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_79659981 | stackoverflow | MACHINE_LEARNING | How to use pyInstaller to package PyTorch code that includes JIT? | How to use pyInstaller to package PyTorch code that includes JIT?
The spec file I used is as follows, based on this discussion.
# -*- mode: python ; coding: utf-8 -*-
from PyInstaller.utils.hooks import collect_data_files
datas = []
datas += collect_data_files('triton', include_py_files=True)
datas += collect_data_f... | https://stackoverflow.com/questions/79659981/how-to-use-pyinstaller-to-package-pytorch-code-that-includes-jit | python, pytorch, pyinstaller | 1,749,539,855 |
se_77444485 | stackoverflow | MACHINE_LEARNING | Using positional encoding in pytorch | Using positional encoding in pytorch
Is there any built-in positional encoding in pytorch? Basically, I want to be able to specify the dimension of the encoding, and then be able to get the i'th encoding for every i. | https://stackoverflow.com/questions/77444485/using-positional-encoding-in-pytorch | python, deep-learning, pytorch, transformer-model | 1,699,437,475 |
se_79657483 | stackoverflow | MACHINE_LEARNING | num workers does not run in parallel | num workers does not run in parallel
from torch.utils.data import Dataset, DataLoader
import time
import multiprocessing as mp
import torch
class Sleep(Dataset):
def __len__(self): return 20
def __getitem__(self, i):
import time, os
time.sleep(1)
return os.getpid()
if __name__ == "__m... | https://stackoverflow.com/questions/79657483/num-workers-does-not-run-in-parallel | pytorch, pytorch-dataloader | 1,749,354,240 |
se_79655763 | stackoverflow | MACHINE_LEARNING | Efficiency of torch matrix operations on CPU | Efficiency of torch matrix operations on CPU
I am currently working on optimizing PyTorch code running on CPU. On CUDA, you can write fused multiple operators into specialized kernels to reduce memory transfers, avoid intermediate data allocations and thus, improve performance. Is it also possible to do this on CPU wi... | https://stackoverflow.com/questions/79655763/efficiency-of-torch-matrix-operations-on-cpu | optimization, pytorch, libtorch | 1,749,204,550 |
se_70816481 | stackoverflow | MACHINE_LEARNING | IndexError: index 89 is out of bounds for axis 0 with size 89 | IndexError: index 89 is out of bounds for axis 0 with size 89
I am getting this error but I don't understand how to solve it, can anyone please help?
I am trying to run a pre-implemented project on my own text dataset. I am using CUB 200-2011 bird dataset which had initially 11788 birds images and author model has bee... | https://stackoverflow.com/questions/70816481/indexerror-index-89-is-out-of-bounds-for-axis-0-with-size-89 | python, machine-learning, deep-learning, pytorch | 1,642,880,417 |
se_76985251 | stackoverflow | MACHINE_LEARNING | Determining PCELoss(weight=?) for a NN with 1 binary output class? | Determining PCELoss(weight=?) for a NN with 1 binary output class?
I have a neural network for classification with 1 binary output class. The training dataset is unbalanced. 97% for 0 or False, 3% for 1 or True.
I'm using BCELoss for the loss function. What do I send in the BCELoss(weight= ???) argument? How do calc... | https://stackoverflow.com/questions/76985251/determining-pcelossweight-for-a-nn-with-1-binary-output-class | python, pytorch | 1,693,093,992 |
se_63357718 | stackoverflow | MACHINE_LEARNING | ImportError: TensorBoard logging requires TensorBoard version 1.15 or above | ImportError: TensorBoard logging requires TensorBoard version 1.15 or above
I follow the tutorials in pytorch.org
It occurs error：TensorBoard logging requires TensorBoard version 1.15 or above,but I have install TensorBoard already.
Here is the code:
#from torch.utils.tensorboard import SummaryWriter
from tensorboardX... | https://stackoverflow.com/questions/63357718/importerror-tensorboard-logging-requires-tensorboard-version-1-15-or-above | pytorch, tensorboard, tensorboardx | 1,597,147,364 |
se_79657416 | stackoverflow | MACHINE_LEARNING | Loading and training data on Sagemaker with a Self-supervised pre-training model | Loading and training data on Sagemaker with a Self-supervised pre-training model
I'm testing a Self-supervise pre-training model, independently of the model I'm getting the same Error. My environment is Jupiter Labs for AWS Sagemaker, the problem comes when, using args and trying to load the data (either from an S3 bu... | https://stackoverflow.com/questions/79657416/loading-and-training-data-on-sagemaker-with-a-self-supervised-pre-training-model | python, machine-learning, amazon-s3, pytorch, amazon-sagemaker | 1,749,341,448 |
se_79658001 | stackoverflow | MACHINE_LEARNING | Need Assistance with Fine-tuning my Content Moderation Neural Network with RoBERTa. (Dataset: Jigsaw) | Need Assistance with Fine-tuning my Content Moderation Neural Network with RoBERTa. (Dataset: Jigsaw)
I can't quite figure out how to fine-tune my neural network with jigsaw and make it a multi-classifier rather than a binary-classifier (multiple types of output rather than just positive and negative) and need assista... | https://stackoverflow.com/questions/79658001/need-assistance-with-fine-tuning-my-content-moderation-neural-network-with-rober | python, pytorch, artificial-intelligence, data-science | 1,749,400,310 |
se_79658051 | stackoverflow | MACHINE_LEARNING | Why PyTorch softmax computes individual weighted scores differently | Why PyTorch softmax computes individual weighted scores differently
I have a simple tensor
test_tensor =torch.tensor([ [.1, .2, .3],[.4, .5, .6]])
when I use softmax
weights = torch.softmax ( test_tensor, dim = -1), I get:
tensor([[0.3006, 0.3322, 0.3672],
[0.3006, 0.3322, 0.3672]])
I thought if I do this man... | https://stackoverflow.com/questions/79658051/why-pytorch-softmax-computes-individual-weighted-scores-differently | pytorch, softmax | 1,749,404,293 |
se_79597119 | stackoverflow | MACHINE_LEARNING | How to reduce GPU memory usage when running Stable Diffusion with HuggingFace Diffusers? | How to reduce GPU memory usage when running Stable Diffusion with HuggingFace Diffusers?
I'm trying to run Stable Diffusion using HuggingFace's diffusers library, but I keep getting CUDA out of memory errors on my RTX 3060 (12GB VRAM). I'm using the standard StableDiffusionPipeline from the "CompVis/stable-diffusion-v... | https://stackoverflow.com/questions/79597119/how-to-reduce-gpu-memory-usage-when-running-stable-diffusion-with-huggingface-di | python, machine-learning, deep-learning, pytorch, stable-diffusion | 1,745,866,176 |
se_79656972 | stackoverflow | MACHINE_LEARNING | How to speed up a custom pytorch activation function? | How to speed up a custom pytorch activation function?
I wrote a custom activation function in torch, but it is painfully slow:
class NoisyRelu(nn.Module):
def __init__(self):
super(NoisyRelu, self).__init__()
def forward(self, x: torch.Tensor)-> torch.Tensor:
relu_result = F.relu(x)
return relu_result... | https://stackoverflow.com/questions/79656972/how-to-speed-up-a-custom-pytorch-activation-function | pytorch, activation-function | 1,749,302,106 |
se_55411921 | stackoverflow | MACHINE_LEARNING | Is there a pytorch method to check the number of cpus? | Is there a pytorch method to check the number of cpus?
I can use this torch.cuda.device_count() to check the number of GPUs. I was wondering if there was something equivalent to check the number of CPUs. | https://stackoverflow.com/questions/55411921/is-there-a-pytorch-method-to-check-the-number-of-cpus | python, neural-network, deep-learning, pytorch | 1,553,842,208 |
se_52750622 | stackoverflow | MACHINE_LEARNING | How to install pytorch on Power 8 or PPC64 machine? | How to install pytorch on Power 8 or PPC64 machine?
I am trying to install pytorch using conda on power 8 IBM machine. Although, I read articles from IBM blog, I couldn't install with success because I got stuck with compiling magma. | https://stackoverflow.com/questions/52750622/how-to-install-pytorch-on-power-8-or-ppc64-machine | pytorch, powerpc | 1,539,218,969 |
se_79537819 | stackoverflow | MACHINE_LEARNING | What is the command to install pytorch with cuda 12.8? | What is the command to install pytorch with cuda 12.8?
I notice on the website of pytorch (https://pytorch.org/get-started/locally/) there is a command for cuda 12.6 but not for the latest version of cuda which is 12.8.
Is there a command specifically for cuda 12.8?
Will the command for cuda 12.6 work if I'm using cud... | https://stackoverflow.com/questions/79537819/what-is-the-command-to-install-pytorch-with-cuda-12-8 | python, pytorch | 1,743,049,102 |
se_75305358 | stackoverflow | MACHINE_LEARNING | RuntimeError: expected scalar type Float but found Half in Stable Diffusion | RuntimeError: expected scalar type Float but found Half in Stable Diffusion
I am currently using Kangle Kurnel using Python version 3.7
It kept saying RuntimeError: expected scalar type Float but found Half
installed packs
accelerate 0.12.0
torch 1.9.1+cu111
t... | https://stackoverflow.com/questions/75305358/runtimeerror-expected-scalar-type-float-but-found-half-in-stable-diffusion | python, error-handling, pytorch, artificial-intelligence, stable-diffusion | 1,675,222,115 |
se_79532275 | stackoverflow | MACHINE_LEARNING | Why does torch import complain about numpy version | Why does torch import complain about numpy version
I created a virtual environment on MacOS and installed pytorch with pip:
python -m env torch-env
source torch-env/bin/activate
pip install torch torchvision torchaudio
Launching python and importing torch fails, however:
Python 3.11.2 (main, Mar 5 2023, 23:08:47) [C... | https://stackoverflow.com/questions/79532275/why-does-torch-import-complain-about-numpy-version | python, python-3.x, numpy, pytorch | 1,742,854,410 |
se_79647152 | stackoverflow | MACHINE_LEARNING | AttributeError: module 'torch' has no attribute 'get_default_device' when using SentenceTransformer | AttributeError: module 'torch' has no attribute 'get_default_device' when using SentenceTransformer
I'm working on a Python NLP project and using the following library versions:
PyTorch 2.2.2
Transformers 4.52.3
Sentence-Transformers 4.1.0
When I run this code:
from sentence_transformers import Sentenc... | https://stackoverflow.com/questions/79647152/attributeerror-module-torch-has-no-attribute-get-default-device-when-using | python, pytorch, huggingface-transformers, sentence-transformers | 1,748,747,871 |
se_69785483 | stackoverflow | MACHINE_LEARNING | Why I face the "UserWarning: The NumPy module was reloaded (imported a second time)..." when I run pytorch code? | Why I face the "UserWarning: The NumPy module was reloaded (imported a second time)..." when I run pytorch code?
My environment: Anaconda, Python 3.8.8, Pytorch1.8.1+cu111
Question: When I run the code below I get the following error:
UserWarning: "D:\Anaconda3\envs\pytorch\lib\site-packages\torch\cuda\amp\a... | https://stackoverflow.com/questions/69785483/why-i-face-the-userwarning-the-numpy-module-was-reloaded-imported-a-second-ti | python, numpy, pytorch | 1,635,672,399 |
se_76177216 | stackoverflow | MACHINE_LEARNING | How is scaled_dot_product_attention meant to be used with cached keys/values in causal LM? | How is scaled_dot_product_attention meant to be used with cached keys/values in causal LM?
I'm implementing a transformer and I have everything working, including attention using the new scaled_dot_product_attention from PyTorch 2.0. I'll only be doing causal attention, however, so it seems like it makes sense to use ... | https://stackoverflow.com/questions/76177216/how-is-scaled-dot-product-attention-meant-to-be-used-with-cached-keys-values-in | pytorch, language-model, self-attention | 1,683,232,761 |
se_75385142 | stackoverflow | MACHINE_LEARNING | tokenizer.push_to_hub(repo_name) is not working | tokenizer.push_to_hub(repo_name) is not working
I'm trying to puch my tokonizer to my huggingface repo...
it consist of the model vocab.Json (I'm making a speech recognition model)
My code:
vocab_dict["|"] = vocab_dict[" "]
del vocab_dict[" "]
vocab_dict["[UNK]"] = len(vocab_dict)
vocab_dict["[PAD]"] = len(vocab_dict)... | https://stackoverflow.com/questions/75385142/tokenizer-push-to-hubrepo-name-is-not-working | python, pytorch, huggingface-transformers, huggingface-tokenizers, huggingface | 1,675,855,768 |
se_79652783 | stackoverflow | MACHINE_LEARNING | no_grad causing problem in Pytorch NN model | no_grad causing problem in Pytorch NN model
I'm building regression neural network model for my NLP data.
But can't get through this error: RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn
What should I do?
ChatGPT says:
it's requires_grad=False somewhere in the code which isn't tr... | https://stackoverflow.com/questions/79652783/no-grad-causing-problem-in-pytorch-nn-model | python, pytorch, nlp | 1,749,040,793 |
se_79650016 | stackoverflow | MACHINE_LEARNING | Neural Network model in PyTorch prediction problem for anomaly detection in a simulated irrigation system | Neural Network model in PyTorch prediction problem for anomaly detection in a simulated irrigation system
I'm working on my final studies project, which is detecting anomalies in an irrigation system.
We simulated the irrigation network on a limited environment as you can see in the photo below.the model we created
Th... | https://stackoverflow.com/questions/79650016/neural-network-model-in-pytorch-prediction-problem-for-anomaly-detection-in-a-si | python, machine-learning, pytorch, artificial-intelligence | 1,748,882,118 |
se_79646476 | stackoverflow | MACHINE_LEARNING | some_operation().to(device) vs to(device).some_operation() | some_operation().to(device) vs to(device).some_operation()
Just found I randomly coded some_data.unsqueeze(0).to(device) and some_data.to(device).unsqueeze(0).
If I recall correctly, torch.Tensor.to involves data transferring, something like cudaMemcpyHostToDevice?.
Which makes me wonder, suppose device is set to GPU,... | https://stackoverflow.com/questions/79646476/some-operation-todevice-vs-todevice-some-operation | python, pytorch | 1,748,683,097 |
se_61633944 | stackoverflow | MACHINE_LEARNING | I am getting Attribute error as 'int' object has no attribute 'to' | I am getting Attribute error as 'int' object has no attribute 'to'
I am writing a python code in Kaggle notebook for Image Classification. In the training part, I am getting an error
AttributeError Traceback (most recent call last)
<ipython-input-22-052723d8ce9d> in <module... | https://stackoverflow.com/questions/61633944/i-am-getting-attribute-error-as-int-object-has-no-attribute-to | python, pytorch | 1,588,764,249 |
se_79639173 | stackoverflow | MACHINE_LEARNING | LSTM model produces single output for full batch of training data | LSTM model produces single output for full batch of training data
My training set has dimensions [7000, 2], but my output has single number in it. I want to configure the model to understand that "I want one output for each row in X_train", but I don't know how to do that. In other words, my input has 7000 rows and 2 ... | https://stackoverflow.com/questions/79639173/lstm-model-produces-single-output-for-full-batch-of-training-data | pytorch, lstm, recurrent-neural-network | 1,748,271,845 |
se_79641308 | stackoverflow | MACHINE_LEARNING | Understanding PyTorch gradients and backward function, when backwarding more than once | Understanding PyTorch gradients and backward function, when backwarding more than once
I'm trying to add more than one generator training step per cycle to a GAN, i.e. I want my Generator to update its parameters n times every m updates of the Discriminator, where n > m.
I wrote this piece of code:
for epoch in range(... | https://stackoverflow.com/questions/79641308/understanding-pytorch-gradients-and-backward-function-when-backwarding-more-tha | python, pytorch, generative-adversarial-network | 1,748,387,042 |
se_70148547 | stackoverflow | MACHINE_LEARNING | WSL2 Pytorch - RuntimeError: No CUDA GPUs are available with RTX3080 | WSL2 Pytorch - RuntimeError: No CUDA GPUs are available with RTX3080
I have been struggling for day to make torch work on WSL2 using an RTX 3080.
I Installed the CUDA-toolkit version 11.3
Running nvcc -V returns this :
nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Su... | https://stackoverflow.com/questions/70148547/wsl2-pytorch-runtimeerror-no-cuda-gpus-are-available-with-rtx3080 | pytorch | 1,638,144,575 |
se_73471929 | stackoverflow | MACHINE_LEARNING | How to use OneCycleLR? | How to use OneCycleLR?
I want to train on CIFAR-10, suppose for 200 epochs.
This is my optimizer:
optimizer = optim.Adam([x for x in model.parameters() if x.requires_grad], lr=0.001)
I want to use OneCycleLR as scheduler. Now, according to the documentation, these are the parameters of OneCycleLR:
torch.optim.lr_sched... | https://stackoverflow.com/questions/73471929/how-to-use-onecyclelr | optimization, deep-learning, neural-network, pytorch, learning-rate | 1,661,338,702 |
se_57977880 | stackoverflow | MACHINE_LEARNING | Testing that I've installed PyTorch correctly | Testing that I've installed PyTorch correctly
I have installed the PyTorch. How can I test in my Python script whether the installation is correct, e.g., whether it can enable CUDA or not, etc? | https://stackoverflow.com/questions/57977880/testing-that-ive-installed-pytorch-correctly | deep-learning, pytorch | 1,568,735,406 |
se_79134990 | stackoverflow | MACHINE_LEARNING | Fast AI Siamese model not improving | Fast AI Siamese model not improving
So I was following this tutorial: Fast Ai Siamese, however after I completed it, I got 50% accuracy. I tried loads of things, but nothing worked. So the only place where I think the problem could be is in the Siamese implementation itself, but I have little experience with fast.ai a... | https://stackoverflow.com/questions/79134990/fast-ai-siamese-model-not-improving | machine-learning, pytorch, computer-vision, fast-ai, siamese-network | 1,730,146,664 |
se_79638455 | stackoverflow | MACHINE_LEARNING | Torch: how to insert a tensor into another tensor at certain index | Torch: how to insert a tensor into another tensor at certain index
I have a padded tensor X with shape (B, T1, C) and a padded tensor Y with shape (B, T2, C), I also know the sample lengths L for X. I want to insert the samples of X into Y at certain index I and pad at the end.
For example, if I = 5, the goal of the t... | https://stackoverflow.com/questions/79638455/torch-how-to-insert-a-tensor-into-another-tensor-at-certain-index | python, indexing, pytorch, tensor | 1,748,243,165 |
se_70906050 | stackoverflow | MACHINE_LEARNING | How many num_workers in DataLoader? | How many num_workers in DataLoader?
I have a machine with 1500 Gb of ram and 112 cores but no GPU. I would like to know how to calculate suitable number of num_workers in DataLoader and batch size.
I have to make the inference with Inception-v3(pytorch) on 80,000,000 images.
I tried with a batch size of 30k and num_wo... | https://stackoverflow.com/questions/70906050/how-many-num-workers-in-dataloader | python, machine-learning, deep-learning, pytorch | 1,643,463,981 |
se_71639484 | stackoverflow | MACHINE_LEARNING | NaN error during backpropagation of torch.sqrt() even though an epsilon is added inside the square root | NaN error during backpropagation of torch.sqrt() even though an epsilon is added inside the square root
I am training a neural network with custom loss function that calls torch.sqrt() at one point. To avoid getting NaN gradients during backpropagation, I add a small epsilon value inside the square root. However, the ... | https://stackoverflow.com/questions/71639484/nan-error-during-backpropagation-of-torch-sqrt-even-though-an-epsilon-is-added | pytorch, nan, backpropagation | 1,648,408,243 |
se_79628802 | stackoverflow | MACHINE_LEARNING | Why is device_map="xpu" insufficient VRAM when using madlad400-3b-mt in Pytorch? | Why is device_map="xpu" insufficient VRAM when using madlad400-3b-mt in Pytorch?
1.Follow the example in this link https://huggingface.co/google/madlad400-3b-mt
2.Using AUTO does not seem to work on XPU, but it can run normally on CPU
3.What am I missing? How can I get it to work properly on the XPU?
import... | https://stackoverflow.com/questions/79628802/why-is-device-map-xpu-insufficient-vram-when-using-madlad400-3b-mt-in-pytorch | pytorch, intel-pytorch, xpu | 1,747,659,572 |
se_79584215 | stackoverflow | MACHINE_LEARNING | How to select certain indices for multiple dimensions of a PyTorch tensor? | How to select certain indices for multiple dimensions of a PyTorch tensor?
I have a situation where I need to add one PyTorch tensor to parts of another tensor. An example is like this:
import torch
x = torch.randn([10, 7, 128, 128]) # [batch, channel, height, width]
# In the actual program, batch_idx and channel_i... | https://stackoverflow.com/questions/79584215/how-to-select-certain-indices-for-multiple-dimensions-of-a-pytorch-tensor | python, pytorch | 1,745,221,626 |
se_78746073 | stackoverflow | MACHINE_LEARNING | How to solve "Torch was not compiled with flash attention" warning? | How to solve "Torch was not compiled with flash attention" warning?
I am using the Vision Transformer as part of the CLIP model and I keep getting the following warning:
..\site-packages\torch\nn\functional.py:5504: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at ..\aten\s... | https://stackoverflow.com/questions/78746073/how-to-solve-torch-was-not-compiled-with-flash-attention-warning | pytorch, self-attention, vision-transformer | 1,720,950,911 |
se_66130547 | stackoverflow | MACHINE_LEARNING | What is the difference between 'torch.backends.cudnn.deterministic=True' and 'torch.set_deterministic(True)'? | What is the difference between 'torch.backends.cudnn.deterministic=True' and 'torch.set_deterministic(True)'?
My network includes torch.nn.MaxPool3d which throw a RuntimeError when the cudnn deterministic flag is on according to the PyTorch docs (version 1.7 - https://pytorch.org/docs/stable/generated/... | https://stackoverflow.com/questions/66130547/what-is-the-difference-between-torch-backends-cudnn-deterministic-true-and-to | python, pytorch, deterministic, reproducible-research | 1,612,927,930 |
se_55097671 | stackoverflow | MACHINE_LEARNING | How to save and load random number generator state in Pytorch? | How to save and load random number generator state in Pytorch?
I am training a DL model in Pytorch, and want to train my model in a deterministic way.
As written in this official guide, I set random seeds like this:
np.random.seed(0)
torch.manual_seed(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.... | https://stackoverflow.com/questions/55097671/how-to-save-and-load-random-number-generator-state-in-pytorch | python, pytorch, random-seed, reproducible-research | 1,552,292,229 |
se_79633395 | stackoverflow | MACHINE_LEARNING | Why am I getting the error: one of the variables needed for gradient computation has been modified by an inplace operation while running backward | Why am I getting the error: one of the variables needed for gradient computation has been modified by an inplace operation while running backward
I am working on my YOLO model. When I try to train my model with the code below an error occured
def main():
# Initialize model, loss, and optimizer
model = Yolov5(v... | https://stackoverflow.com/questions/79633395/why-am-i-getting-the-error-one-of-the-variables-needed-for-gradient-computation | pytorch, loss, yolov5, in-place | 1,747,903,551 |
se_79631762 | stackoverflow | MACHINE_LEARNING | Error in PyTorch when trying to create a generative AI (autoregression) Model | Error in PyTorch when trying to create a generative AI (autoregression) Model
I'm trying to build an AI Model, but am getting this error:
Traceback (most recent call last):
File "F:\Pendrive\!!! Pivate !!!\Other\Other\Private\AI\PyTorch\Model_1\main.py", line 20, in <module>
model.pretrain_on_corpus(
File "F:\... | https://stackoverflow.com/questions/79631762/error-in-pytorch-when-trying-to-create-a-generative-ai-autoregression-model | python, machine-learning, error-handling, pytorch, artificial-intelligence | 1,747,822,302 |
se_79631387 | stackoverflow | MACHINE_LEARNING | Discrepancy in number of elements outputted by torch Dataset and DataLoader | Discrepancy in number of elements outputted by torch Dataset and DataLoader
I have a custom Subset:
class TestSubset2(Subset):
def __init__(self, dataset, indices, days=False):
super().__init__(dataset, indices)
self.days = days
def __getitem__(self, idx):
original_idx = self.indices[id... | https://stackoverflow.com/questions/79631387/discrepancy-in-number-of-elements-outputted-by-torch-dataset-and-dataloader | python, pytorch, dataset, pytorch-dataloader | 1,747,791,719 |
se_79025552 | stackoverflow | MACHINE_LEARNING | PyTorch: difference between reshape() and view() method | PyTorch: difference between reshape() and view() method
What is the difference between reshape and view method and why do we need and I am using pytorch tensors and working on changing the shape of data then I came to know these two functions. what are the affects on memory which consumes the more memory and which is ... | https://stackoverflow.com/questions/79025552/pytorch-difference-between-reshape-and-view-method | python, arrays, pytorch, dataset | 1,727,326,451 |
se_79628713 | stackoverflow | MACHINE_LEARNING | torch.cuda.device_count() return 0 when torch.cuda.is_available() return True in jupyter notebook | torch.cuda.device_count() return 0 when torch.cuda.is_available() return True in jupyter notebook
I got an error in jupyternotebook said that
RuntimeError: Attempting to deserialize object on CUDA device 0 but torch.cuda.device_count() is 0. Please use torch.load with map_location to map your storages to an existing d... | https://stackoverflow.com/questions/79628713/torch-cuda-device-count-return-0-when-torch-cuda-is-available-return-true-in | python, machine-learning, jupyter-notebook, pytorch, cuda | 1,747,656,598 |
se_46595157 | stackoverflow | MACHINE_LEARNING | How to apply the torch.inverse() function of PyTorch to every sample in the batch? | How to apply the torch.inverse() function of PyTorch to every sample in the batch?
This may seem like a basic question, but I am unable to work it through.
In the forward pass of my neural network, I have an output tensor of shape 8x3x3, where 8 is my batch size. We can assume each 3x3 tensor to be a non-singular ma... | https://stackoverflow.com/questions/46595157/how-to-apply-the-torch-inverse-function-of-pytorch-to-every-sample-in-the-batc | python, pytorch | 1,507,239,405 |
se_58206286 | stackoverflow | MACHINE_LEARNING | Multilabel classification with class imbalance in Pytorch | Multilabel classification with class imbalance in Pytorch
I have a multilabel classification problem, which I am trying to solve with CNNs in Pytorch. I have 80,000 training examples and 7900 classes; every example can belong to multiple classes at the same time, mean number of classes per example is 130.
The proble... | https://stackoverflow.com/questions/58206286/multilabel-classification-with-class-imbalance-in-pytorch | pytorch, multilabel-classification, imbalanced-data | 1,570,036,657 |
se_70097798 | stackoverflow | MACHINE_LEARNING | Does number of parameters and FLOPS change when converting a model from PyTorch to ONNX or TensorRT format? | Does number of parameters and FLOPS change when converting a model from PyTorch to ONNX or TensorRT format?
Does number of parameters and FLOPS (float operations per second) change when converting a model from PyTorch to ONNX or TensorRT format? | https://stackoverflow.com/questions/70097798/does-number-of-parameters-and-flops-change-when-converting-a-model-from-pytorch | deep-learning, pytorch, onnx, tensorrt | 1,637,763,821 |
se_77183339 | stackoverflow | MACHINE_LEARNING | Installing torch with GPU support but without downloading 3 GB of duplicated siloed CUDA libraries? | Installing torch with GPU support but without downloading 3 GB of duplicated siloed CUDA libraries?
I'm trying to make CUDA containers for DNN less heavy. PyTorch goes against my efforts, as it seems to come bundled with its own siloed copy of a large subset of CUDA libraries. But what if we have them already (possibl... | https://stackoverflow.com/questions/77183339/installing-torch-with-gpu-support-but-without-downloading-3-gb-of-duplicated-sil | python, pip, pytorch, gpu | 1,695,761,553 |
se_79630622 | stackoverflow | MACHINE_LEARNING | "UserWarning: 'pin_memory' argument is set as true but no accelerator is found, then device pinned memory won't be used." | "UserWarning: 'pin_memory' argument is set as true but no accelerator is found, then device pinned memory won't be used."
I am trying to use EasyOCR,
reader = easyocr.Reader(['en'], gpu=False)
def read_sign(sign):
result = reader.readtext(sign)
return 'STOP' in result`
However while it ... | https://stackoverflow.com/questions/79630622/userwarning-pin-memory-argument-is-set-as-true-but-no-accelerator-is-found | python, pytorch, ocr, torchvision, easyocr | 1,747,750,217 |
se_67311527 | stackoverflow | MACHINE_LEARNING | How to set GPU count to 0 using os.environ['CUDA_VISIBLE_DEVICES'] =""? | How to set GPU count to 0 using os.environ['CUDA_VISIBLE_DEVICES'] =""?
So I have the following GPU configured in my system:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 461.33 Driver Version: 461.33 CUDA Version: 11.2 |
|---------------... | https://stackoverflow.com/questions/67311527/how-to-set-gpu-count-to-0-using-os-environcuda-visible-devices | python-3.x, pytorch, nvidia, python-os | 1,619,674,373 |
se_79629787 | stackoverflow | MACHINE_LEARNING | What is the currently recommended way to install Pytorch with CUDA enabled using conda? | What is the currently recommended way to install Pytorch with CUDA enabled using conda?
Pytorch official website used to have an installation option using conda (see printscreen in this answer: https://stackoverflow.com/a/51229368/1273751)
But currently no conda option is available:
Nevertheless, there still is pytor... | https://stackoverflow.com/questions/79629787/what-is-the-currently-recommended-way-to-install-pytorch-with-cuda-enabled-using | python, pytorch, anaconda, conda | 1,747,715,851 |
se_79629559 | stackoverflow | MACHINE_LEARNING | How to format input data for Pytorch? | How to format input data for Pytorch?
I have written a conv. neural network from scratch before, but I've decided to use Pytorch for its speed. However, I could not find documentation as to how to format for the conv2d layer. In general, there seems to be a lot of overheads and wrappers which prevents me from viewing ... | https://stackoverflow.com/questions/79629559/how-to-format-input-data-for-pytorch | python, pytorch, conv-neural-network | 1,747,693,987 |
se_78328401 | stackoverflow | MACHINE_LEARNING | libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive | libtorch_cpu.so: undefined symbol: iJIT_IsProfilingActive
I have created this Conda environment:
conda env create -f environment.yml
The environment.yml file:
name: deep3d_pytorch
channels:
- pytorch
- conda-forge
- defaults
dependencies:
- python=3.6
- pytorch=1.6.0
- torchvision=0.7.0
- numpy=1.18.1
... | https://stackoverflow.com/questions/78328401/libtorch-cpu-so-undefined-symbol-ijit-isprofilingactive | pytorch, anaconda, conda, anaconda3 | 1,713,184,189 |
se_63218710 | stackoverflow | MACHINE_LEARNING | RuntimeError("grad can be implicitly created only for scalar outputs") | RuntimeError("grad can be implicitly created only for scalar outputs")
I have following code for train function for training an A3C.
I am stuck with following error.
RuntimeError("grad can be implicitly created only for scalar outputs")
at line (policy_loss + 0.5 * value_loss).backward()
Here is my code, ca... | https://stackoverflow.com/questions/63218710/runtimeerrorgrad-can-be-implicitly-created-only-for-scalar-outputs | python, pytorch, reinforcement-learning | 1,596,387,349 |
se_60987997 | stackoverflow | MACHINE_LEARNING | Why `torch.cuda.is_available()` returns False even after installing pytorch with cuda? | Why `torch.cuda.is_available()` returns False even after installing pytorch with cuda?
On a Windows 10 PC with an NVidia GeForce 820M
I installed CUDA 9.2 and cudnn 7.1 successfully,
and then installed PyTorch using the instructions at pytorch.org:
pip install torch==1.4.0+cu92 torchvision==0.5.0+cu92 -f https://downl... | https://stackoverflow.com/questions/60987997/why-torch-cuda-is-available-returns-false-even-after-installing-pytorch-with | python, pytorch | 1,585,818,739 |
se_79226995 | stackoverflow | MACHINE_LEARNING | Why is (remote) Jupyter busy during ML training, but not actually doing anything? | Why is (remote) Jupyter busy during ML training, but not actually doing anything?
I am training an ML model with PyTorch on my own dedicated remote server, using Jupyter as my IDE.
Around 120 epochs (about 2 hours into training), the Jupyter cell stops updating the output, but the status bar still says busy as the ker... | https://stackoverflow.com/questions/79226995/why-is-remote-jupyter-busy-during-ml-training-but-not-actually-doing-anything | machine-learning, jupyter-notebook, pytorch | 1,732,629,311 |
se_64987430 | stackoverflow | MACHINE_LEARNING | What exactly does the forward function output in Pytorch? | What exactly does the forward function output in Pytorch?
This example is taken verbatim from the PyTorch Documentation. Now I do have some background on Deep Learning in general and know that it should be obvious that the forward call represents a forward pass, passing through different layers and finally reaching th... | https://stackoverflow.com/questions/64987430/what-exactly-does-the-forward-function-output-in-pytorch | python, machine-learning, neural-network, pytorch | 1,606,224,078 |
se_79504951 | stackoverflow | MACHINE_LEARNING | PyTorch Checkpointing Error: Recomputed Tensor Metadata Mismatch in Global Representation with Extra Sampling | PyTorch Checkpointing Error: Recomputed Tensor Metadata Mismatch in Global Representation with Extra Sampling
I’m working on a PyTorch model where I compute a “global representation” through a forward pipeline. This pipeline is subsequently used in an extra sampling procedure later on in the network. When I compute th... | https://stackoverflow.com/questions/79504951/pytorch-checkpointing-error-recomputed-tensor-metadata-mismatch-in-global-repre | python, pytorch, autograd, checkpointing, automatic-mixed-precision | 1,741,816,895 |
se_73180675 | stackoverflow | MACHINE_LEARNING | Is there any "better way" to train a quadruped to walk using reinforcement Learning | Is there any "better way" to train a quadruped to walk using reinforcement Learning
I have been chasing this problem of using RL to train a quadruped to walk. But have got NO noteworthy success. Following are the Details of the GYM ENV I am using.
Sim: pybullet
env.action_space = box(shape=(12,), upper = 1... | https://stackoverflow.com/questions/73180675/is-there-any-better-way-to-train-a-quadruped-to-walk-using-reinforcement-learn | pytorch, ros, reinforcement-learning, stable-baselines | 1,659,241,764 |
se_79619583 | stackoverflow | MACHINE_LEARNING | Pytorch - torchvision model getting different results in python and kotlin | Pytorch - torchvision model getting different results in python and kotlin
I have a torchvision model which is mobilenet without the classification head to use as a similarity search. I have saved it as a torchvision model. When I use it within python with the similarity search it gets the right result but within kotl... | https://stackoverflow.com/questions/79619583/pytorch-torchvision-model-getting-different-results-in-python-and-kotlin | python, kotlin, machine-learning, pytorch, torchvision | 1,747,137,143 |
se_79623585 | stackoverflow | MACHINE_LEARNING | YOLOv8 RuntimeError: “could not create a primitive” on CPU using PyTorch | YOLOv8 RuntimeError: “could not create a primitive” on CPU using PyTorch
I'm trying to run YOLOv8 inference using Ultralytics on CPU, but I get a RuntimeError: could not create a primitive. I'm using Windows and working in a virtual environment with PyTorch. I'm new to YOLO and would appreciate help understanding this... | https://stackoverflow.com/questions/79623585/yolov8-runtimeerror-could-not-create-a-primitive-on-cpu-using-pytorch | python, pytorch, ultralytics | 1,747,319,427 |
se_79623038 | stackoverflow | MACHINE_LEARNING | PyCharm 2025.1 Jupyter kernel fails on import torch with ImportError: libnccl.so.2, but same virtual-env works in terminal | PyCharm 2025.1 Jupyter kernel fails on import torch with ImportError: libnccl.so.2, but same virtual-env works in terminal
I am running into the weirdest error.
Using PyCharm's Jupyter Notebook IDE (2025.1) I get the following error when I run import torch
--------------------------------------------------------------... | https://stackoverflow.com/questions/79623038/pycharm-2025-1-jupyter-kernel-fails-on-import-torch-with-importerror-libnccl-so | pytorch, pycharm, cuda, jetbrains-ide | 1,747,302,287 |
se_53972159 | stackoverflow | MACHINE_LEARNING | How does Pytorch's "Fold" and "Unfold" work? | How does Pytorch's "Fold" and "Unfold" work?
I've gone through the official doc. I'm having a hard time understanding what this function is used for and how it works. Can someone explain this in layman's terms? | https://stackoverflow.com/questions/53972159/how-does-pytorchs-fold-and-unfold-work | python, machine-learning, deep-learning, computer-vision, pytorch | 1,546,107,254 |
se_42480111 | stackoverflow | MACHINE_LEARNING | How do I print the model summary in PyTorch? | How do I print the model summary in PyTorch?
How do I print the summary of a model in PyTorch like what model.summary() does in Keras:
Model Summary:
____________________________________________________________________________________________________
Layer (type) Output Shape Param # C... | https://stackoverflow.com/questions/42480111/how-do-i-print-the-model-summary-in-pytorch | python, machine-learning, deep-learning, pytorch | 1,488,180,942 |
se_61598771 | stackoverflow | MACHINE_LEARNING | `squeeze()` vs `unsqueeze()` in PyTorch | `squeeze()` vs `unsqueeze()` in PyTorch
I don't understand what squeeze() and unsqueeze() do to a tensor, even after looking at the docs and related questions.
I tried to understand it by exploring it myself in python. I first created a random tensor with
x = torch.rand(3,2,dtype=torch.float)
>>> x
tensor([[0.3703, 0.... | https://stackoverflow.com/questions/61598771/squeeze-vs-unsqueeze-in-pytorch | python, machine-learning, deep-learning, pytorch, tensor | 1,588,615,598 |
se_42479902 | stackoverflow | MACHINE_LEARNING | What does `view()` do in PyTorch? | What does `view()` do in PyTorch?
What does view() do to the tensor x? What do negative values mean?
x = x.view(-1, 16 * 5 * 5) | https://stackoverflow.com/questions/42479902/what-does-view-do-in-pytorch | python, machine-learning, memory, pytorch, tensor | 1,488,180,070 |
se_70307952 | stackoverflow | MACHINE_LEARNING | Get warning : You should probably TRAIN this model on a downstream task to be able to use it for predictions and inference. when loadin finetune model | Get warning : You should probably TRAIN this model on a downstream task to be able to use it for predictions and inference. when loadin finetune model
I get this message when loading a finetune model of Bert with a forward neural network on the last layer from a checkpoint directory.
This IS expected if you are initia... | https://stackoverflow.com/questions/70307952/get-warning-you-should-probably-train-this-model-on-a-downstream-task-to-be-ab | python, python-3.x, tensorflow, pytorch, huggingface-transformers | 1,639,155,382 |
se_54307225 | stackoverflow | MACHINE_LEARNING | `stack()` vs `cat()` in PyTorch | `stack()` vs `cat()` in PyTorch
OpenAI's REINFORCE and actor-critic example for reinforcement learning has the following code:
REINFORCE:
policy_loss = torch.cat(policy_loss).sum()
actor-critic:
loss = torch.stack(policy_losses).sum() + torch.stack(value_losses).sum()
One is using torch.cat, the other uses torch.sta... | https://stackoverflow.com/questions/54307225/stack-vs-cat-in-pytorch | python, machine-learning, deep-learning, pytorch, concatenation | 1,548,156,287 |
se_44856691 | stackoverflow | MACHINE_LEARNING | How do you alter the size of a Pytorch Dataset? | How do you alter the size of a Pytorch Dataset?
Say I am loading MNIST from torchvision.datasets.MNIST, but I only want to load in 10000 images total, how would I slice the data to limit it to only some number of data points? I understand that the DataLoader is a generator yielding data in the size of the specified b... | https://stackoverflow.com/questions/44856691/how-do-you-alter-the-size-of-a-pytorch-dataset | python, machine-learning, dataset, torch, pytorch | 1,498,873,960 |
se_42704283 | stackoverflow | MACHINE_LEARNING | L1/L2 regularization in PyTorch | L1/L2 regularization in PyTorch
How do I add L1/L2 regularization in PyTorch without manually computing it? | https://stackoverflow.com/questions/42704283/l1-l2-regularization-in-pytorch | python, machine-learning, pytorch, loss-function, regularized | 1,489,089,259 |
se_66488807 | stackoverflow | MACHINE_LEARNING | PyTorch model input shape | PyTorch model input shape
I loaded a custom PyTorch model and I want to find out its input shape. Something like this:
model.input_shape
Is it possible to get this information?
Update: print() and summary() don't show this model's input shape, so they are not what I'm looking for. | https://stackoverflow.com/questions/66488807/pytorch-model-input-shape | python, machine-learning, deep-learning, pytorch, conv-neural-network | 1,614,931,192 |
se_57234095 | stackoverflow | MACHINE_LEARNING | What is the difference between .flatten() and .view(-1) in PyTorch? | What is the difference between .flatten() and .view(-1) in PyTorch?
Both .flatten() and .view(-1) flatten a tensor in PyTorch. What's the difference?
Does .flatten() copy the data of the tensor?
Is .view(-1) faster?
Is there any situation that .flatten() doesn't work? | https://stackoverflow.com/questions/57234095/what-is-the-difference-between-flatten-and-view-1-in-pytorch | python, machine-learning, deep-learning, pytorch | 1,564,245,319 |
se_57237352 | stackoverflow | MACHINE_LEARNING | What does "unsqueeze" do in Pytorch? | What does "unsqueeze" do in Pytorch?
The PyTorch documentation says:
Returns a new tensor with a dimension of size one inserted at the specified position. [...]
>>> x = torch.tensor([1, 2, 3, 4])
>>> torch.unsqueeze(x, 0)
tensor([[ 1, 2, 3, 4]])
>>> torch.unsqueeze(x, 1)
tensor([[ 1],
[ 2],
... | https://stackoverflow.com/questions/57237352/what-does-unsqueeze-do-in-pytorch | python, numpy, machine-learning, deep-learning, pytorch | 1,564,278,223 |
se_79082850 | stackoverflow | MACHINE_LEARNING | ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.26.0` but I have version already installed 1.0.1 | ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.26.0` but I have version already installed 1.0.1
I'm trying to run traning this way but face import error, how to fix it:
args = TrainingArguments(output_dir="finetuned",
num_train_epochs=10,
... | https://stackoverflow.com/questions/79082850/importerror-using-the-trainer-with-pytorch-requires-accelerate-0-26-0-bu | import, pytorch, huggingface-transformers, accelerate | 1,728,812,730 |
se_78846880 | stackoverflow | MACHINE_LEARNING | huggingface train only new tokens embedding | huggingface train only new tokens embedding
I want to add new tokens to a huggingface model and train only their embeddings. How can I do that?
There are some ways to train only part of a weight tensor (e.g. https://discuss.pytorch.org/t/how-can-i-freeze-weights-in-element-wise/117988), however they seem to have acces... | https://stackoverflow.com/questions/78846880/huggingface-train-only-new-tokens-embedding | python, pytorch, large-language-model, word-embedding, huggingface | 1,723,099,650 |
se_79619981 | stackoverflow | MACHINE_LEARNING | tflite model does not predict all the lines in hand as the .pt model does | tflite model does not predict all the lines in hand as the .pt model does
I trained a YOLOv8 model for hand line detection. When I test the model in Python, it correctly detects all four hand lines, but when I convert the model to .tflite format and test it in Android Studio (Kotlin), it only predicts three lines.
Pro... | https://stackoverflow.com/questions/79619981/tflite-model-does-not-predict-all-the-lines-in-hand-as-the-pt-model-does | kotlin, tensorflow, pytorch, artificial-intelligence | 1,747,150,614 |
se_77418680 | stackoverflow | MACHINE_LEARNING | Should the shuffle=True argument be used during training in torch.utils.data.DataLoader() when we have time series data? | Should the shuffle=True argument be used during training in torch.utils.data.DataLoader() when we have time series data?
I am confused regarding whether the shuffle=True argument should be used in the pytorch torch.utils.data.DataLoader() during training when the training data are time series data. I believe that shuf... | https://stackoverflow.com/questions/77418680/should-the-shuffle-true-argument-be-used-during-training-in-torch-utils-data-dat | python, deep-learning, pytorch, time-series, pytorch-dataloader | 1,699,033,125 |
se_79618964 | stackoverflow | MACHINE_LEARNING | PyTorch Gan training: shape mismatch between real and fake tensor | PyTorch Gan training: shape mismatch between real and fake tensor
I’m working on a custom CTGAN-like model for tabular data, where I implemented my own _collate_fn and run_step() logic to control sampling, noise injection, and discriminator inputs.
However, I consistently run into shape mismatch errors between the rea... | https://stackoverflow.com/questions/79618964/pytorch-gan-training-shape-mismatch-between-real-and-fake-tensor | python, pytorch, generative-adversarial-network | 1,747,112,245 |
se_79618775 | stackoverflow | MACHINE_LEARNING | How to add new feature to torch geometric data object | How to add new feature to torch geometric data object
I am using the Zinc graph dataset via torch geometric which I access as
zinc_dataset = ZINC(root='my_path', split='train')
Each data element is a graph zinc_dataset[0] looks like
Data(x=[33, 1], edge_index=[2, 72], edge_attr=[72], y=[1])
I have computed a tensor ... | https://stackoverflow.com/questions/79618775/how-to-add-new-feature-to-torch-geometric-data-object | python, graph, pytorch, pytorch-geometric | 1,747,094,667 |
se_79294216 | stackoverflow | MACHINE_LEARNING | "Inconsistent Predictions in PyTorch Model: Single Image vs. Batch Processing" | "Inconsistent Predictions in PyTorch Model: Single Image vs. Batch Processing"
I am noticing a significant difference in model predictions when running predictions on a single image versus the whole dataset. The model, which was trained using PyTorch, gives drastically different predictions for the same imag... | https://stackoverflow.com/questions/79294216/inconsistent-predictions-in-pytorch-model-single-image-vs-batch-processing | python, pytorch, huggingface-transformers, huggingface, huggingface-trainer | 1,734,609,867 |
se_77670973 | stackoverflow | MACHINE_LEARNING | How to use torcheval.metrics.FrechetInceptionDistance in pytorch for mnist dataset? | How to use torcheval.metrics.FrechetInceptionDistance in pytorch for mnist dataset?
I defined a GAN model and I want to evaluate it using FID score. I have 1 channel images which are mnist dataset but this method wants 3 channels images. How can I do to solve this problem? | https://stackoverflow.com/questions/77670973/how-to-use-torcheval-metrics-frechetinceptiondistance-in-pytorch-for-mnist-datas | python, pytorch, evaluation, mnist, generative-adversarial-network | 1,702,731,167 |
se_70954722 | stackoverflow | MACHINE_LEARNING | Invert PyTorch Indexing | Invert PyTorch Indexing
Suppose, I have a PyTorch tensor a of shape ba,c,h,w and wish to zero out some rows of a with indices given in another tensor b of shape ba,2 of dtype=torch.int16 and b[batch, 0] <= b[batch, 1].
The for loop way of doing is:
for batch in range(ba):
a[batch,:,0:b[batch,0],:] = 0 # stmnt 1
... | https://stackoverflow.com/questions/70954722/invert-pytorch-indexing | python, pytorch, slice, tensor | 1,643,800,972 |
se_79615651 | stackoverflow | MACHINE_LEARNING | Pylance: "Variable not allowed in type expression" for torch.Tensor return type with from __future__ import annotations (Python 3.12, PyTorch 2.5) | Pylance: "Variable not allowed in type expression" for torch.Tensor return type with from __future__ import annotations (Python 3.12, PyTorch 2.5)
I'm encountering a Pylance(reportInvalidTypeForm) error when using torch.Tensor as a return type hint in my PyTorch nn.Module subclasses. This happens even though... | https://stackoverflow.com/questions/79615651/pylance-variable-not-allowed-in-type-expression-for-torch-tensor-return-type | python, pytorch, python-typing, pylance | 1,746,891,033 |
se_76566144 | stackoverflow | MACHINE_LEARNING | View PyTorch Implementation details interactively | View PyTorch Implementation details interactively
How to see the actual implementation of PyTorch functionalities, classes, and methods.
I did not find them on PyTorch's official website. I want an easy way to navigate through the implementation to better understand the concepts. | https://stackoverflow.com/questions/76566144/view-pytorch-implementation-details-interactively | pytorch | 1,687,877,659 |
se_75794403 | stackoverflow | MACHINE_LEARNING | AttributeError: module 'os' has no attribute 'add_dll_directory' | AttributeError: module 'os' has no attribute 'add_dll_directory'
ERROR
https://github.com/CorentinJ/Real-Time-Voice-Cloning
I am trying to clone my voice using ML. I am following : https://github.com/CorentinJ/Real-Time-Voice-Cloning repository. But at the third step of Setup that is when I run the com... | https://stackoverflow.com/questions/75794403/attributeerror-module-os-has-no-attribute-add-dll-directory | python, module, pytorch, attributes, attributeerror | 1,679,339,636 |
se_74577562 | stackoverflow | MACHINE_LEARNING | Get paths of saved checkpoints from Pytorch-Lightning ModelCheckpoint | Get paths of saved checkpoints from Pytorch-Lightning ModelCheckpoint
I am using PytorchLightning and a ModelCheckpoint which saves models with a formatted filename like filename="model_{epoch}-{val_acc:.2f}"
Afterwards I want to access these checkpoints again and need their paths. For simplicity I want the best from ... | https://stackoverflow.com/questions/74577562/get-paths-of-saved-checkpoints-from-pytorch-lightning-modelcheckpoint | python, pytorch, pytorch-lightning, checkpointing | 1,669,407,709 |
se_63920887 | stackoverflow | MACHINE_LEARNING | Whitelist tokens for text generation (XLNet, GPT-2) in huggingface-transformers | Whitelist tokens for text generation (XLNet, GPT-2) in huggingface-transformers
In the documentation on text generation (https://huggingface.co/transformers/main_classes/model.html#generative-models) there is the option to put
bad_words_ids (List[int], optional) – List of token ids that are not allowed to be generated... | https://stackoverflow.com/questions/63920887/whitelist-tokens-for-text-generation-xlnet-gpt-2-in-huggingface-transformers | python-3.x, nlp, pytorch, huggingface-transformers | 1,600,262,138 |
se_76644106 | stackoverflow | MACHINE_LEARNING | How to resolve runtime error in CNN model related to mismatch input size? | How to resolve runtime error in CNN model related to mismatch input size?
I am trying to run a CNN model on a synthetic dataset consisting of 4000 sample of semi simple random points with 2 features and 1 cluster per class and input data size x is [4000,2] and corresponding labels size is [4000].
I understand that as ... | https://stackoverflow.com/questions/76644106/how-to-resolve-runtime-error-in-cnn-model-related-to-mismatch-input-size | machine-learning, deep-learning, pytorch, neural-network, conv-neural-network | 1,688,836,447 |
se_79613435 | stackoverflow | MACHINE_LEARNING | Soft Actor Critic -- actor forward pass outputs NaN immediately | Soft Actor Critic -- actor forward pass outputs NaN immediately
I have the following code for my Actor network in my Soft Actor Critic. However, once the batch is full and it starts to do back prop, (batch size: 128), after about 5 iterations of updating the parameters (batch size: 135), the forward pass of the Actor ... | https://stackoverflow.com/questions/79613435/soft-actor-critic-actor-forward-pass-outputs-nan-immediately | pytorch, reinforcement-learning | 1,746,759,605 |
se_79612729 | stackoverflow | MACHINE_LEARNING | Training and validation losses do not reduce when fine-tuning ViTPose from huggingface | Training and validation losses do not reduce when fine-tuning ViTPose from huggingface
I am trying to fine-tune a transformer/encoder based pose estimation model available here at:
https://huggingface.co/docs/transformers/en/model_doc/vitpose
When passing "labels" attribute to the forward pass of the model, the model ... | https://stackoverflow.com/questions/79612729/training-and-validation-losses-do-not-reduce-when-fine-tuning-vitpose-from-huggi | python, machine-learning, pytorch, huggingface-transformers, transformer-model | 1,746,718,134 |
se_71651362 | stackoverflow | MACHINE_LEARNING | Raytune tune.choice Typeerror: int() argument must be a string, a bytes-like object or a number, not 'Categorical' | Raytune tune.choice Typeerror: int() argument must be a string, a bytes-like object or a number, not 'Categorical'
I am trying hyperparameter tuning using Ray-tune.
current my tune_config is shown in below code
self.tune_config = {
"batch_size": tune.choice([128, 256, 512]),
"epoch": tune.choice([50, 1... | https://stackoverflow.com/questions/71651362/raytune-tune-choice-typeerror-int-argument-must-be-a-string-a-bytes-like-obj | performance, pytorch, typeerror, hyperparameters, ray-tune | 1,648,488,674 |
se_61515915 | stackoverflow | MACHINE_LEARNING | Custom submodules in pytorch / libtorch C++ | Custom submodules in pytorch / libtorch C++
Full disclosure, I asked this same question on the PyTorch forums about a few days ago and got no reply, so this is technically a repost, but I believe it's still a good question, because I've been unable to find an answer anywhere online. Here goes:
Can you show an example... | https://stackoverflow.com/questions/61515915/custom-submodules-in-pytorch-libtorch-c | c++, pytorch, libtorch | 1,588,220,784 |
se_78792142 | stackoverflow | MACHINE_LEARNING | Pyarrow error with ray & lightning on databricks | Pyarrow error with ray & lightning on databricks
I am trying to train a neural net with pytorch lightning on ray on a databricks cluster. As a start, I copied the example from https://docs.ray.io/en/latest/train/getting-started-pytorch-lightning.html. Unfortunately, the training stops after one epoch with a RayTas... | https://stackoverflow.com/questions/78792142/pyarrow-error-with-ray-lightning-on-databricks | pytorch, databricks, pyarrow, ray, lightning | 1,721,894,889 |
se_68526138 | stackoverflow | MACHINE_LEARNING | Torchvision Datasets: Flickr8k not importing Datapoints correctly | Torchvision Datasets: Flickr8k not importing Datapoints correctly
I am using torchvision.Datasets to import Flickr8k for later usage inside a Jupyter Notebook. I downloaded all Images from Kaggle into a Folder "archive/Images" and have the file "captions.txt" inside the "archive" Folder. Below is the Problem, the Imag... | https://stackoverflow.com/questions/68526138/torchvision-datasets-flickr8k-not-importing-datapoints-correctly | python, jupyter-notebook, pytorch, kaggle, torchvision | 1,627,285,316 |
se_78975293 | stackoverflow | MACHINE_LEARNING | Linear FFNN Model achieving 100% accuracy in predicting sums | Linear FFNN Model achieving 100% accuracy in predicting sums
I have a model that adds numbers between -10 to positive 10. The task is simply to predict the sum of those numbers. However the train accuracy quickly reaches 100%.
I am not sure if the model is just quickly training, or if there is something wrong and it i... | https://stackoverflow.com/questions/78975293/linear-ffnn-model-achieving-100-accuracy-in-predicting-sums | python, machine-learning, deep-learning, pytorch, perceptron | 1,726,080,228 |
se_79609919 | stackoverflow | MACHINE_LEARNING | How to make NN really find optimal solution during training? | How to make NN really find optimal solution during training?
Imagine a simple problem: make a function that gets a month index as input (zero-based: 0=Jan, 1=Feb, etc) and outputs number of days in this month (leap year ignored).
Of course, using NN for that task is an overkill, but I wondered, can NN actually be trai... | https://stackoverflow.com/questions/79609919/how-to-make-nn-really-find-optimal-solution-during-training | machine-learning, deep-learning, pytorch, artificial-intelligence | 1,746,600,444 |
se_79596508 | stackoverflow | MACHINE_LEARNING | Why is day_size set to 32 in temporal embedding code? | Why is day_size set to 32 in temporal embedding code?
I am trying to understand the code for temporal embedding inside autoformer implementation using pytorch.
https://github.com/thuml/Autoformer/blob/main/layers/Embed.py
class TemporalEmbedding(nn.Module):
def __init__(self, d_model, embed_type='fixed', freq='h')... | https://stackoverflow.com/questions/79596508/why-is-day-size-set-to-32-in-temporal-embedding-code | python, pytorch, transformer-model | 1,745,844,359 |
se_79599360 | stackoverflow | MACHINE_LEARNING | What is the equivalent of torch.nn.Parameter(...) in julia's flux? | What is the equivalent of torch.nn.Parameter(...) in julia's flux?
In pytorch I can create a custom module as follows (this code example is taken from here):
from torch import nn
class MyModel(nn.Module):
def __init__(self):
super().__init__()
self.param = nn.Parameter(torch.randn(1, 1))
... | https://stackoverflow.com/questions/79599360/what-is-the-equivalent-of-torch-nn-parameter-in-julias-flux | python, pytorch, julia, flux.jl | 1,745,972,851 |
se_79609591 | stackoverflow | MACHINE_LEARNING | How to trace PyTorch Dataloader workers with VizTracer? | How to trace PyTorch Dataloader workers with VizTracer?
I'm using VizTracer to debug performance issues in my PyTorch data loading pipeline. Specifically, I'm using a DataLoader with num_workers > 0 to load data in parallel using multiple subprocesses.
However, I noticed that VizTracer doesn't trace these worker subpr... | https://stackoverflow.com/questions/79609591/how-to-trace-pytorch-dataloader-workers-with-viztracer | python, pytorch, multiprocessing, trace, pytorch-dataloader | 1,746,571,717 |
se_79609199 | stackoverflow | MACHINE_LEARNING | Numerically stable noncentral chi-squared distribution in torch? | Numerically stable noncentral chi-squared distribution in torch?
I need numerically stable non-central chi2 distribution in torch. | https://stackoverflow.com/questions/79609199/numerically-stable-noncentral-chi-squared-distribution-in-torch | python, pytorch, statistics, numerical-methods | 1,746,552,587 |
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