instruction stringclasses 1
value | input stringlengths 137 2k | output stringlengths 107 2k |
|---|---|---|
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Output and Broadcast shape mismatch in MNIST, torchvision
I am getting following error when using MNIST dataset in Torchvision
```
RuntimeError: output with shape [1, 28, 28] doesn't match the broadcast shape [3, 28, 28]
```
Here is my code:
```
import torch
from torchvision import datasets, transforms
transform ... | The error is due to color vs grayscale on the dataset, the dataset is grayscale.
I fixed it by changing transform to
```
transform = transforms.Compose([transforms.ToTensor(),
transforms.Normalize((0.5,), (0.5,))
])
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Is there a way to use torch.nn.DataParallel with CPU?
I'm trying to change some PyTorch code so that it can run on the CPU.
The model was trained with
```
torch.nn.DataParallel()
```
so when I load the pre-trained model and try using it I must use
```
nn.DataParallel()
```
which I am currently doing like this... | When you use
```
torch.nn.DataParallel()
```
it implements data parallelism at the module level.
According to the doc:
The parallelized module must have its parameters and buffers on device_ids[0] before running this DataParallel module.
So even though you are doing
```
.to(torch.device('cpu'))
```
it is sti... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Espresso ANERuntimeEngine Program Inference overflow
I have two CoreML models. One works fine, and the other generates this error message:
```
[espresso] [Espresso::ANERuntimeEngine::__forward_segment 0] evaluate[RealTime]WithModel returned 0; code=5 err=Error Domain=com.apple.appleneuralengine Code=5 "processRequest... | That's a LOT of layers!
Espresso is the C++ library that runs the Core ML models. ANERuntimeEngine is used with the Apple Neural Engine chip.
By passing in an
```
MLModelConfiguration
```
with
```
computeUnits
```
set to
```
.cpuAndGPU
```
when you load the Core ML model, you can tell Core ML to not use t... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Is there a way to install pytorch on python 3.12.0?
I'm making an app using
```
gpt-neo
```
and I'm trying to install
```
torch
```
, but it won't install.
The error message is as follows:
```
C:\Users\Ben>pip install torch
ERROR: Could not find a version that satisfies the requirement torch (from versions: n... | Its possible now if you use the nightly version.
Instructions here
https://pytorch.org/
, but pasted here for completeness
```
pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu118
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Install specific PyTorch version (pytorch==1.0.1)
I'm trying to install specific PyTorch version under conda env:
Using pip:
```
pip3 install pytorch==1.0.1
WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.
Please see https://github.com/pypa/pip/issues/5599 for advice... | You can download/install the version you like from the official
Pytorch's Conda package
. the link you specified is an old version and is not supported/updated for quit some time now!.
Install your desired version like this :
```
conda install pytorch==1.0.1 torchvision==0.2.2 -c pytorch
```
If you are looking for... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to convert torch tensor to float?
I am using flask to do inference and I am getting this result. Is their any way to convert this tensor into float because I want to use this result to display in a react app:
```
{
result: {
predictions: "tensor([[-3.4333]], grad_fn=<AddmmBackward>)"
}
}
``` | From
Torch.Tensor.item
docs:
```
x = torch.tensor([1.0])
print((x.item())
```
output:
```
1.0
```
type check:
```
print(type(x.item())
```
output:
```
float
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Freeze certain layers of an existing model in PyTorch
I am using the mobileNetV2 and I only want to freeze part of the model. I know I can use the following code to freeze the entire model
```
MobileNet = models.mobilenet_v2(pretrained = True)
for param in MobileNet.parameters():
param.requires_grad = False
``... | Start by freezing everything:
```
for param in MobileNet.parameters():
param.requires_grad = False
```
Then, unfreeze parameters in (15):
```
for param in MobileNet.features[15].parameters():
param.requires_grad = True
```
Or, unfreeze parameters in (15)-(18):
```
for i in range(15, 19):
for param in... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Taking subsets of a pytorch dataset
I have a network which I want to train on some dataset (as an example, say
```
CIFAR10
```
). I can create data loader object via
```
trainset = torchvision.datasets.CIFAR10(root='./data', train=True,
download=True, transform=transform)
tr... | ```
torch.utils.data.Subset
```
is easier, supports
```
shuffle
```
, and doesn't require writing your own sampler:
```
import torchvision
import torch
trainset = torchvision.datasets.CIFAR10(root='./data', train=True,
download=True, transform=None)
evens = list(range(0, ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | OSError: [WinError 127] The specified procedure could not be found
While importing torch (
```
import torch
```
) I'm facing the following error message:
```
OSError: [WinError 127] The specified procedure could not be found. Error loading "C:\Users\myUserName\anaconda3\lib\site-packages\torch\lib\jitbackend_test.d... | Fortunately, after extensive research, I found a solution.
Someone suggested me to create a new conda environment. And that worked for me!
Solution:
create new conda env by:
```
conda create --name new-env
```
install python:
```
conda install python=3.8.5
```
run:
```
conda install pytorch torchvision torcha... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | 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... | The command to install the stable version of PyTorch (2.7.0) with CUDA 12.8 using pip on Linux is:
```
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Finding non-intersection of two pytorch tensors
Thanks everyone in advance for your help! What I'm trying to do in PyTorch is something like numpy's
```
setdiff1d
```
. For example given the below two tensors:
```
t1 = torch.tensor([1, 9, 12, 5, 24]).to('cuda:0')
t2 = torch.tensor([1, 24]).to('cuda:0')
```
The e... | I came across the same problem but the proposed solutions were far too slow when using larger arrays. The following simple solution works on CPU and GPU and is significantly faster than the other proposed solutions:
```
combined = torch.cat((t1, t2))
uniques, counts = combined.unique(return_counts=True)
difference = u... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: Attempting to deserialize object on CUDA device 2 but torch.cuda.device_count() is 1
I've got a snippet of python code for training a model. The problem is that after running:
```
loaded_state = torch.load(model_path+seq_to_seq_test_model_fname)
```
to load a pretrained model,I'm getting:
```
Trac... | I just figured it out:
```
loaded_state = torch.load(model_path+seq_to_seq_test_model_fname,map_location='cuda:0')
```
is the solution |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Certain members of a torch module aren't moved to GPU even if model.to(device) is called
An mwe is as follows:
```
import torch
import torch.nn as nn
class model(nn.Module):
def __init__(self):
super(model,self).__init__()
self.mat = torch.randn(2,2)
def forward(self,x):
print('s... | pytorch
apply Module's methods such as
```
.cpu()
```
,
```
.cuda()
```
and
```
.to()
```
only to sub-modules,
parameters
and
buffers
, but
NOT
to regular class members. pytorch has no way of knowing that
```
self.mat
```
, in your case, is an actual tensor that should be moved around.
Once you dec... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | TRANSFORMERS: Asking to pad but the tokenizer does not have a padding token
In trying to evaluate several transformers models sequentially with the same dataset to check which one performs better.
The list of models is this one:
```
MODELS = [
('xlm-mlm-enfr-1024' ,"XLMModel"),
('distilbert-base-cased'... | kkgarg idea
was right, but you also need to update your model token embeding size.
So, the code will be:
```
tokenizer = AutoTokenizer.from_pretrained(pretrained_weights)
model = TFAutoModel.from_pretrained(pretrained_weights)
if tokenizer.pad_token is None:
tokenizer.add_special_tokens({'pad_token': '[PAD]'})
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | import torch.fx ModuleNotFoundError: No module named 'torch.fx'
After enabling torch and Cuda for my system according to my system GPU compatibility, whenever I am trying to run any program which needs to be run on GPU to enable the system, this error is coming. I could not able to find any solution for this. ... | ```
torch.fx
```
was added in PyTorch 1.8.0. Check
release post
. You're probably using an older version. Upgrade pytorch from
website
. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same
This:
```
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
for data in dataloader:
inputs, labels = data
outputs = model(inputs)
```
Gives the error:
RuntimeError:... | You get this error because your model is on the GPU, but your data is on the CPU. So, you need to send your input tensors to the GPU.
```
inputs, labels = data # this is what you had
inputs, labels = inputs.cuda(), labels.cuda() # add this line
```
Or like this, to stay consistent with the re... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to free gpu memory by deleting tensors?
Suppose I create a tensor and put it on the GPU and don't need it later and want to free the GPU memory allocated to it; How do I do it?
```
import torch
a=torch.randn(3,4).cuda() # nvidia-smi shows that some mem has been allocated.
# do something
# a does not exist and nvi... | Running
```
del tensor
```
frees the memory from the GPU but does not return it to the device which is why the memory still being shown as used on
```
nvidia-smi
```
. You can create a new tensor and that would reuse that memory.
Sources
https://discuss.pytorch.org/t/how-to-delete-pytorch-objects-correctly-fro... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | can't find the inplace operation: one of the variables needed for gradient computation has been modified by an inplace operation
I am trying to compute a loss on the jacobian of the network (i.e. to perform double backprop), and I get the following error:
RuntimeError: one of the variables needed for gradient comp... | You can make use of
```
set_detect_anomaly
```
function available in
```
autograd
```
package to exactly find which line is responsible for the error.
Here is the
link
which describes the same problem and a solution using the abovementioned function. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How downsample work in ResNet in pytorch code?
In this pytorch ResNet code example they define downsample as variable in line 44. and line 58 use it as function. How this downsample work here as CNN point of view and as python Code point of view.
code example :
pytorch ResNet
i searched for if downsample is any pyt... | If you look into the original ResNet Paper (
http://openaccess.thecvf.com/content_cvpr_2016/papers/He_Deep_Residual_Learning_CVPR_2016_paper.pdf
) they use strided convolutions to downsample the image. The main path is downsampled automatically using these strided convolutions as is done in your code. The residual path... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: CUDA error: no kernel image is available for execution on the device after model.cuda()
I am working on this model:
```
class Model(torch.nn.Module):
def __init__(self, sizes, config):
super(Model, self).__init__()
self.lstm = []
for i in range(len(sizes) - 2):
s... | I checked the latest
```
torch
```
and
```
torchvision
```
version with
```
cuda
```
from the given link. Stable versions list:
https://download.pytorch.org/whl/cu113/torch_stable.html
Below versions solved the error,
```
pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytor... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AttributeError: 'collections.OrderedDict' object has no attribute 'eval'
I have a model file which looks like this
```
OrderedDict([('inp.conv1.conv.weight',
(0 ,0 ,0 ,.,.) =
-1.5073e-01 6.4760e-02 1.9156e-01
1.2175e-01 3.5886e-02 1.3992e-01
-1.5903e-0... | It is not a model file, instead, this is a state file. In a model file, the complete model is stored, whereas in a state file only the parameters are stored.
So, your
```
OrderedDict
```
are just values for your model. You will need to create the model and then need to load these values into your model. So, the pr... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Incompletable PyTorch with any CUDA version (module 'torch' has no attribute 'cuda')
I have NVidia 1080TI, Ubuntu x64, and Python 3.6.9 installed.
I was trying to launch PyTorch with command
```
import torch
print(torch.cuda.is_available)
```
and expected to see 'True' but met the error:
```
Attrib... | As a result, I had a file named
```
torch.py
```
in my home directory. After the renaming problem was solved.
Thanks. Maybe my answer will be helpful to someone. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Calculate the accuracy every epoch in PyTorch
I am working on a Neural Network problem, to classify data as 1 or 0. I am using Binary cross entropy loss to do this. The loss is fine, however, the accuracy is very low and isn't improving. I am assuming I did a mistake in the accuracy calculation. After every epoch, I a... | A better way would be calculating
correct
right after optimization step
```
for epoch in range(num_epochs):
correct = 0
for i, (inputs,labels) in enumerate (train_loader):
...
output = net(inputs)
...
optimizer.step()
correct += (output == labels).float().sum()
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to access the network weights while using PyTorch 'nn.Sequential'?
I'm building a neural network and I don't know how to access the model weights for each layer.
I've tried
```
model.input_size.weight
```
Code:
```
input_size = 784
hidden_sizes = [128, 64]
output_size = 10
# Build a feed-forward ne... | If you print out the model using
```
print(model)
```
, you would get
```
Sequential(
(0): Linear(in_features=784, out_features=128, bias=True)
(1): ReLU()
(2): Linear(in_features=128, out_features=64, bias=True)
(3): ReLU()
(4): Linear(in_features=64, out_features=10, bias=True)
(5): Softmax(dim=1) )
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Given input size: (128x1x1). Calculated output size: (128x0x0). Output size is too small
I am trying to train a U-Net which looks like this
```
`class UNet(nn.Module):
def __init__(self, imsize):
super(UNet, self).__init__()
self.imsize = imsize
self.activation = F.relu
self.pool1 = nn.MaxPool2d(2)
... | Your problem is that before the Pool4 your image has already reduced to a
```
1x1
```
pixel size image. So you need to either feed an much larger image of size at least around double that (~134x134) or remove a pooling layer in your network. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | cuDNN error: CUDNN_STATUS_BAD_PARAM.Can someone explain why i am getting this error and how can i correct it?
I am trying to implement a Character LSTM using Pytorch.But I am getting cudnn_status_bad_params errors.This is the training loop.I getting error on line output = model(input_seq).
```
for epoch in tqdm(range... | I got the same error, if you switch to CPU, you'll get a much better description of the error. In my case the problem was in type of input that I was giving to the network. I was sending I guess
```
long
```
, while the model needed
```
float
```
. I made the following changes and the code worked. Basically switc... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Using flatten in pytorch v1.0 Sequential module
Due to my CUDA version being 8, I am using torch 1.0.0
I need to use the Flatten layer for Sequential model. Here's my code :
```
import torch
import torch.nn as nn
import torch.nn.functional as F
print(torch.__version__)
# 1.0.0
from collections import OrderedDict
l... | Just make a new Flatten layer.
```
from collections import OrderedDict
class Flatten(nn.Module):
def forward(self, input):
return input.view(input.size(0), -1)
layers = OrderedDict()
layers['conv1'] = nn.Conv2d(1, 5, 3)
layers['relu1'] = nn.ReLU()
layers['conv2'] = nn.Conv2d(5, 1, 3)
layers['relu2'] = nn... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Can numpy arrays run in GPUs?
I am using PyTorch. I have the following code:
```
import numpy as np
import torch
X = np.array([[1, 3, 2, 3], [2, 3, 5, 6], [1, 2, 3, 4]])
X = torch.DoubleTensor(X).cuda()
X_split = np.array_split(X.numpy(),
indices_or_sections = 2,
... | No you cannot generally run numpy functions on GPU arrays. PyTorch reimplements much of the functionality in numpy for PyTorch tensors. For example
```
torch.chunk
```
works similarly to
```
np.array_split
```
so you could do the following:
```
X = np.array([[1, 3, 2, 3], [2, 3, 5, 6], [1, 2, 3, 4]])
X = torch... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | What does x[x!=x] mean?
I don't understand
this line
:
```
lprobs[lprobs != lprobs] = torch.tensor(-math.inf).to(lprobs)
```
There is no comment, so is it some well-known Python (or PyTorch?) idiom? Could someone explain what it means, or show a different way that makes the intent clearer?
```
lprobs
```
is a
... | It's a combination of
fancy indexing with a boolean mask
, and a
"trick"
(although intended by design) to check for
```
NaN
```
:
```
x != x
```
holds iff
```
x
```
is
```
NaN
```
(for floats, that is).
They could alternatively have written
```
lprobs[torch.isnan(lprobs)] = torch.tensor(-math.inf).t... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to disable progress bar in Pytorch Lightning
I have a lot of issues withe the tqdm progress bar in Pytorch Lightning:
when I run trainings in a terminal, the progress bars overwrite themselves. At the end of an training epoch, a validation progress bar is printed under the training bar, but when that ends, the... | F.Y.I.
```
show_progress_bar=False
```
deprecated since version 0.7.2, but you can use
```
progress_bar_refresh_rate=0
```
update:
```
progress_bar_refresh_rate
```
has been deprecated in v1.5 and will be removed in v1.7. To disable the progress bar, set
```
enable_progress_bar
```
to false
```
progress_... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch Error checking compiler version for cl (cpp_extension.py)
I'm using Anaconda and I have installed PyTorch using the following command:
```
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
```
Now I'm getting the following error in torch/utils/cpp_extension.py... | I had the same issue, but I could resolve by following instructions below. The idea is to find the compiler
```
cl
```
in your windows system and add the directory to the path
Make sure you have installed Microsoft Visual Studio BuildTools.
Press Windows Button and type
```
x86
```
, you will get something cal... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | 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.
``` | In
```
PyTorch
```
, for every mini-batch during the
training
phase, we typically want to explicitly set the gradients to zero before starting to do backpropagation (i.e., updating the
W
eights
and
b
iases
) because PyTorch
accumulates the gradients
on subsequent backward passes. This accumulating behavior is... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | pytorch code sudden fails on colab with NVIDIA driver on your system is too old
I had some code which worked on colab (gpu runtime) just a short while ago. Suddenly I am getting
The NVIDIA driver on your system is too old (found version 10010).
nvcc shows
Cuda compilation tools, release 10.1, V10.1.243
I tried torc... | The light-the-torch package is designed to solve exactly this type of issue. Try this:
```
!pip install light-the-torch
!ltt install torch torchvision
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | cannot import name 'flash_attn_func' from 'flash_attn'
try to load llama2 model:
```
model = AutoModelForCausalLM.from_pretrained(
model_name,
quantization_config=bnb_config,
device_map=device_map
)
```
with these bnb_config:
```
BitsAndBytesConfig {
"bnb_4bit_compute_dtype": "bfloat1... | I was having the same error when finetuning llama2 model, the solution will be to revert to the previous version of transformers.
```
pip install transformers==4.33.1 --upgrade
```
This should work. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: Expected a 'cuda' device type for generator but found 'cpu'
I am trying to train
PeleeNet pytorch
and got the following error
```
train.py
```
line 80
```
pelee_voc
```
train configuration | Reading the link provided in
@Dwijay 's answer
, I found an answer that does not require you to do any source code change.
Indeed, it is very dangerous I would say to change PyTorch source code.
But the idea of modifying the
```
Generator
```
is the good one.
Indeed by default the random number generator generates... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to iterate over layers in Pytorch
Let's say I have a network model object called
```
m
```
. Now I have no prior information about the number of layers this network has. How can create a for loop to iterate over its layer?
I am looking for something like:
```
Weight=[]
for layer in m._modules:
Weight.appen... | Let's say you have the following neural network.
```
import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
# 1 input image channel, 6 output channels, 5x5 square convolution
# kernel
self.conv1 = nn... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How does pytorch's nn.Module register submodule?
When I read the source code(python) of torch.nn.Module , I found the
attribute
```
self._modules
```
has been used in many functions like
```
self.modules(), self.children()
```
, etc. However, I didn't find any functions
updating it. So, where will the... | Add some details to Jiren Jin's answer:
Layers of a net (inherited from
```
nn.Module
```
) are stored in
```
Module._modules
```
, which is initialized in
```
__construct
```
:
```
def __init__(self):
self.__construct()
# initialize self.training separately from the rest of the internal
# state,... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch geometric: Having issues with tensor sizes
This is the first time I'm using Pytorch and Pytorch geometric. I'm trying to create a simple Graph Neural Network with Pytorch Geometric. I'm creating a custom dataset by following the Pytorch Geometric documentations and extending the InMemoryDataset. After that I s... | I agree with @trialNerror -- it is a data problem. Your
```
edge_index
```
should refer to the data nodes and its
```
max
```
should not be that high. Since you don't want to show us the data and ask for "creating a graph on any kind of data ", here it is.
I mostly left your
```
Net
```
unchanged. You can ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to check the output gradient by each layer in pytorch in my code?
I am working on the pytorch to learn.
And There is a question how to check the output gradient by each layer in my code.
My code is below
```
#import the nescessary libs
import numpy as np
import torch
import time
# Loading the Fashion-MNIST da... | Well, this is a good question if you need to know the inner computation within your model. Let me explain to you!
So firstly when you print the
```
model
```
variable you'll get this output:
```
Sequential(
(0): Linear(in_features=784, out_features=128, bias=True)
(1): ReLU()
(2): Linear(in_features=128, ou... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Understanding Gradient in Pytorch
I have some Pytorch code which demonstrates the gradient calculation within Pytorch, but I am thoroughly confused what got calculated and how it is used. This post
here
demonstrates the usage of it, but it does not make sense to me in terms of the back propagation algorithm. Looking... | Backpropagation is based on the chain-rule for calculating derivatives. This means the gradients are computed step-by-step from tail to head and always passed back to the previous step ("previous" w.r.t. to the preceding forward pass).
For scalar output the process is initiated by assuming a gradient of
```
d (out1)... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Loading Hugging face model is taking too much memory
I am trying to load a large Hugging face model with code like below:
```
model_from_disc = AutoModelForCausalLM.from_pretrained(path_to_model)
tokenizer_from_disc = AutoTokenizer.from_pretrained(path_to_model)
generator = pipeline("text-generation", model=model_fro... | You could try to load it with
low_cpu_mem_usage
:
```
from transformers import AutoModelForSeq2SeqLM
model_from_disc = AutoModelForCausalLM.from_pretrained(path_to_model, low_cpu_mem_usage=True)
```
Please note that
```
low_cpu_mem_usage
```
requires:
Accelerate >= 0.9.0 and PyTorch >= 1.9.0. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Should I use softmax as output when using cross entropy loss in PyTorch?
I have a problem with classifying fully connected deep neural net with 2 hidden layers for
MNIST dataset in pytorch
.
I want to use
tanh
as activations in both hidden layers, but in the end, I should use
softmax
.
For the loss, I am choosin... | As stated in the
```
torch.nn.CrossEntropyLoss()
```
doc:
This criterion combines
```
nn.LogSoftmax()
```
and
```
nn.NLLLoss()
```
in one single class.
Therefore, you should
not
use softmax before. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to convert a list of strings into a tensor in pytorch?
I am working on classification problem in which I have a list of strings as class labels and I want to convert them into a tensor. So far I have tried converting the list of strings into a
```
numpy array
```
using the
```
np.array
```
function provide... | Unfortunately, you can't right now. And I don't think it is a good idea since it will make PyTorch clumsy. A popular workaround could convert it into numeric types using
sklearn
.
Here is a short example:
```
from sklearn import preprocessing
import torch
labels = ['cat', 'dog', 'mouse', 'elephant', 'pandas']
le = ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | img should be PIL Image. Got <class 'torch.Tensor'>
I'm trying to iterate through a loader to check if it's working, however the below error is given:
```
TypeError: img should be PIL Image. Got <class 'torch.Tensor'>
```
I've tried adding both
```
transforms.ToTensor()
```
and
```
transforms.ToP... | ```
transforms.RandomHorizontalFlip()
```
works on
```
PIL.Images
```
, not
```
torch.Tensor
```
. In your code above, you are applying
```
transforms.ToTensor()
```
prior to
```
transforms.RandomHorizontalFlip()
```
, which results in tensor.
But, as per the official pytorch documentation
here
,
tr... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | What's the reason of the error ValueError: Expected more than 1 value per channel?
reference fast.ai
github repository of fast.ai
(as the code elevates the library which is built on top of
PyTorch
)
Please scroll the discussion a bit
I am running the following code, and get an error while trying to pass the d... | It will fail on batches of size 1 if we use feature-wise batch normalization.
As Batch normalization computes:
```
y = (x - mean(x)) / (std(x) + eps)
```
If we have one sample per batch then
```
mean(x) = x
```
, and the output will be entirely zero (ignoring the bias). We can't use that for learning... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Tensorboard resume training plot
I ran a reinforcement learning training script which used Pytorch and logged data to tensorboardX and saved checkpoints. Now I want to continue training. How do I tell tensorboardX to continue from where I left off? Thank you! | I figured out how to continue the training plot. While creating the summarywriter, we need to provide the same
```
log_dir
```
that we used while training the first time.
```
from tensorboardX import SummaryWriter
writer = SummaryWriter('log_dir')
```
Then inside the training loop step needs to start from where ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to replicate PyTorch normalization in OpenCV or NumPy?
I need to replicate PyTorch image normalization in OpenCV or NumPy.
Quick backstory: I'm doing a project where I'm training in PyTorch but will have to inference in OpenCV due to deploying to an embedded device where I won't have the storage space to install ... | This probably would be helpful
If you look at actual implementation of
```
torchvision.transforms.Normalize(
mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225],
)
```
Below block is what it actually does:
```
import numpy as np
from PIL import Image
MEAN = 255 * np.array([0.485, 0.456, 0.406... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch [1 if x > 0.5 else 0 for x in outputs ] with tensors
I have a list outputs from a sigmoid function as a tensor in PyTorch
E.g
```
output (type) = torch.Size([4]) tensor([0.4481, 0.4014, 0.5820, 0.2877], device='cuda:0',
```
As I'm doing binary classification I want to turn all values bellow 0.5 to 0 and... | ```
prob = torch.tensor([0.3,0.4,0.6,0.7])
out = (prob>0.5).float()
# tensor([0.,0.,1.,1.])
```
Explanation: In pytorch, you can directly use
```
prob>0.5
```
to get a
```
torch.bool
```
type tensor. Then you can convert to float type via
```
.float()
```
. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Get probability of multi-token word in MASK position
It is relatively easy to get a token's probability according to a language model, as the snippet below shows. You can get the output of a model, restrict yourself to the output of the masked token, and then find the probability of your requested token in the output ... | Since the split word is not present in the dictionary, BERT is simply unaware of its probability, so there is no use of masking it before tokenization.
And you can't get its probability by exploiting the rule of chain, see
response
by J.Devlin. To illustrate it, let's take a more generic example. Try to estimate the... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Obtaining the image iterations before final image has been generated StableDiffusionPipeline.pretrained
I am currently using the
```
diffusers StableDiffusionPipeline
```
(from hugging face) to generate AI images with a discord bot which I use with my friends. I was wondering if it was possible to get a preview of... | You can use the callback argument of the stable diffusion pipeline to get the latent space representation of the image:
link to documentation
The
implementation
shows how the latents are converted back to an image. We just have to copy that code and decode the latents.
Here is a small example that saves the genera... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Imorting zero_gradients from torch.autograd.gradcheck
I want to replicate the code
here
, and I get the following error while running in Google Colab?
ImportError: cannot import name 'zero_gradients' from
'torch.autograd.gradcheck'
(/usr/local/lib/python3.7/dist-packages/torch/autograd/gradcheck.py)
Can someone hel... | This seems like it's using a very old version of PyTorch, the function itself is not available anymore. However, if you look at
this commit
, you will see the implementation of
```
zero_gradients
```
. What it does is simply zero out the gradient of the input:
```
def zero_gradients(i):
for t in iter_gradients... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Is there a way to overide the backward operation on nn.Module
I am looking for a nice way of overriding the backward operation in nn.Module for example:
```
class LayerWithCustomGrad(nn.Module):
def __init__(self):
super(LayerWithCustomGrad, self).__init__()
self.weights = nn.Parameter(torch.randn... | The way PyTorch is built you should first implement a custom
```
torch.autograd.Function
```
which will contain the forward
and
backward pass for your layer. Then you can create a
```
nn.Module
```
to wrap this function with the necessary parameters.
In this
tutorial page
you can see the ReLU being impleme... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch RuntimeError: device >= 0 && device < num_gpus INTERNAL ASSERT FAILED
I'm trying to perform some inference with
```
YOLOv8
```
models, simply using the following command:
```
yolo detect predict source=input.jpg model=yolov8n.pt device=0
```
But I'm getting this error related to PyTorch (m... | This was a bug in PyTorch. To solve, find and go to
```
python3.xx\site-packages\torch\cuda\__init__.py
```
and modify this function:
Remove or comment out this old function:
```
'''
@lru_cache(maxsize=1)
def device_count() -> int:
r"""Return the number of GPUs available."""
if not _is_compiled():
ret... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | In PyTorch is GPU memory freed when a GPU tensor is assigned a new value?
When a Cuda variable in PyTorch is assigned a new value, it becomes a CPU variable again (As illustrated by the code below). In this case, is the memory held by the variable on the GPU previously is freed automatically?
```
import torch
t1 = t... | In python an object is freed as soon as there are no remaining references to it. Since you assign
```
t1
```
to reference a brand new tensor there are no more references to the original GPU tensor so that tensor is freed. That said, when PyTorch is instructed to free a GPU tensor it tends to cache that GPU memory f... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Python matplotlib, invalid shape for image data
Currently I have this code to show three images:
```
imshow(image1, title='1')
imshow(image2, title='2')
imshow(image3, title='3')
```
And it works fine. But I am trying to put them all three in a row instead of column.
Here is the code I have tried:
```
f = plt.fi... | The matplotlib function 'imshow' gets 3-channel pictures as (h, w, 3) as you can see in the
documentation
.
It seems that you passed a "batch" of single image (the first dimention) of three channels (second dimention) of the image (h and w are the third and forth dimention).
You need to reshape or view your image (a... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Loss doesn't decrease in Pytorch CNN
I'm doing a CNN with Pytorch for a task, but it won't learn and improve the accuracy. I made a version working with the MNIST dataset so I could post it here. I'm just looking for an answer as to why it's not working. The architecture is fine, I implemented it in Keras and I ha... | First the major issues...
1.
The main issue with this code is that you're using the wrong output shape and the wrong loss function for classification.
```
nn.BCELoss
```
computes the
binary
cross entropy loss. This is applicable when you have one or more targets which are either 0 or 1 (hence the binary). In you... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Is a .pth file a security risk, and how can we sanitise it?
It's well-established that pickled files are [unsafe][1] to simply load directly. However, the advice on that SE post concludes that basically one should not use a pickled file if they are not sure of its provenance.
What about PyTorch machine-learning mode... | As pointed out by
```
@MobeusZoom
```
, this is answer is about Pickle and not PyTorch format. Anyway as
PyTorch load mechanism relies on Pickle behind the scene
observations drawn in this answer still apply.
TL;DR;
Don't try to sanitize pickle. Trust or reject.
Quoted from Marco Slaviero in his presentation
S... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | No module named "Torch"
I successfully installed pytorch via conda:
```
conda install pytorch-cpu torchvision-cpu -c pytorch
```
I also successfully installed pytorch via pip:
```
pip3 install https://download.pytorch.org/whl/cpu/torch-1.0.1-cp36-cp36m-win_amd64.whl
pip3 install torchvision
```
But, it... | Try to install PyTorch using pip:
First create a Conda environment using:
```
conda create -n env_pytorch python=3.6
```
Activate the environment using:
```
conda activate env_pytorch
```
Now install PyTorch using pip:
```
pip install torchvision
```
Note
: This will install both torch and torchvision.
Now ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | CNN Pytorch Error : Input type (torch.cuda.ByteTensor) and weight type (torch.cuda.FloatTensor) should be the same
I'm receiving the error,
Input type (torch.cuda.ByteTensor) and weight type (torch.cuda.FloatTensor) should be the same
Following is my code,
```
device = torch.device('cuda:0')
trainData = torchvi... | Cast your input
```
x_batch
```
to float. Use
```
x_batch = x_batch.float()
```
before you pass it through your model. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Passing tensorDataset or Dataloader to skorch
I want to apply cross validation in Pytorch using skorch, so I prepared my model and my tensorDataset which returns (image,caption and captions_length) and so it has X and Y, so I'll not be able to set Y in the method
```
net.fit(dataset)
```
but when I tried that I go... | You are (implicitly) using the internal CV split of skorch which uses a stratified split in case of the
```
NeuralNetClassifier
```
which in turn needs information about the labels beforehand.
When passing
```
X
```
and
```
y
```
to
```
fit
```
separately this works fine since
```
y
```
is accessi... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to resolve runtime error due to size mismatch in PyTorch?
I am trying to implement a simple autoencoder using
```
PyTorch
```
. My dataset consists of 256 x 256 x 3 images. I have built a
```
torch.utils.data.dataloader.DataLoader
```
object which has the image stored as tensor. When I run the autoencoder, ... | Whenever you have:
```
RuntimeError: size mismatch, m1: [a x b], m2: [c x d]
```
all you have to care is
```
b=c
```
and you are done:
```
m1
```
is
```
[a x b]
```
which is
```
[batch size x in features]
```
```
m2
```
is
```
[c x d]
```
which is
```
[in features x out features]
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Convert pytorch tensor to opencv mat and vice versa in C++
I want to convert pytorch tensors to opencv mat and vice versa in C++. I have these two functions:
```
cv::Mat TensorToCVMat(torch::Tensor tensor)
{
std::cout << "converting tensor to cvmat\n";
tensor = tensor.squeeze().detach().permute({1, 2, 0});
... | I am using torch>=1.7.0.
For a tensor of
dtype=uint8
and size
[1, 3, height, width]
this is what worked for me
```
cv::Mat torchTensortoCVMat(torch::Tensor& tensor)
{
tensor = tensor.squeeze().detach();
tensor = tensor.permute({1, 2, 0}).contiguous();
tensor = tensor.mul(255).clamp(0, ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | how to apply gradients manually in pytorch
Starting to learn pytorch and was trying to do something very simple, trying to move a randomly initialized vector of size 5 to a target vector of value [1,2,3,4,5].
But my distance is not decreasing!! And my vector
```
x
```
just goes crazy. No idea what I am missing.
... | There are two errors in your code that prevents you from getting the desired results.
The first error is that you should put the distance calculation in the loop. Because the distance is the loss in this case. So we have to monitor its change in each iteration.
The second error is that you should manually zero out t... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to fix 'Input and hidden tensors are not at the same device' in pytorch
When I want to put the model on the GPU, I get the following error:
"RuntimeError: Input and hidden tensors are not at the same device, found input tensor at cuda:0 and hidden tensor at cpu"
However, all of the above had been put on ... | You need to move the model, the inputs, and the targets to Cuda:
```
if torch.cuda.is_available():
model.cuda()
inputs = inputs.cuda()
target = target.cuda()
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Python: BERT Error - Some weights of the model checkpoint at were not used when initializing BertModel
I am creating an entity extraction model in PyTorch using
```
bert-base-uncased
```
but when I try to run the model I get this error:
```
Some weights of the model checkpoint at D:\Transformers\bert-entity-extra... | As R. Marolahy suggests, if you don't want to see this every time, I know I don't, add the following:
```
from transformers import logging
logging.set_verbosity_error()
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to assign NaN to tensor element?
I want to assign NaN to a tensor element.
```
import torch
x = torch.tensor([1, 2, 3])
x[x == 2] = None
```
I have the error:
```
TypeError: can't assign a NoneType to a torch.LongTensor
```
I need it to make sure that some later sophisticated calculations are not made for cer... | The following code will set the desired value to
```
nan
```
:
```
import torch
x = torch.tensor([1, 2, 3]).float()
x[x == 2] = float('nan')
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | One hot encoding in pytorch
I am really new to coding, right now I am trying to turn my label to one hot encoding. I have already done transferring the np.array to tensor as shown below
```
tensor([4., 4., 4., 4., 4., 4., 4., 4., 4., 4., 4., 4., 4., 4., 4., 1., 1., 1.,
1., 1., 1., 1., 1., 1., 1., 1., 1., 1., ... | You will have to convert it in
```
long
```
type. Can't do it with float.
```
F.one_hot
```
only takes LongTensor.
```
F.one_hot(t.long())
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: 0D or 1D target tensor expected, multi-target not supported I was training a deep learning model but I am getting this issue
```
*My Training Model*
def train(model,criterion,optimizer,iters):
epoch = iters
train_loss = []
validaion_loss = []
train_acc = []
validation_acc = []
sta... | Your problem is that labels have the correct shape to calculate the loss. When you add
```
.unsqueeze(1)
```
to labels you made your labels with this shape [32,1] which is not consistent to the requirment to calcualte the loss.
To fix the problem, you only need to remove
```
.unsqueeze(1)
```
for labels.
If y... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Convert PyTorch CUDA tensor to NumPy array
How do I convert a
```
torch.Tensor
```
(on GPU) to a
```
numpy.ndarray
```
(on CPU)? | Use
```
.detach()
```
to convert from GPU / CUDA Tensor to numpy array:
```
tensor.detach().cpu().numpy()
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | groupby aggregate mean in pytorch
I have a 2D tensor:
```
samples = torch.Tensor([
[0.1, 0.1], #-> group / class 1
[0.2, 0.2], #-> group / class 2
[0.4, 0.4], #-> group / class 2
[0.0, 0.0] #-> group / class 0
])
```
and a label for each sample corresponding to a class:
```
labels = to... | All you need to do is form an mxn matrix (m=num classes, n=num samples) which will select the appropriate weights, and scale the mean appropriately. Then you can perform a matrix multiplication between your newly formed matrix and the samples matrix.
Given your labels, your matrix should be (each row is a class numbe... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch MNIST autoencoder to learn 10-digit classification
I'm trying to build a simple autoencoder for MNIST, where the middle layer is just 10 neurons. My hope is that it will learn to classify the 10 digits, and I assume that would lead to the lowest error in the end (wrt reproducing the original image).
I have th... | Autoencoder is technically not used as a classifier in general. They learn how to encode a given image into a short vector and reconstruct the same image from the encoded vector. It is a way of compressing image into a short vector:
Since you want to train autoencoder with classification capabilities, we need to make ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | 1D CNN on Pytorch: mat1 and mat2 shapes cannot be multiplied (10x3 and 10x2)
I have a time series with sample of 500 size and 2 types of labels and want to construct a 1D CNN with pytorch on them:
```
class Simple1DCNN(torch.nn.Module):
def __init__(self):
super(Simple1DCNN, self).__init__()
self.... | The shape of the output of the line
```
x = self.layer2(x)
```
(which is also the input of the next line
```
x = self.fc1(x)
```
) is
```
torch.Size([1, 10, 3])
```
.
Now from the definition of
```
self.fc1
```
, it expects the last dimension of it's input to be
```
10 * 1 * 1
```
which is
```
10
``... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to train model with multiple GPUs in pytorch？
My server has two GPUs, How can I use two GPUs for training at the same time to maximize their computing power? Is my code below correct? Does it allow my model to be properly trained?
```
class MyModel(nn.Module):
def __init__(self):
super(MyModel, self).... | There are two different ways to train on multiple GPUs:
Data Parallelism = splitting a large batch that can't fit into a single GPU memory into multiple GPUs, so every GPU will process a small batch that can fit into its GPU
Model Parallelism = splitting the layers within the model into different devices is a bit tr... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Channel wise CrossEntropyLoss for image segmentation in pytorch
I am doing an image segmentation task. There are 7 classes in total so the final outout is a tensor like [batch, 7, height, width] which is a softmax output. Now intuitively I wanted to use CrossEntropy loss but the pytorch implementation doesn't work on ... | As Shai's answer already states, the documentation on the
```
torch.nn.CrossEntropy()
```
function can be found
here
and the code can be found
here
. The built-in functions do indeed already support KD cross-entropy loss.
In the 3D case, the
```
torch.nn.CrossEntropy()
```
functions expects two arguments: ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | mat1 and mat2 must have the same dtype
I'm trying to build a neural network to predict per-capita-income for counties in US based on the education level of their citizens.
X and y have the same dtype (I have checked this) but I'm getting an error.
Here is my data:
```
county_FIPS state county per_capita_... | The reason for this is because the parameters dtype of
```
nn.Linear
```
doesn't match your input's dtype; the default dtype for
```
nn.Linear
```
is
```
torch.float32
```
which is in your case different from your input data -
```
float64
```
.
The solution to
this question
solves your problem and exp... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | I am trying to import:from torchtext.legacy.data import Field, BucketIterator,Iterator,data, but get error 'No module named 'torchtext.legacy'
I am trying to execute the following code for a nlp proj
```
import torchtext
from torchtext.legacy.data import Field, BucketIterator, Iterator
from torchtext.lega... | Before you
```
import torchtext.legacy
```
, you need to
```
!pip install torchtext==0.10.0
```
.
Maybe legacy was removed in version 0.11.0. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Specifying cpu-only for pytorch in conda YAML file
I can set up a conda environment successfully as follows:
```
conda create --name temp python=3.8.5
conda install pytorch==1.6.0 torchvision==0.7.0 cpuonly -c pytorch
```
I then save the environment to a YAML config file. The looks like this:
```
name: temp
channe... | For systems that have optional CUDA support (Linux and Windows) PyTorch provides a mutex metapackage
```
cpuonly
```
that when installed constrains the
```
pytorch
```
package solve to only non-CUDA builds. Going through
the PyTorch installation widget
will suggest including the
```
cpuonly
```
package wh... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | BCEWithLogitsLoss: Trying to get binary output for predicted label as a tensor, confused with output layer
Each element of my dataset has a multi-label tensor like
```
[1, 0, 0, 1]
```
with varying combinations of
```
1's
```
and
```
0's
```
. In this scenario, since I have 4 tensors, I have the output laye... | When using
```
BCEWithLogitsLoss
```
you make a 1D prediction per output binary label.
In your example, you have 4 binary labels to predict, and therefore, your model outputs 4d vector, each entry represents the prediction of one of the binary labels.
Using
```
BCEWithLogitsLoss
```
you
implicitly
apply Sig... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch: _thnn_nll_loss_forward is not implemented for type torch.LongTensor
When trying to create a model using PyTorch, when I am trying to implement the loss function
```
nll_loss
```
, it is throwing the following error
```
RuntimeError: _thnn_nll_loss_forward is not implemented for type torch.LongTensor
```... | Look at the
description
of
```
F.nll_loss
```
. It expects to get as input not the
```
argmax
```
of the prediction (type
```
torch.long
```
), but rather the full 64x50x43 prediction vectors (of type
```
torch.float
```
). Note that indeed the prediction you provide to
```
F.nll_loss
```
has an extr... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | please use torch.load with map_location=torch.device('cpu')
I am running Python program, but I do not have a GPU, what can I do to make Python use CPU instead of GPU?
```
$ python extract_feature.py --data mnist --net checkpoint_4.pth.tar --features pretrained
```
It gives me the following warning:
=> Runt... | I got into a similar error. Then by trying the following workaround issue is solved. (If your model is .pth or .h5 format.)
```
MODEL_PATH = 'Somemodelname.pth'
model.load_state_dict(torch.load(MODEL_PATH,
map_location=torch.device('cpu')))
```
If you want certain GPU to be used in your machine. Then,
```
map_loc... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Whats the purpose of torch.positive?
From the
documentation
:
```
torch.positive(input)
```
→
```
Tensor
```
Returns
```
input
```
. Throws a runtime error if input is a bool tensor.
It just returns the input and throws error if its a
```
bool
```
tensor, but that's not an efficient nor readable way of ... | It seems like pytorch added
```
pytorch.positive
```
in parity with
```
numpy
```
which has a
function of the same name
.
So back to your question,
```
positive
```
is a unary operator which basically multiplies everything by
```
+1
```
. This is not a particularly useful operation, but is symmetric t... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AttributeError: 'torch.return_types.max' object has no attribute 'dim' - Maxpooling Channel
I'm trying to do maxpooling over channel dimension:
```
class ChannelPool(nn.Module):
def forward(self, input):
return torch.max(input, dim=1)
```
but I get the error
```
AttributeError: 'torch.r... | The
```
torch.max
```
function called with
```
dim
```
returns a tuple so:
```
class ChannelPool(nn.Module):
def forward(self, input):
input_max, max_indices = torch.max(input, dim=1)
return input_max
```
From the
documentation of torch.max
:
Returns a namedtuple (values, indices) where... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Problem with building PyTorch from source on Linux
❓ Problem with building PyTorch from source
Hello everyone,
I have problem with building PyTorch from source. I followed the
official build instructions
. I use Anaconda Python 3.7.1 (version 2018.12, build py37_0). I installed all neccessary dependencies using
`... | Problem solved.
I found what was wrong and I fixed it. The whole problem lies in the fact that Anaconda distribution comes with its own ld linker that is located in /opt/anaconda/compiler_compat/ and it overshadows system ld residing at /usr/bin.
To fix my error I ran python setup.py clean and then I temporarily re... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError occurs in PyTorch backward function
I am trying to calculate the grad of a variable in PyTorch. However, there was a RuntimeError which tells me that the shape of output and grad must be the same. However, in my case, the shape of output and grad cannot be the same. Here is my code to reproduce:
```
impo... | First of all you don't need to use numpy and then convert to Variable (which is deprecated by the way), you can just use
```
G = torch.rand(m, n)
```
etc. Second, when you write
```
out.backward(z)
```
, you are passing
```
z
```
as the
gradient
of
```
out
```
, i.e.
```
out.backward(gradient=z)
```
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars
I'm currently working with the PyTorch framework and trying to understand foreign code. I got an indices issue and wanted to print the shape of a list.
The only way of doing so (as far as Google tells me) is to conve... | It seems like you have a list of tensors. For each tensor you can see its
```
size()
```
(no need to convert to list/numpy). If you insist, you can convert a tensor to numpy array using
```
numpy()
```
:
Return a list of tensor shapes:
```
>> [t.size() for t in my_list_of_tensors]
```
Returns a list of numpy... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Which PyTorch modules are affected by model.eval() and model.train()?
The
```
model.eval()
```
method modifies certain modules (layers) which are required to behave differently during training and inference. Some examples are listed in
the docs
:
This has [an] effect only on certain modules. See documentations o... | In addition to info provided by
@iacob
:
Base class
Module
Criteria
```
RNNBase
```
RNN
LSTM
GRU
```
dropout > 0
```
(default:
```
0
```
)
Transformer layers
Transformer
TransformerEncoder
TransformerDecoder
```
dropout > 0
```
(
```
Transformer
```
default:
```
0.1
```
)
Lazy variants... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Understanding gradient computation using backward() in PyTorch
I'm trying to understand the basic pytorch autograd system:
```
x = torch.tensor(10., requires_grad=True)
print('tensor:',x)
x.backward()
print('gradient:',x.grad)
```
output:
```
tensor: tensor(10., requires_grad=True)
gradient: tensor(1.)
```
since... | Whenever you are using
```
value.backward()
```
, you compute the derivative
```
value
```
(in your case
```
value == x
```
) with respect to all your parameters (in your case that is just
```
x
```
). Roughly speaking, this means all tensors that are somehow involved in your computation that have
```
re... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | TypeError: forward() missing 1 required positional argument: 'hidden'
I'm trying to visualize my GRU model using PyTorchViz but every time I run this code it gives me an error.
I want something like this in the
```
import torch
from torch import nn
from torchviz import make_dot, make_dot_from_trace
model = ... | I think the error message is pretty straight forward. You have two positional arguments
```
input_tokens
```
and
```
hidden
```
for your
```
forward()
```
.
Python complains that one of them (
```
hidden
```
) is missing when you call your
```
forward()
```
function.
Looking at your code, you call... |
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