-s-stuck-in-a-bad | python, tensorflow, machine-learning, deep-learning, neural-network | 1,758,778,581 |
se_79766096 | stackoverflow | MACHINE_LEARNING | GraphMAE self-supervised learning: node attribute (sampled points) reconstruction works in minimal script but fails in full pipeline | GraphMAE self-supervised learning: node attribute (sampled points) reconstruction works in minimal script but fails in full pipeline
I am experimenting with a GraphMAE self-supervised architecture using PyTorch + DGL.
In my task, each graph node represents a CAD entity, and one node attribute stores sampled points (co... | https://stackoverflow.com/questions/79766096/graphmae-self-supervised-learning-node-attribute-sampled-points-reconstructio | python, deep-learning, graph-neural-network, self-supervised-learning | 1,758,017,506 |
se_72016494 | stackoverflow | MACHINE_LEARNING | Creating a image dataset | Creating a image dataset
I have a folder with 38000 images and I'm trying to create a dataset from them to use in a Convolutional LSTM, which supports input in the format of a 5d array (B,T,W,H,C) where B is the number of samples, T is the size of the samples and the rest of the array are the image properties.
So far ... | https://stackoverflow.com/questions/72016494/creating-a-image-dataset | python, arrays, machine-learning, deep-learning, data-science | 1,650,986,397 |
se_69526429 | stackoverflow | MACHINE_LEARNING | Why do we need 'value', 'key', and 'query' in attention layer? | Why do we need 'value', 'key', and 'query' in attention layer?
I am learning basic ideas about the 'Transformer' Model. Based on the paper and tutorial I saw, the 'Attention layer' uses the neural network to get the 'value', the 'key', and the 'query'.
Here is the attention layer I learned from... | https://stackoverflow.com/questions/69526429/why-do-we-need-value-key-and-query-in-attention-layer | machine-learning, deep-learning, transformer-model, attention-model, self-attention | 1,633,956,312 |
se_79760189 | stackoverflow | MACHINE_LEARNING | Why isn't my keras model throwing and error when different sizes are passed to the dense layer? | Why isn't my keras model throwing and error when different sizes are passed to the dense layer?
I am working on a dynamic time series multi-class segmentation problem with keras (tensorflow version 2.12.0), and I wanted to see what would happen when I dropped in a dense layer into the network architecture. My expe... | https://stackoverflow.com/questions/79760189/why-isnt-my-keras-model-throwing-and-error-when-different-sizes-are-passed-to-t | python, tensorflow, machine-learning, keras, deep-learning | 1,757,443,996 |
se_53949880 | stackoverflow | MACHINE_LEARNING | Jointly training custom model with Tensorflow Object Detection API | Jointly training custom model with Tensorflow Object Detection API
I am trying to use Tensorflow object detection API models in another custom model I built (in the same codebase). Specifically, I am trying to figure out how below can be handled (mutually exclusive points):
jointly train Tensorflow object detection ... | https://stackoverflow.com/questions/53949880/jointly-training-custom-model-with-tensorflow-object-detection-api | python, tensorflow, machine-learning, deep-learning, computer-vision | 1,545,938,657 |
se_69367939 | stackoverflow | MACHINE_LEARNING | Understanding backpropagation in PyTorch | Understanding backpropagation in PyTorch
I am exploring PyTorch, and I do not understand the output of the following example:
# Initialize x, y and z to values 4, -3 and 5
x = torch.tensor(4., requires_grad = True)
y = torch.tensor(-3., requires_grad = True)
z = torch.tensor(5., requires_grad = True)
# Set q to sum ... | https://stackoverflow.com/questions/69367939/understanding-backpropagation-in-pytorch | python, deep-learning, neural-network, pytorch, backpropagation | 1,632,859,822 |
se_70344059 | stackoverflow | MACHINE_LEARNING | OSError: Unable to open file (file signature not found) | OSError: Unable to open file (file signature not found)
I am currently doing an assignment on deep learning by downloading the assignment files from github.
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import Image
from scipy import ndimage
from lr_utils import load_dataset
%ma... | https://stackoverflow.com/questions/70344059/oserror-unable-to-open-file-file-signature-not-found | python-3.x, deep-learning, jupyter-notebook, h5py | 1,639,458,601 |
se_44483233 | stackoverflow | MACHINE_LEARNING | Is using batch size as 'powers of 2' faster on tensorflow? | Is using batch size as 'powers of 2' faster on tensorflow?
I read from somewhere that if you choose a batch size that is a power 2, training will be faster. What is this rule? Is this applicable to other applications? Can you provide a reference paper? | https://stackoverflow.com/questions/44483233/is-using-batch-size-as-powers-of-2-faster-on-tensorflow | tensorflow, machine-learning, deep-learning, batchsize | 1,497,179,856 |
se_79751915 | stackoverflow | MACHINE_LEARNING | PyTorch XPU training loop memory leak despite explicit cleanup (gc.collect, torch.xpu.empty_cache) | PyTorch XPU training loop memory leak despite explicit cleanup (gc.collect, torch.xpu.empty_cache)
I’m training a RVC which use HIFI-GAN-style speech model on Intel XPU (PyTorch 2.3, oneAPI backend). During training, my GPU/XPU memory usage keeps growing with each batch until OOM, even though I explicitly delete tenso... | https://stackoverflow.com/questions/79751915/pytorch-xpu-training-loop-memory-leak-despite-explicit-cleanup-gc-collect-torc | machine-learning, deep-learning, pytorch | 1,756,660,623 |
se_75701948 | stackoverflow | MACHINE_LEARNING | How to merge many data frames to only one | How to merge many data frames to only one
I have directory that has many folders inside each folder has (images folder & labels text) and I want to combine them to one dataframe file by concatnating folders name with images name to make them uinque names .
The structuer of my directory like below :
$ tree
.
├── sampl... | https://stackoverflow.com/questions/75701948/how-to-merge-many-data-frames-to-only-one | python, json, pandas, dataframe, deep-learning | 1,678,492,427 |
se_42689345 | stackoverflow | MACHINE_LEARNING | Subset of Imagenet Dataset for image classification | Subset of Imagenet Dataset for image classification
I need an annotated dataset, subset of Imagenet, that includes square images of size: 224x224.
I tried Tiny Imagenet and Cifar-10, but they consist of quite smaller images and don't fit my needs.
Is there anything similar available? I cannot use the entire Imagenet... | https://stackoverflow.com/questions/42689345/subset-of-imagenet-dataset-for-image-classification | image, machine-learning, dataset, deep-learning, conv-neural-network | 1,489,045,023 |
se_79748706 | stackoverflow | MACHINE_LEARNING | Gradcam with ResNet-50 Error: The name "input_layer_1" is used 2 times in the model. All operation names should be unique | Gradcam with ResNet-50 Error: The name "input_layer_1" is used 2 times in the model. All operation names should be unique
I am new to the implementation of Gradcam, and having a trouble with it.
I have created a model
img_shape = (256, 256, 3)
base_model = ResNet50(include_top=False,
... | https://stackoverflow.com/questions/79748706/gradcam-with-resnet-50-error-the-name-input-layer-1-is-used-2-times-in-the-mo | deep-learning, resnet, gradienttape, gradcam | 1,756,362,044 |
se_79747243 | stackoverflow | MACHINE_LEARNING | KFold cross-validation in Keras: model not resetting between folds (MobileNet backbone) | KFold cross-validation in Keras: model not resetting between folds (MobileNet backbone)
I am trying to perform KFold cross-validation on a Keras model. The first fold runs exactly as expected, but from the second fold onwards the model doesn’t seem to reset. The training behaves strangely, as if the weights from the p... | https://stackoverflow.com/questions/79747243/kfold-cross-validation-in-keras-model-not-resetting-between-folds-mobilenet-ba | python, tensorflow, keras, deep-learning, neural-network | 1,756,236,458 |
se_79746857 | stackoverflow | MACHINE_LEARNING | Why does MATLAB selfAttentionLayer give different parameter counts for head/key-channel pairs with the same total key dimension? | Why does MATLAB selfAttentionLayer give different parameter counts for head/key-channel pairs with the same total key dimension?
I’m experimenting with the MathWorks example that inserts a multi-head self-attention layer into a simple CNN for the DigitDataset:
Link to example
layers = [
imageInputLayer([28 28 1])
... | https://stackoverflow.com/questions/79746857/why-does-matlab-selfattentionlayer-give-different-parameter-counts-for-head-key | matlab, deep-learning, conv-neural-network, self-attention, multihead-attention | 1,756,212,685 |
se_56818719 | stackoverflow | MACHINE_LEARNING | Getting error to fit a Conv1d to classify diabetic patients using the Pima Indian diabetes data set using keras in R | Getting error to fit a Conv1d to classify diabetic patients using the Pima Indian diabetes data set using keras in R
I am new to the machine learning field. I was using keras package in R to classify the diabetic individuals, using the Pima Indian diabetes dataset and fitting a Conv1d. I am not sure where I am doing t... | https://stackoverflow.com/questions/56818719/getting-error-to-fit-a-conv1d-to-classify-diabetic-patients-using-the-pima-india | r, machine-learning, deep-learning | 1,561,821,948 |
se_79745664 | stackoverflow | MACHINE_LEARNING | Layer "dense" expects 1 input(s), but it received 2 input tensors | Layer "dense" expects 1 input(s), but it received 2 input tensors
Environment
Raspberry Pi 4: 8 GB RAM
Relevant Dependencies:
keras 3.11.3
numpy 1.26.4
opencv-python 4.12.0.88
pillow 11.3.0
tensorflow 2.20.0
Issue
Trained MobileNetV... | https://stackoverflow.com/questions/79745664/layer-dense-expects-1-inputs-but-it-received-2-input-tensors | tensorflow, deep-learning, raspberry-pi, valueerror | 1,756,120,182 |
se_79744026 | stackoverflow | MACHINE_LEARNING | Ram Memory leak when scripting a Sampling Trainer for a Bert Encoder and LSTM Decoder Tensorflow on GPU | Ram Memory leak when scripting a Sampling Trainer for a Bert Encoder and LSTM Decoder Tensorflow on GPU
I wrote the module attached below. However, I notice a constant increase of RAM until I get an out of memory error. The code runs on CPU without a problem (except the slow training time). It can finish the first tra... | https://stackoverflow.com/questions/79744026/ram-memory-leak-when-scripting-a-sampling-trainer-for-a-bert-encoder-and-lstm-de | python, python-3.x, tensorflow, deep-learning, lstm | 1,755,927,646 |
se_79741908 | stackoverflow | MACHINE_LEARNING | Calculating the partial derivative of PyTorch model output with respect to neurons pre-activation | Calculating the partial derivative of PyTorch model output with respect to neurons pre-activation
I am working on neuron importance for ANNs (in a classification setting). A simple baseline is the partial derivative of the model output for the correct class with respect to the given neuron pre-activation. My goal is t... | https://stackoverflow.com/questions/79741908/calculating-the-partial-derivative-of-pytorch-model-output-with-respect-to-neuro | python, machine-learning, deep-learning, pytorch | 1,755,757,301 |
se_51433378 | stackoverflow | MACHINE_LEARNING | What does model.train() do in PyTorch? | What does model.train() do in PyTorch?
Does it call forward() in nn.Module? I thought when we call the model, forward method is being used.
Why do we need to specify train()? | https://stackoverflow.com/questions/51433378/what-does-model-train-do-in-pytorch | python, machine-learning, deep-learning, pytorch | 1,532,045,400 |
se_79621906 | stackoverflow | MACHINE_LEARNING | Error about attention in the last yolo version | Error about attention in the last yolo version
When I want to use YOLO12 in inference, I get this error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-16-65468ee2f515> in <cell line: 0>()
----> 1 ... | https://stackoverflow.com/questions/79621906/error-about-attention-in-the-last-yolo-version | python, deep-learning, pytorch, yolo, ultralytics | 1,747,239,904 |
se_71789376 | stackoverflow | MACHINE_LEARNING | How to convert yolo annotations to coco format. Json? | How to convert yolo annotations to coco format. Json?
I want to convert my labels in yolo format to coco format
I have tried
https://github.com/Taeyoung96/Yolo-to-COCO-format-converter
And
Pylabel
They all have a bugs.
I want to train on detectron 2 but it fails to load the dataset because of the wrong json file. | https://stackoverflow.com/questions/71789376/how-to-convert-yolo-annotations-to-coco-format-json | machine-learning, deep-learning, object-detection, data-annotations, annotation-processing | 1,649,368,498 |
se_79718146 | stackoverflow | MACHINE_LEARNING | JAX lax.scan: How to iterate over layers and memory slices simultaneously without dynamic indexing in a multi-layer RNN structure? | JAX lax.scan: How to iterate over layers and memory slices simultaneously without dynamic indexing in a multi-layer RNN structure?
I'm trying to implement a framework that manages RNN networks with an arbitrary number of layers (it's all part of a library I'm building based on jax/equinox), the problem is that I can't... | https://stackoverflow.com/questions/79718146/jax-lax-scan-how-to-iterate-over-layers-and-memory-slices-simultaneously-withou | python, deep-learning, recurrent-neural-network, jax, equinox | 1,753,766,278 |
se_79736455 | stackoverflow | MACHINE_LEARNING | Replacing WideResNet50 with EfficientNetV2-M in GLASS defect detection model causes Module layer2 not found in the model | Replacing WideResNet50 with EfficientNetV2-M in GLASS defect detection model causes Module layer2 not found in the model
I’m using the GLASS defect detection model and want to replace its default wideresnet50 backbone with efficientnetv2_m in shell/run-custom.sh.However, when I run
bash run-custom.sh
I get the follow... | https://stackoverflow.com/questions/79736455/replacing-wideresnet50-with-efficientnetv2-m-in-glass-defect-detection-model-cau | machine-learning, deep-learning, pytorch, computer-vision, artificial-intelligence | 1,755,263,394 |
se_79736231 | stackoverflow | MACHINE_LEARNING | How do I format my a tensorflow dataset for a multi output model? | How do I format my a tensorflow dataset for a multi output model?
I have an image dataset where each image has multiple categorical features that I want to predict. I am getting this error when trying to train:
ValueError: y_true and y_pred have different structures.
y_true: *
y_pred: ['*', '*', '*', '*']
Here's is m... | https://stackoverflow.com/questions/79736231/how-do-i-format-my-a-tensorflow-dataset-for-a-multi-output-model | python, tensorflow, machine-learning, keras, deep-learning | 1,755,246,327 |
se_55447901 | stackoverflow | MACHINE_LEARNING | ValueError: Error when checking target: expected dense_8 to have 4 dimensions, but got array with shape (37800, 10, 10) | ValueError: Error when checking target: expected dense_8 to have 4 dimensions, but got array with shape (37800, 10, 10)
I'm a beginner at machine learning. I am working on mnist dataset which I downloaded from kaggle. I am making this very first project by the help of a tutorial. But I'm facing this issue which I am u... | https://stackoverflow.com/questions/55447901/valueerror-error-when-checking-target-expected-dense-8-to-have-4-dimensions-b | machine-learning, deep-learning, mnist | 1,554,090,756 |
se_79653092 | stackoverflow | MACHINE_LEARNING | CNN Constant Predictions | CNN Constant Predictions
I’m building a Keras model based on MobileNetV2 for frame-level prediction of 6 human competencies. Each output head represents a competency and is a softmax over 100 classes (scores 0–99). The model takes in 224x224 RGB frames, normalized to [-1, 1] (compatible with MobileNetV2 preprocessing)... | https://stackoverflow.com/questions/79653092/cnn-constant-predictions | python, tensorflow, machine-learning, deep-learning, conv-neural-network | 1,749,051,612 |
se_41488279 | stackoverflow | MACHINE_LEARNING | Neural network always predicts the same class | Neural network always predicts the same class
I'm trying to implement a neural network that classifies images into one of the two discrete categories. The problem is, however, that it currently always predicts 0 for any input and I'm not really sure why.
Here's my feature extraction method:
def extract(file):
# ... | https://stackoverflow.com/questions/41488279/neural-network-always-predicts-the-same-class | python-3.x, numpy, neural-network, deep-learning, gradient-descent | 1,483,628,815 |
se_66750391 | stackoverflow | MACHINE_LEARNING | RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces) | RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces)
I am using Pytorch. I got this RuntimeError while evaluating a model. Any idea how to solve this? | https://stackoverflow.com/questions/66750391/runtimeerror-view-size-is-not-compatible-with-input-tensors-size-and-stride-a | python, machine-learning, deep-learning, pytorch, computer-vision | 1,616,431,812 |
se_54157205 | stackoverflow | MACHINE_LEARNING | Why Confusion Maxtrix and Model ACC are different | Why Confusion Maxtrix and Model ACC are different
Currently, we are building the Confusion Matrix using CNN, which is different from Model Acc.
Model ACC is 92.3% when 51% accuracy is calculated using the Confusion Matrix.
Which of the following should be true for Model ACC and Confusion Matrix in this case?
And ho... | https://stackoverflow.com/questions/54157205/why-confusion-maxtrix-and-model-acc-are-different | keras, deep-learning, conv-neural-network, confusion-matrix | 1,547,273,430 |
se_62986313 | stackoverflow | MACHINE_LEARNING | keras 2.4. producing completely different output than 2.3.1 | keras 2.4. producing completely different output than 2.3.1
I am trying to implement autoencoders. Using MNIST dataset, I am first encoding the images and then decoding them. When I use keras version 2.3.1 I am getting decoded Images very close to original but on using Keras 2.4.3 and no change to code I am getting co... | https://stackoverflow.com/questions/62986313/keras-2-4-producing-completely-different-output-than-2-3-1 | python, tensorflow, machine-learning, keras, deep-learning | 1,595,197,223 |
se_37407574 | stackoverflow | MACHINE_LEARNING | What do BACKEND and SCALE mean in data layer definition? | What do BACKEND and SCALE mean in data layer definition?
I'm new to Caffe and I am following MNIST handwritten digits recognize example.
When seeing
layer {
name: "mnist"
type: "Data"
transform_param {
scale: 0.00390625
}
data_param {
source: "mnist_train_lmdb"
backend: LMDB
batch_size: 64
... | https://stackoverflow.com/questions/37407574/what-do-backend-and-scale-mean-in-data-layer-definition | neural-network, protocol-buffers, deep-learning, caffe | 1,464,076,719 |
se_67770595 | stackoverflow | MACHINE_LEARNING | How to extract the hidden vector (the output of the ReLU after the third encoder layer) as the image representation | How to extract the hidden vector (the output of the ReLU after the third encoder layer) as the image representation
I am implementing an autoencoder using the Fashion MNIST dataset. The code for the encoder-
class MNISTClassifier(Model):
def __init__(self):
super(MNISTClassifier, self).__init__()
s... | https://stackoverflow.com/questions/67770595/how-to-extract-the-hidden-vector-the-output-of-the-relu-after-the-third-encoder | tensorflow, keras, deep-learning, tensorflow2.0, autoencoder | 1,622,451,050 |
se_79725054 | stackoverflow | MACHINE_LEARNING | RuntimeError in torch.cat during VACE-Wan2.1 inference: mask and video tensor shape mismatch | RuntimeError in torch.cat during VACE-Wan2.1 inference: mask and video tensor shape mismatch
I'm using the Wan2.1-VACE video generation model, and during inference I encountered a RuntimeError related to mismatched tensor shapes in a torch.cat operation inside the vace_latent() function.
From the debug output:
src_vid... | https://stackoverflow.com/questions/79725054/runtimeerror-in-torch-cat-during-vace-wan2-1-inference-mask-and-video-tensor-sh | python, machine-learning, deep-learning, pytorch, computer-vision | 1,754,318,209 |
se_79719714 | stackoverflow | MACHINE_LEARNING | Saving embeddings from encoder efficiently with fast random access | Saving embeddings from encoder efficiently with fast random access
I have embeddings (about 160 Million) that I created with a BERT-based encoder model.
Right now they are in a .pt format and takes about 500GB in the disk.
I want 2 things:
To save them in an efficient way if possible (minimum disk space as possible)
... | https://stackoverflow.com/questions/79719714/saving-embeddings-from-encoder-efficiently-with-fast-random-access | data-structures, deep-learning, nlp, word-embedding, encoder | 1,753,867,885 |
se_56640990 | stackoverflow | MACHINE_LEARNING | How to match the output shape of generator and the input shape of discriminator in GAN? | How to match the output shape of generator and the input shape of discriminator in GAN?
I am working on my first GANs model, I've followed Tensorflow's official documentation using MNIST dataset. I've run it smoothly. I tried to replace MNIST with my own dataset, I've prepared it to match the same size as MNIST: 28 * ... | https://stackoverflow.com/questions/56640990/how-to-match-the-output-shape-of-generator-and-the-input-shape-of-discriminator | python, tensorflow, keras, neural-network, deep-learning | 1,560,824,690 |
se_77237582 | stackoverflow | MACHINE_LEARNING | Highly imbalanced Alzheimer's Disease MRI image dataset | Highly imbalanced Alzheimer's Disease MRI image dataset
I am currently doing my final year project and I need your humble opinion. My dataset consists of 4 classes which contain :
Mild demented - 896 images
Moderate demented - 64 images
Non demented - 3200 images
Very Mild demented - 2240 images
As you can see, my... | https://stackoverflow.com/questions/77237582/highly-imbalanced-alzheimers-disease-mri-image-dataset | image, deep-learning, data-augmentation, imbalanced-data, smote | 1,696,512,546 |
se_71962563 | stackoverflow | MACHINE_LEARNING | How are the nodes/units in the output layer of NN assigned to the classes? | How are the nodes/units in the output layer of NN assigned to the classes?
I am learning deep Learning and I keep wondering how are the nodes/units in the output layer of NN assigned to the classes because we don't usually indicate manually which neuron/node to represent which class label? For e.g., for MNIST dataset ... | https://stackoverflow.com/questions/71962563/how-are-the-nodes-units-in-the-output-layer-of-nn-assigned-to-the-classes | deep-learning, neural-network | 1,650,591,498 |
se_79722074 | stackoverflow | MACHINE_LEARNING | MNIST multi digit prediction | MNIST multi digit prediction
I tried to train a model on mnist dataset. It's working fine for single digit prediction and I got 96.92% accuracy on test data too but I have everything but it's not working for multidigit.
even though I took an image with spacing in between and it was able to split and preprocess it prop... | https://stackoverflow.com/questions/79722074/mnist-multi-digit-prediction | python, machine-learning, deep-learning, mnist | 1,754,024,484 |
se_77200057 | stackoverflow | MACHINE_LEARNING | Test Accuracy and ConfMatrix dont match up? | Test Accuracy and ConfMatrix dont match up?
I'm doing the "hello world" project involving the MNIST dataset. But by test accuracy doesn't seem to match with the diagonal of my confusion matrix. I'm not sure if I have a bug somewhere that's causing this or if my accuracy function is not correct.
Here is the model:
clas... | https://stackoverflow.com/questions/77200057/test-accuracy-and-confmatrix-dont-match-up | python, deep-learning, neural-network, classification, mnist | 1,695,971,432 |
se_79559122 | stackoverflow | MACHINE_LEARNING | OSError: Qwen/Qwen2.5-VL-7B-Instruct does not appear to have files named model-00002-of-00005.safetensors despite having the file locally | OSError: Qwen/Qwen2.5-VL-7B-Instruct does not appear to have files named model-00002-of-00005.safetensors despite having the file locally
I'm trying to use the Qwen2.5-VL-7B model for my project, and I've downloaded a local file named model-00002-of-00005.safetensors. However, when I run my code, I encounter the follo... | https://stackoverflow.com/questions/79559122/oserror-qwen-qwen2-5-vl-7b-instruct-does-not-appear-to-have-files-named-model-0 | python, deep-learning, pytorch, fine-tuning, oserror | 1,744,003,354 |
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