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. | pytorch instance tensor not moved to gpu even with explicit cuda() call
I'm working on a project where the model requires access to a tensor that i declare in the constructor
init
of the class (im sub-classing torch.nn.Module class) and then i need to use this tensor in the forward() method via a simple matmul() , ... | Let's assume the following:
```
X
```
is moved correctly to the GPU
The tensor declared in the
```
Model
```
class is a simple attribute.
i.e. Something like the following:
```
class Model(nn.Module):
def __init__(self):
super().__init__()
self.matrix = torch.randn(784, 10)
def for... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Cannot fix ImportError: cannot import name 'ToTensorV2' from 'albumentations.pytorch' on Colab
I tried all three solutions from
this question
to solve the problem, but still receive an error:
```
ImportError: cannot import name 'ToTensorV2' from 'albumentations.pytorch' (/usr/local/lib/python3.7/dis... | Have you tried factory resetting the runtime? If you haven't, maybe python was still loading the earlier version. I have just tested the accepted solution from the linked question on a fresh colab instance and it worked fine:
```
!pip install albumentations==0.4.6
import albumentations
from albumentations.pytorch imp... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | bool value of Tensor with more than one value is ambiguous
I'm writing a neural network to do regression and here is my codes:
```
class Model(nn.Module):
def __init__(self, input_size, hidden_size, num_classes):
super().__init__()
self.h1 = nn.Linear(input_size, hidden_size)
self.h2 = nn.... | The issue originates from calling
```
torch.nn.MSELoss(out, target)
```
which is the constructor for the
```
MSELoss
```
which accepts
```
size_average
```
and
```
reduce
```
as the first and second optional positional arguments.
```
loss = torch.nn.MSELoss(out, target)
```
Instead, you need to creat... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Model() got multiple values for argument 'nr_class' - SpaCy multi-classification model (BERT integration)
Hi I am working on implementing a multi-classification model (5 classes) with the new SpaCy Model
```
en_pytt_bertbaseuncased_lg
```
. The code for the new pipe is here:
```
nlp = spacy.load('en_pytt_b... | This is a regression in the most recent version we released of
```
spacy-pytorch-transformers
```
. Sorry about this!
The root cause is, this is another case of the evils of
```
**kwargs
```
. I'm looking forward to refining the spaCy API to prevent these issues in future.
You can see the offending line here:
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | 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. | PyTorch flexibility
PyTorch models are very flexible objects, to the point where they do not enforce or generally expect a fixed input shape for data.
If you have certain layers there may be constraints e.g:
a flatten followed by a fully connected layer of width N would enforce the dimensions of your original input ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Tried installing FastAi but I got "ERROR: No matching distribution found for torchvision>=0.7"
I tried installing Fast Ai using the command
```
pip install fastai
```
But then I got this error
ERROR: Could not find a version that satisfies the requirement torchvision>=0.7 (from fastai) (from versions:... | The error just means that you are missing a required library of the given version
```
PyTorch>=0.7
```
.
As it states in the
Instructions
if you installing it by using
```
pip
```
make sure to install
```
pytorch
```
manually to the required version. You can see
here
on instructions for installing
```... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch set_grad_enabled(False) vs with no_grad():
Assuming autograd is on (as it is by default), is there any difference (besides indent) between doing:
```
with torch.no_grad():
<code>
```
and
```
torch.set_grad_enabled(False)
<code>
torch.set_grad_enabled(True)
``` | Actually no, there no difference in the way used in the question. When you take a look at the source code of
```
no_grad
```
. You see that it is actually using
```
torch.set_grad_enabled
```
to archive this behaviour:
```
class no_grad(object):
r"""Context-manager that disabled gradient calculation.
D... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Why PyTorch nn.Module.cuda() not moving Module tensor but only parameters and buffers to GPU?
```
nn.Module.cuda()
```
moves all model parameters and buffers to the GPU.
But why not the model member tensor?
```
class ToyModule(torch.nn.Module):
def __init__(self) -> None:
super(ToyModule, self).__init_... | If you define a tensor inside the module it needs to be registered as either a parameter or a buffer so that the module is aware of it.
Parameters
are tensors that are to be trained and will be returned by
```
model.parameters()
```
. They are easy to register, all you need to do is wrap the tensor in the
```
nn... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Understanding torch.nn.Flatten
I understand that Flatten removes all of the dimensions except for one. For example, I understand
flatten()
:
```
> t = torch.ones(4, 3)
> t
tensor([[1., 1., 1.],
[1., 1., 1.],
[1., 1., 1.],
[1., 1., 1.]])
> flatten(t)
tensor([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.... | It is a difference in the default behaviour.
```
torch.flatten
```
flattens all dimensions by default, while
```
torch.nn.Flatten
```
flattens all dimensions starting from the second dimension (index 1) by default.
You can see this behaviour in the default values of the
```
start_dim
```
and
```
end_dim
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AttributeError: cannot assign module before Module.__init__() call
I am getting the following error:
```
Traceback (most recent call last):
File "main.py", line 63, in <module>
question_classifier = QuestionClassifier(corpus.dictionary, embeddings_index, corpus.max_sent_length, args)
File "/net/if5/wua4nw/was... | Looking at the
```
pytorch
```
source code for
```
Module
```
, we see in the docstring an example of deriving from
```
Module
```
includes:
```
class Model(nn.Module):
def __init__(self):
super(Model, self).__init__()
self.conv1 = nn.Conv2d(1, 20, 5)
self.conv2... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch: AttributeError: 'function' object has no attribute 'copy'
I am trying to load a model
```
state_dict
```
I trained on Google Colab GPU, here is my code to load the model:
```
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
model = models.resnet50()
num_ftrs = mode... | I am guessing this is what you did by mistake.
You saved the function
```
torch.save(model.state_dict, 'model_state.pth')
```
instead of the state_dict()
```
torch.save(model.state_dict(), 'model_state.pth')
```
Otherwise, everything should work as expected. (I tested the following code on Colab)
Replace
```
mo... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AttributeError: 'Upsample' object has no attribute 'recompute_scale_factor'
I get error on line
```
x_stats = dec(z).float()
```
.
```
import torch.nn.functional as F
z_logits = enc(x)
z = torch.argmax(z_logits, axis=1)
z = F.one_hot(z, num_classes=enc.vocab_size).permute(0, 3, 1, 2).float()
x_st... | Install Torch version, this will solve the issue
```
pip install torchvision==0.10.1
pip install torch==1.9.1
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How do I assign a numpy.int64 to a torch.cuda.FloatTensor?
Im not able to assign int64 to torch tensor. I have got the following tensor
```
tempScale = torch.zeros((total, len(scale))).cuda() if useGpu else torch.zeros((nbPatchTotal, len(scale)))
```
In my code, when I'm using the following line, it's throwing an ... | You have to convert
```
scale
```
to a torch tensor of the same type and device as
```
tmpScale
```
before assignment.
```
tmpScale[:, j] = torch.from_numpy(scale).to(tmpScale)
```
Note that this is casting
```
scale
```
from an
```
int64
```
to a
```
float32
```
which will likely result in a
lo... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | evaluation_strategy() not supported in transformers library
I've recently been attempting to fine-tune the pretrained neural network, "cardiffnlp/twitter-roberta-base-offensive." However, when I attempted to run a Python program I created, "evaluation_strategy" was considered to be an "unexpected argument" regardless ... | "evaluation_strategy" has been deprecated since version 4.46 of the Hugging Face Transformers library.
https://github.com/huggingface/transformers/pull/30190
Changing
```
evaluation_strategy=""
```
to
```
eval_strategy=""
```
should fix the unexpected argument issue.
Your configuration for the 6-label classi... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Can't install Pytorch in Pycharm terminal, Python 3.10 .win 10
I go to pytorch site and take this
```
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio===0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
```
I have windows 10 ,Python version is 3.10 ,CUDA version is 11... | Check out the official
issue
on Pytorch's Github repository.
I've tried your exact command on python 3.9.5 and it works. I believe the issue is that PyTorch is not supported by python 3.10 yet.
Downgrading to any 3.9 version of Python should solve your problem. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Efficient metrics evaluation in PyTorch
I am new to PyTorch and want to efficiently evaluate among others F1 during my Training and my Validation Loop.
So far, my approach was to calculate the predictions on GPU, then push them to CPU and append them to a vector for both Training and Validation. After Training and Va... | You can compute the F-score yourself in pytorch. The F1-score is defined for single-class (true/false) classification only. The only thing you need is to aggregating the number of:
Count of the class in the ground truth target data;
Count of the class in the predictions;
Count how many times the class was correctly ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Trouble Converting LSTM Pytorch Model to ONNX
I am trying to export my LSTM Anomally-Detection Pytorch model to ONNX, but I'm experiencing errors. Please take a look at my code below.
Note: My data is shaped as [2685, 5, 6].
Here is where I define my model:
```
class Model(torch.nn.Module):
def __init__(self, in... | If you're coming here from Google the previous answers are no longer up to date. ONNX now supports an
LSTM operator
. Take care as exporting from PyTorch will fix the input sequence length by default unless you use the
```
dynamic_axes
```
parameter.
Below is a minimal LSTM export example I adapted from the
torc... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: Expected object of backend CUDA but got backend CPU for argument: ret = torch.addmm(torch.jit._unwrap_optional(bias), input, weight.t())
When the
```
forward
```
function of my neural network (after the training phase is completed) is being executed, I'm experiencing
```
RuntimeError: Expected obje... | The error only happens only at the testing step, when you try calculating the accuracy, this might already give you a hint. The training loop runs without a problem.
The error is simply that you don't send the images and labels to the GPU at this step. This is your corrected evaluation loop:
```
with torch.no_grad():... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch speed comparison - GPU slower than CPU
I was trying to find out if GPU tensor operations are actually faster than CPU ones. So, I wrote this particular code below to implement a simple 2D addition of CPU tensors and GPU cuda tensors successively to see the speed difference:
```
import torch
import time
###CP... | GPU acceleration works by heavy parallelization of computation. On a GPU you have a huge amount of cores, each of them is not very powerful, but the huge amount of cores here matters.
Frameworks like PyTorch do their to make it possible to compute as much as possible in parallel. In general matrix operations are very ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | pytorch: "multi-target not supported" error message
So I want to classify some
```
(3, 50, 50)
```
pictures. First I loaded the dataset from the file without a dataloader or batches, it worked. Now, after adding both things I get that error:
```
RuntimeError: multi-target not supported at /pytorch/aten/... | For
```
nn.CrossEntropyLoss
```
the target has to be a single number from the interval [0, #classes] instead of a one-hot encoded target vector. Your target is [1, 0], thus PyTorch thinks you want to have multiple labels per input which is not supported.
Replace your one-hot-encoded targets:
[1, 0] --> 0
[0, 1] ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Gaussian filter in PyTorch
I am looking for a way to apply a Gaussian filter to an image (tensor) only using PyTorch functions. Using numpy, the equivalent code is
```
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
# Define 2D Gaussian kernel
def gkern(kernlen=256, std=128):
"""Ret... | Yupp I also had the same idea. So now the question becomes: is there a way to define a Gaussian kernel (or a 2D Gaussian) without using Numpy and/or explicitly specifying the weights?
Yes, it is pretty easy. Just have a look to the function documentation of
signal.gaussian
. There is a link to the
source code
. So w... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch mask missing values when calculating rmse
I'm trying to calculate the rmse error of two torch tensors. I would like to ignore/mask the rows where the labels are 0 (missing values). How could I modify this line to take that restriction into account?
```
torch.sqrt(((preds.detach() - labels) ** 2).mean()).item... | This can be solved by defining a custom MSE loss function* that masks out the missing values, 0 in your case, from both the input and target tensors:
```
def mse_loss_with_nans(input, target):
# Missing data are nan's
# mask = torch.isnan(target)
# Missing data are 0's
mask = target == 0
out = (... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Runtime error 999 when trying to use cuda with pytorch
I installed Cuda 10.1 and the latest Nvidia Driver for my Geforce 2080 ti. I try to run a basic script to test if pytorch is working and I get the following error:
```
RuntimeError: cuda runtime error (999) : unknown error at ..\aten\src\THC\THCGeneral.cpp:50
``... | Restarting my computer fixed this for me.
But for a less invasive fix, you can also try this solution (from a
tensorflow issue thread
):
```
sudo rmmod nvidia_uvm
sudo rmmod nvidia
sudo modprobe nvidia
sudo modprobe nvidia_uvm
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: Can only calculate the mean of floating types. Got Byte instead. for mean += images_data.mean(2).sum(0)
I have the following pieces of code:
```
# Device configuration
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
seed = 42
np.random.seed(seed)
torch.manual_seed(seed)
# split ... | As the error says, your
```
images_data
```
is a ByteTensor, i.e. has dtype
```
uint8
```
. Torch refuses to compute the mean of integers. You can convert the data to
```
float
```
with:
```
(images_data * 1.0).mean(2)
```
Or
```
torch.Tensor.float(images_data).mean(2)
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch NLP Huggingface: model not loaded on GPU
I have this code that init a class with a model and a tokenizer from Huggingface.
On Google Colab this code works fine, it loads the model on the GPU memory without problems.
On Google Cloud Platform it does not work, it loads the model on gpu, whatever I try.
```
clas... | You should use the
```
.to(device)
```
method like this:
```
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = nameofyourmodel.to(device)
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Gradients returning None in huggingface module
I want to get the gradient of an embedding layer from a pytorch/huggingface model. Here's a minimal working example:
```
from transformers import pipeline
nlp = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
responses = ["I'm having a great day!... | I was also very surprised of this issue. Although I have never used the library I went down and did some debugging and found out that the issue is coming from the library transformers. The problem is comming from from this
line
:
```
encoder_states = tuple(hidden_state.transpose(0, 1) for hidden_state in encoder_sta... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | I can't load my model because I can't put a PosixPath
I'm setting up a script and I need to use some functions from
```
fast-ai
```
package. The fact is that I'm on Windows and when I define my paths, the function from
```
fast-ai
```
named
```
load_learner
```
can't load the model.
I've tried to ... | Just redirect
```
PosixPath
```
to
```
WindowsPath
```
.
```
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath
```
I am also loading
```
fastai
```
models and this trick works.
IMPORTANT
: Since this might cause issues later, remember to set
```
pathlib.PosixPath = temp
``... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Taking sample from Categorical distribution pytorch
I'm currently working on a Deep reinforcement learning problem, and I'm using the categorical distribution to help the agent get random action. This is the code.
```
def choose_action(self,enc_current_node,goal_node):
#print('nn')
#vector=self.convert_... | If you look at your probabilities for sampling
```
probs
```
, you see that the
```
1
```
th class has the largest probability, and almost all others are < 1%. If you are not familiar with scientific notation, here it is formatted as rounded percentages:
```
for label, p in enumerate(probs[0]):
print(f'{labe... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Comparing Conv2D with padding between Tensorflow and PyTorch
I am trying to import weights saved from a Tensorflow model to PyTorch. So far the results have been very similar. I ran into a snag when the model calls for
```
conv2d
```
with
```
stride=2
```
.
To verify the mismatch, I set up a very simple compar... | To replicate the behavior, padding sizes are calculated as described in the Tensorflow documentation. Here, I test the padding behavior by setting
```
stride=2
```
and padding the PyTorch input.
```
import tensorflow as tf
import numpy as np
import torch
import torch.nn.functional as F
np.random.seed(0)
sess = tf... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Does batch_first affect hidden tensors in Pytorch LSTMs?
Does
```
batch_first
```
affect hidden tensors in Pytorch LSTMs?
That is if
```
batch_first
```
parameter is true,
Will the hidden state be
```
(numlayer*direction,num_batch,encoding_dim)
```
or
```
(num_batch,numlayer*direction,encoding_dim)
```
... | I was thinking about the same question some time ago. Like laydog outlined, in the documentation it says
batch_first – If True, then the input and output tensors are provided
as (batch, seq, feature)
As I understand the question we are talking about the hidden / cell state tuple, not the actual inputs and outputs.... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Input type into Linear4bit is torch.float16, but bnb_4bit_compute_type=torch.float32 (default). This will lead to slow inference or training speed
I am trying to run Llama 2.0 on my computer with server and it warns me that my speed is going to be less as I am making some mistake which I am unaware of, however, it wor... | You can find the solution in the next
Notebook
, use something like:
```
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_use_double_quant=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16
)
```
When you load your model using from_pretrained() Transformers method:
```
model = Aut... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | torch.cuda.is_available() returns false in colab
I am trying to use GPU in google colab. Below are the details of the versions of pytorch and cuda installed in my colab.
```
Torch 1.3.1 CUDA 10.1.243
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_20... | Make sure your Hardware accelerator is set to GPU.
```
Runtime > Change runtime type > Hardware Accelerator
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | What is tape-based autograd in Pytorch?
I understand
```
autograd
```
is used to imply automatic differentiation. But what exactly is
```
tape-based autograd
```
in
```
Pytorch
```
and why there are so many discussions that affirm or deny it.
For example:
this
In pytorch, there is no traditional sense o... | There are different types of automatic differentiation e.g.
```
forward-mode
```
,
```
reverse-mode
```
,
```
hybrids
```
; (
more explanation
). The
```
tape-based
```
autograd in
```
Pytorch
```
simply refers to the uses of
reverse-mode
automatic differentiation,
source
. The
reverse-mode
auto d... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Duplicate layers when reusing pytorch model
I am trying to reuse some of the resnet layers for a custom architecture and ran into a issue I can't figure out. Here is a simplified example; when I run:
```
import torch
from torchvision import models
from torchsummary import summary
def convrelu(in_channels, out_channe... | Your layers aren't actually being invoked twice. This is an artifact of how
```
summary
```
is implemented.
The simple reason is because
```
summary
```
recursively iterates over all the children of your module and registers forward hooks for each of them. Since you have repeated children (in
```
base_model
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AMD ROCm with Pytorch on Navi10 (RX 5700 / RX 5700 XT)
I am one of those miserable creatures who own a AMD GPU (RX 5700, Navi10). I want to use up-to-date PyTorch libraries to do some Deep Learning on my local machine and stop using cloud instances.
I saw all over the internet that AMD is promising Navi10 support in ... | Set the
```
HSA_OVERRIDE_GFX_VERSION=10.3.0
```
environment variable.
For example, in the terminal, input:
```
$ HSA_OVERRIDE_GFX_VERSION=10.3.0 python launch.py
```
I used 5700xt to run stable-diffusion for months, it works. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | NameError: name 'nn' is not defined
Several times when I copy PyTorch code I get this error:
```
NameError: name 'nn' is not defined
```
What is missing? What is
```
nn
```
?
To reproduce:
```
class SLL(nn.Module):
"single linear layer"
def __init__(self):
super().__init__()
sel... | If you got this error you can fix it with the following code:
```
import torch
import torch.nn as nn
```
You need to include both lines, since if you set just the second one it may not work if the
```
torch
```
package is not imported.
Where
```
torch
```
and
```
torch.nn
```
(or just
```
nn
```
) ar... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Getting gradient of vectorized function in pytorch
I am brand new to PyTorch and want to do what I assume is a very simple thing but am having a lot of difficulty.
I have the function
```
sin(x) * cos(x) + x^2
```
and I want to get the derivative of that function at any point.
If I do this with one point it wo... | Here
you can find relevant discussion about your error.
In essence, when you call
```
backward()
```
without arguments it is implicitly converted to
```
backward(torch.Tensor([1]))
```
, where
```
torch.Tensor([1])
```
is the output value with respect to which gradients are calculated.
If you pass
```
4... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Unable to import pytorch_lightning on google colab
I have done the following:
```
!pip install pytorch_lightning -qqq
import pytorch_lightning
```
But get the following error:
```
ImportError Traceback (most recent call last)
<ipython-input-7-d883b15aac58> in <module>()
----> 1 import... | As said in Issue #6415 on
Github
, try installing from the GitHub.
It worked for me.
```
!pip install git+https://github.com/PyTorchLightning/pytorch-lightning
import pytorch_lightning as pl
print(pl.__version__)
```
Output:
```
1.3.0dev
```
It seems that the error is coming from
Issue #6210
and they say it w... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Understanding the PyTorch implementation of Conv2DTranspose
I am trying to understand an example snippet that makes use of the PyTorch transposed convolution function, with documentation
here
, where in the docs the author writes:
"The padding argument effectively adds dilation * (kernel_size - 1) -
padding amount o... | The output spatial dimensions of
```
nn.ConvTranspose2d
```
are given by:
```
out = (x - 1)s - 2p + d(k - 1) + op + 1
```
where
```
x
```
is the
input
spatial dimension and
```
out
```
the corresponding
output
size,
```
s
```
is the stride,
```
d
```
the dilation,
```
p
```
the padding,
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Is it possible to run multiple CUDA version on windows?
I am doing an experiment on a chest x-ray Project. and I want multiple versions of the CUDA toolkit but the problem is that my system put the latest version which I installed lastly is appearing.
Is it possible to run any of CUDA like 9.0, 10.2, 11.0 as required ... | You may set CUDA_PATH_V9_0, CUDA_PATH_V10_0, etc properly, then set CUDA_PATH to any one of them (e.g. CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0).
Then in your VS project, set your cuda library path using the CUDA_PATH (e.g. $CUDA_PATH\lib).
To switch, just set the CUDA_PATH to another version... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AttributeError: 'tuple' object has no attribute 'log_softmax'
while trying to finetune inception_V3 for my own dataset by changing the last fc layer like
```
last_layer =nn.Linear(n_inputs, len(classes))
inception_v3.fc = last_layer
```
after that when I train it got this error on this position
``... | This is a well known problem.
Try one the following solutions:
disable aux_logits when the model is created here by also passing
```
aux_logits=False
```
to the inception_v3 function.
edit your train function to accept and unpack the returned tuple to be something like:
```
output, aux = model(input_var)
`... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch detection of CUDA
Which is the
command
to see the "correct" CUDA Version that
```
pytorch
```
in conda env is seeing?
This
, is a similar question, but doesn't get me far.
```
nvidia-smi
```
says I have cuda version
```
10.1
```
```
conda list
```
tells me cudatoolkit version is
```
10.2.89
`... | In the conda env (myenv) where pytorch is installed do the following:
```
conda activate myenv
torch.version.cuda
```
```
Nvidia-smi
```
only shows compatible version. Does not seem to talk about the version
```
pytorch
```
's own cuda is built on. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch torch.load ModuleNotFoundError: No module named 'utils'
I'm trying to load a pretrained model with torch.load.
I get the following error:
```
ModuleNotFoundError: No module named 'utils'
```
I've checked that the path I am using is correct by opening it from the command line. What could be causing ... | I've had the same exact error and was wondering what the problem was.
Turns out the problem is that the data saved with
```
torch.load()
```
needed the module
```
utils
```
.
Example:
```
from utils import some_function
model = some_function()
torch.save(model)
```
When saving with torch in the given exampl... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to save LambdaLR scheduler in pytorch with lambda function?
Running pytorch 0.4.1 with python 3.6 I encountered this problem:
I cannot
```
torch.save
```
my learning rate scheduler because python won't pickle a lambda function:
```
lambda1 = lambda epoch: epoch // 30
scheduler = LambdaLR(optimizer, lr_lambda... | If one wishes to stay with default behavior of
```
torch.save
```
and
```
torch.load
```
, the lambda function can be replaced with a class, for example:
```
class LRPolicy(object):
def __init__(self, rate=30):
self.rate = rate
def __call__(self, epoch):
return epoch // self.rate
```
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Tensor for argument #2 'mat1' is on CPU, but expected it to be on GPU
Following my previous
question
, I have written this code to train an autoencoder and then extract the features.
(There might be some changes in the variable names)
```
# Autoencoder class
#https://medium.com/pytorch/implementing-an-autoe... | I see that Your model is moved to
device
which is decided by this line
```
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
```
This can be is either
```
cpu
```
or
```
cuda
```
.
So adding this line
```
batch_features = batch_features.to(device)
```
will actually move your input ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Does tf.math.reduce_max allows gradient flow like torch.max?
I am trying to build a multi-label binary classification model in Tensorflow. The model has a
```
tf.math.reduce_max
```
operator between two layers (It is not Max Pooling, it's for a different purpose).
And the number of classes is 3.
I am using Binar... | Yes,
```
tf.math.reduce_max
```
does allow gradients to flow. It is easy to check (this is TensorFlow 2.x but it is the same result in 1.x):
```
import tensorflow as tf
with tf.GradientTape() as tape:
x = tf.linspace(0., 2. * 3.1416, 10)
tape.watch(x)
# A sequence of operations involving reduce_max
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | TransformerEncoder with a padding mask
I'm trying to implement torch.nn.TransformerEncoder with a src_key_padding_mask not equal to none. Imagine the input is of the shape
```
src = [20, 95]
```
and the binary padding mask has the shape
```
src_mask = [20, 95]
```
, 1 in the position of padded tokens and 0 for ... | The required shapes are shown in
```
nn.Transformer.forward
```
- Shape
(all building blocks of the transformer refer to it). The relevant ones for the encoder are:
src:
(S, N, E)
src_mask:
(S, S)
src_key_padding_mask:
(N, S)
where
S
is the sequence length,
N
the batch size and
E
the embedding dimensi... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How do I implement a PyTorch Dataset for use with AWS SageMaker?
I have implemented a PyTorch
```
Dataset
```
that works locally (on my own desktop), but when executed on AWS SageMaker, it breaks. My
```
Dataset
```
implementation is as follows.
```
class ImageDataset(Dataset):
def __init__(self, path='./... | I was able to create a PyTorch
```
Dataset
```
backed by S3 data using
```
boto3
```
. Here's the snippet if anyone is interested.
```
class ImageDataset(Dataset):
def __init__(self, path='./images', transform=None):
self.path = path
self.s3 = boto3.resource('s3')
self.bucket = self.... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to invert a PyTorch Embedding?
I have an multi-task encoder/decoder model in PyTorch with a (trainable)
```
torch.nn.Embedding
```
embedding layer at the input.
In one particular task, I'd like to pre-train the model self-supervised (to re-construct masked input data) and use it for inference (to fill in gaps... | You can do it quite easily:
```
import torch
embeddings = torch.nn.Embedding(1000, 100)
my_sample = torch.randn(1, 100)
distance = torch.norm(embeddings.weight.data - my_sample, dim=1)
nearest = torch.argmin(distance)
```
Assuming you have
```
1000
```
tokens with
```
100
```
dimensionality this would retur... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Converting state-parameters of Pytorch LSTM to Keras LSTM
I was trying to port an existing trained PyTorch model into Keras.
During the porting, I got stuck at LSTM layer.
Keras implementation of LSTM network seems to have three state kind of state matrices while Pytorch implementation have four.
For eg, for an Bid... | They are really not that different. If you sum up the two bias vectors in PyTorch, the equations will be the same as what's implemented in Keras.
This is the LSTM formula on
PyTorch documentation
:
PyTorch uses two separate bias vectors for the input transformation (with a subscript starts with
```
i
```
) and re... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch: RuntimeError: expected dtype Float but got dtype Long
I encounter this weird error when building a simple NN in Pytorch. I dont understand this error and why this consern Long and Float datatype in backward function. Anyone encounter this before? Thanks for any help.
```
Traceback (most recent call last):
... | Change the
```
criterion
```
call to:
```
age_loss, gender_loss, race_loss = criterion(output, age.float(), gender, race)
```
If you look at your error we can trace it to:
```
frame #3: at::native::smooth_l1_loss_backward_out
```
In the MultiLoss Class, the
```
smooth_l1_loss
```
works with
```
age
```
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Manually assign weights using PyTorch
I am using Python 3.8 and PyTorch 1.7 to manually assign and change the weights and biases for a neural network. As an example, I have defined a LeNet-300-100 fully-connected neural network to train on MNIST dataset. The code for class definition is:
```
class LeNet300(nn.Module)... | ```
for param in mask_model.parameters():
param.data = nn.parameter.Parameter(torch.ones_like(param))
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Why PyTorch model takes multiple image size inside the model?
I am using a simple object detection model in PyTorch and using a Pytoch Model for Inferencing.
When I am using a simple iterator over the code
```
for k, image_path in enumerate(image_list):
image = imgproc.loadImage(image_path)
print(image.shape... | PyTorch has what is called a
Dynamic Computational Graph
(
other explanation
).
It allows the graph of the neural network to dynamically adapt to its input size, from one input to the next, during training or inference.
This is what you observe in your first example: providing an image as a Tensor of size
```
[1, ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch: DecoderRNN: RuntimeError: input must have 3 dimensions, got 2
I am building a DecoderRNN using PyTorch (This is an image-caption decoder):
```
class DecoderRNN(nn.Module):
def __init__(self, embed_size, hidden_size, vocab_size):
super(DecoderRNN, self).__init__()
self.hidden_size = hidde... | Your GRU input needs to be 3-dimensional:
input
of shape (seq_len, batch, input_size): tensor containing the features of the input sequence.
Further you need to provide the hidden state (last encoder hidden state in this case) as second parameter:
```
self.gru(input, h_0)
```
Where
```
input
```
is your actua... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch `torch.no_grad` vs `torch.inference_mode`
PyTorch has new functionality
```
torch.inference_mode
```
as of v1.9 which is "
analogous to
```
torch.no_grad
```
... Code run under this mode gets better performance by disabling view tracking and version counter bumps."
If I am just evaluating my model at ... | Yes,
```
torch.inference_mode
```
is indeed preferable to
```
torch.no_grad
```
in all situations where inference mode does not throw a runtime error. Check
here
. |
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 two dataloaders simultaneously using pytorch?
I am trying to implement a Siamese network that takes in two images. I load these images and create two separate dataloaders.
In my loop I want to go through both dataloaders simultaneously so that I can train the network on both images.
```
for i, da... | If you want to iterate over two datasets simultaneously, there is no need to define your own dataset class just use TensorDataset like below:
```
dataset = torch.utils.data.TensorDataset(dataset1, dataset2)
dataloader = DataLoader(dataset, batch_size=128, shuffle=True)
for index, (xb1, xb2) in enumerate(dataloader):
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | HTTP Error when trying to download MNIST data
I am using Google Colab for training a LeNet-300-100 fully-connected neural network on MNIST using Python3 and PyTorch 1.8.
To apply the transformations and download the MNIST dataset, the following code is being used:
```
# MNIST dataset statistics:
# mean = tensor([0.1... | I was having the same 503 error and this worked for me
```
!wget www.di.ens.fr/~lelarge/MNIST.tar.gz
!tar -zxvf MNIST.tar.gz
from torchvision.datasets import MNIST
from torchvision import transforms
train_set = MNIST('./', download=True,
transform=transforms.Compose([
transforms.ToTensor(),
]), train=True)
test_set... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch: Testing with torchvision.datasets.ImageFolder and DataLoader
I'm a newbie trying to make this PyTorch CNN work with the
Cats&Dogs dataset from kaggle
. As there are no targets for the test images, I manually classified some of the test images and put the class in the filename, to be able to test (maybe shoul... | Looking at the data from Kaggle and your code, it seems that there are problems in your data loading, both train and test set. First of all, the data should be in a different folder per label for the default PyTorch
```
ImageFolder
```
to load it correctly. In your case, since all the training data is in the same f... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Trying to load a custom dataset in Pytorch
I'm just starting out with PyTorch and am, unfortunately, a bit confused when it comes to using my own training/testing image dataset for a custom algorithm. For starters, I am making a small "hello world"-esque convolutional shirt/sock/pants classifying network. I've only lo... | I think the error comes because in the
```
transform.Compose
```
you are doing first
```
.ToTensor()
```
and, instead, you should do
```
.Scale()
```
.
```
Pytorch
```
has transformations on
tensors
and on
PIL Images
, that are
not
interchangeable.
Reading the docs it says
class torchvision.transf... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch Geometric CUDA installation issues on Google Colab
I was working on a PyTorch Geometric project using Google Colab for CUDA support. Since it's library isn't present by default, I run:
```
!pip install --upgrade torch-scatter
!pip install --upgrade torch-sparse
!pip install --upgrade torch-cluster
!pip instal... | From
their website
Try this
```
!pip install torch-geometric \
torch-sparse==latest+cu101 \
torch-scatter==latest+cu101 \
torch-cluster==latest+cu101 \
-f https://pytorch-geometric.com/whl/torch-1.4.0.html
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to get around in place operation error if index leaf variable for gradient update?
I am encountering In place operation error when I am trying to index a leaf variable to update gradients with customized Shrink function. I cannot work around it. Any help is highly appreciated!
```
import torch.nn as nn
import tor... | I just found: In order to update the variable, it needs to be
```
ht.data[idx]
```
instead of
```
ht[idx]
```
. We can use
```
.data
```
to access the tensor directly. |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Get total amount of free GPU memory and available using pytorch
I'm using google colab free Gpu's for experimentation and wanted to know how much GPU Memory available to play around, torch.cuda.memory_allocated() returns the current GPU memory occupied, but how do we determine total available memory using PyTorch. | PyTorch can provide you total, reserved and allocated info:
```
t = torch.cuda.get_device_properties(0).total_memory
r = torch.cuda.memory_reserved(0)
a = torch.cuda.memory_allocated(0)
f = r-a # free inside reserved
```
Python bindings to NVIDIA can bring you the info for the whole GPU (0 in this case means first ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: Given groups=1, weight of size [32, 3, 16, 16, 16], expected input[100, 16, 16, 16, 3] to have 3 channels, but got 16 channels instead
RuntimeError: Given groups=1, weight of size [32, 3, 16, 16, 16], expected input[100, 16, 16, 16, 3] to have 3 channels, but got 16 channels instead
This is the portion ... | ```
nn.Conv3d
```
expects the input to have size
[batch_size, channels, depth, height, width]
. The first convolution expects 3 channels, but with your input having size
[100,
16
, 16, 16, 3]
, that would be 16 channels.
Assuming that your data is given as
[batch_size, depth, height, width, channels]
, you need ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | "RuntimeError: expected scalar type Double but found Float" in Pytorch CNN training
I just begin to learn Pytorch and create my first CNN. The dataset contains 3360 RGB images and I converted them to a
```
[3360, 3, 224, 224]
```
tensor. The data and label are in the
```
dataset(torch.utils.data.Tensor... | that error is actually refering to the weights of the conv layer which are in
```
float32
```
by default when the matrix multiplication is called. Since your input is
```
double
```
(
```
float64
```
in pytorch) while the weights in conv are
```
float
```
So the solution in your case is :
```
def train_n... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | ImportError about Detectron2
I was trying to do semantic segmentation using
```
Detectron2
```
, but some tricky errors occurred when I ran my program. It seems there might be some problems in my environment.
Does anyone know how to fix it?
ImportError: cannot import name 'is_fx_tracing' from 'torch.fx._symbolic_... | This seems to be an issue with the latest commit of detectron2, you can use the previous commit of detectron2 while installing to avoid this error.
```
pip install 'git+https://github.com/facebookresearch/detectron2.git@5aeb252b194b93dc2879b4ac34bc51a31b5aee13'
```
The issue is resolved in the latest commit of detec... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | The `device` argument should be set by using `torch.device` or passing a string as an argument
My data iterator currently runs on the CPU as
```
device=0
```
argument is deprecated. But I need it to run on the GPU with the rest of the model etc.
Here is my code:
```
pad_idx = TGT.vocab.stoi["<blank>"]
model = ... | ```
pad_idx = TGT.vocab.stoi["<blank>"]
model = make_model(len(SRC.vocab), len(TGT.vocab), N=6)
model = model.to(device)
criterion = LabelSmoothing(size=len(TGT.vocab), padding_idx=pad_idx, smoothing=0.1)
criterion = criterion.to(device)
BATCH_SIZE = 12000
train_iter = MyIterator(train, batch_size=BATCH_SIZE, device = ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | RuntimeError: ‘lengths’ argument should be a 1D CPU int64 tensor, but got 1D cuda:0 Long tensor
I am trying to do a text classification using pytorch and torchtext on paperspace.
I get
```
RuntimeError: ‘lengths’ argument should be a 1D CPU int64 tensor, but got 1D cuda:0 Long tensor
```
My PyTorch version is 1.10... | I just had this problem yesterday, in my case the rnn pad sequences wants length to be on the cpu, so just put the lengths to CPU in your function call like this:
```
packed_sequences = nn.utils.rnn.pack_padded_sequence(padded_tensor, valid_frames.to('cpu'), batch_first=True, enforce_sorted=True)
```
This might not... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | how to see where exactly torch is installed pip vs conda torch installation
On my machine i can't "pip install torch" - i get infamous "single source externally managed error" - i could not fix it and used "conda install torch" from anaconda.
Still, checking version is easy -
```
torch.__version__
```
But how to s... | You can get torch module location which is imported in your script
```
import torch
print(torch.__file__)
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to apply bounds on a variable when performing optimisation in Pytorch?
I am trying to use Pytorch for non-convex optimisation, trying to maximise my objective (so minimise in SGD). I would like to bound my dependent variable x > 0, and also have the sum of my x values be less than 1000.
I think I have the penalty... | I meet the same problem with you.
I want to apply bounds on a variable in PyTorch, too.
And I solved this problem by the below Way3.
Your example is a little compliex but I am still learning English.
So I give a simpler example below.
For example, there is a trainable variable
```
v
```
, its bounds is (-1, 1)
``... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Understanding input shape to PyTorch conv1D?
This seems to be one of the common questions on here (
1
,
2
,
3
), but I am still struggling to define the right shape for input to
PyTorch conv1D
.
I have text sequences of length 512 (number of tokens per sequence) with each token being represented by a vector of len... | In pytorch your input shape of [6, 512, 768] should actually be [6, 768, 512] where the feature length is represented by the channel dimension and sequence length is the length dimension. Then you can define your conv1d with in/out channels of 768 and 100 respectively to get an output of [6, 100, 511].
Given an
```
... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | What information does Pytorch nn.functional.interpolate use?
I have a tensor
```
img
```
in PyTorch of size
```
bx2xhxw
```
and want to upsample it using
```
torch.nn.functional.interpolate
```
. But while interpolation I do not wish channel 1 to use information from channel 2. To do this should I do,
```
... | You should use (2). There is no communication in the first and second dimensions (batch and channel respectively) for all types of interpolation (1D, 2D, 3D), as they should be.
Simple example:
```
import torch
import torch.nn.functional as F
b = 2
c = 4
h = w = 8
a = torch.randn((b, c, h, w))
a_upsample = F.interp... |
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 int64 to torch LongTensor?
I am going through a course which uses a deprecated version of PyTorch which does not change
```
torch.int64
```
to
```
torch.LongTensor
```
as needed. The current section of code which is throwing the error is:
```
loss = loss_fn(Ypred, Ytrain_) # calc loss on... | As stated by
```
user8426627
```
you want to change the tensor type, not the data type. Therefore the solution was to add
```
.type(torch.LongTensor)
```
to convert it to a
```
LongTensor
```
.
Final code:
```
Ytrain_ = torch.from_numpy(Y_train.values).view(1, -1)[0].type(torch.LongTensor)
```
Test tensor... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to set and get confidence threshold from custom YOLOv5 model?
I am trying to perform inference on my custom YOLOv5 model. The
official documentation
uses the default
```
detect.py
```
script for inference.
Example:
```
python detect.py --source data/images --weights yolov5s.pt --conf 0.25
```
I have writ... | It works for me:
```
model.conf = 0.25 # confidence threshold (0-1)
model.iou = 0.45 # NMS IoU threshold (0-1)
```
More information:
https://github.com/ultralytics/yolov5/issues/36 |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch: Add validation error in training
I am using PyTorch to train a cnn model. Here is my Network architecture:
```
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as I
class Net(nn.Module):
def __init__(self):
s... | Here is an example how to split your dataset for training and validation, then switch between the two phases every epoch:
```
import numpy as np
import torch
from torchvision import datasets
from torch.autograd import Variable
from torch.utils.data.sampler import SubsetRandomSampler
# Examples:
my_dataset = datasets.... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to fix RuntimeError "Expected object of scalar type Float but got scalar type Double for argument"?
I'm trying to train a classifier via PyTorch. However, I am experiencing problems with training when I feed the model with training data.
I get this error on
```
y_pred = model(X_trainTensor)
```
:
Run... | Reference is from
this github issue
.
When the error is
```
RuntimeError: Expected object of scalar type Float but got scalar type Double for argument #4 'mat1'
```
, you would need to use the
```
.float()
```
function since it says
```
Expected object of scalar type Float
```
.
Therefore, the solution is ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to compute hessian matrix for all parameters in a network in pytorch?
Suppose vector
```
\theta
```
is all the parameters in a neural network, I wonder how to compute hessian matrix for
```
\theta
```
in pytorch.
Suppose the network is as follows:
```
class Net(Module):
def __init__(self, h, w):
... | Here is one solution, I think it's a little too complex but could be instructive.
Considering about these points:
First, about
```
torch.autograd.functional.hessian()
```
the first argument must be a function, and the second argument should be a tuple or list of tensors. That means we cannot directly pass a scala... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Tensor type mismatch when moving to GPU
I'm getting the following error when trying to move my network and tensors to GPU. I've checked that the network parameters are moved to the GPU and check each batch's tensor and move them if they're not already on the GPU. But I'm still getting this issue say that there's a mis... | This is happening because you are
re-initializing
```
self.input_layer
```
in your
```
forward()
```
function.
The call
```
self.network.cuda()
```
moves all of the model parameters into cuda. Which means any and all the layers you initialize at the creation of your
```
FeedForward
```
object will b... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | ImportError: cannot import name 'PY3' from 'torch._six'
I am testing ZED Camera with the code on
https://github.com/stereolabs/zed-pytorch
. While running the final command: python zed_object_detection.py --config-file configs/caffe2/e2e_mask_rcnn_R_50_C4_1x_caffe2.yaml --min-image-size 256
I get the... | For this question, the reason is that your 'torchvision' and 'pytorch' version, they didn't match. So, you need to upgrade your 'torchvision' and 'pytorch' version to the new version
```
pip install --upgrade torch torchvision
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | No matching distribution found for torch==1.5.0+cpu on Heroku
I am trying to deploy my Django app which uses a machine learning model. And the machine learning model requires pytorch to execute.
When i am trying to deploy it is giving me this error
```
ERROR: Could not find a version that satisfies the requirement to... | PyTorch does not distribute the CPU only versions over PyPI. They are only available through their custom registry.
If you select the CPU only version on
PyTorch - Get Started Locally
you get the following instructions:
```
pip install torch==1.5.0+cpu torchvision==0.6.0+cpu -f https://download.pytorch.org/whl/torc... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Using the full PyTorch Transformer Module
I tried asking this question on the PyTorch forums but didn't get any response so I am hoping someone here can help me. Additionally, if anyone has a good example of using the transformer module please share it as the documentation only shows using a simple linear decoder. For... | ```
loss.backward()
```
traverses through the gradient graph of the model and updates the gradients of each component in the way. You can see the graph using an auxiliary library named
PytorchViz
. Here is an example of what you can visualize using this library:
Whether you use it or not, it looks like you are usin... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Why doesn't pytorch allow inplace operations on leaf variables?
So if I run this code in Pytorch:
```
x = torch.ones(2,2, requires_grad=True)
x.add_(1)
```
I will get the error:
RuntimeError: a leaf Variable that requires grad is being used in an in-place operation.
I understand that Pytorch does not allow in... | As I understand it, any time you do a non-traditional operation on a tensor that was initialized with
```
requires_grad=True
```
, Pytorch throws an error to make sure it was intentional. For example, you normally would only update a weight tensor using
```
optimizer.step()
```
.
For another example, I ran into ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Pytorch: Convert FloatTensor into DoubleTensor
I have 2 numpy arrays, which I convert into tensors to use the TensorDataset object.
```
import torch.utils.data as data_utils
X = np.zeros((100,30))
Y = np.zeros((100,30))
train = data_utils.TensorDataset(torch.from_numpy(X).double(), torch.from_numpy(Y))
train_load... | Your
```
numpy
```
arrays are
```
64-bit floating point
```
and will be converted to
```
torch.DoubleTensor
```
standardly. Now, if you use them with your model, you'll need to make sure that your model parameters are also
```
Double
```
. Or you need to make sure, that your
```
numpy
```
arrays are ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How does one vectorize reinforcement learning environments?
I have a Python class that conforms to OpenAI's environment API, but it's written in non-vectorized form i.e. it receives one input action per step and returns one reward per step. How do I vectorize the environment? I haven't been able to find any clear expl... | You could write a custom class that iterates over an internal tuple of environments while maintaining the basic Gym API. In practice, there will be some differences, because the underlying environments don't terminate on the same timestep. Consequently, it's easier to combine the standard
```
step
```
and
```
res... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | cannot import torch audio ' No audio backend is available.'
```
import torchaudio
```
When I just try to import torch audio on Pycharm, I have this error
```
61: UserWarning: No audio backend is available.
```
warnings.warn('No audio backend is available.') | You need to install the audio file I/O backend. If Linux it's
```
Sox
```
, if Windows it's
```
SoundFile
```
To check if you have one set run
```
str(torchaudio.get_audio_backend())
```
and if 'None' is the result then install the backend.
SoundFile for Windows
```
pip install soundfile
```
Sox for Linux... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Using multiple CPU in PyTorch
I dont have access to any GPU's, but I want to speed-up the training of my model created with PyTorch, which would be using more than 1 CPU. I will use the most basic model for example here.
All I want is this code to run on multiple CPU instead of just 1 (Dataset and Network class in
A... | Torchrun
(included with Pytorch) makes this surprisingly easy.
How you want the CPUs to work together is not clear from your question, but I am assuming (because you refer to
```
DistributedDataParallel
```
that you would like to distribute the data across multiple cores which all do backward passes and broadcast ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Unpickling saved pytorch model throws AttributeError: Can't get attribute 'Net' on <module '__main__' despite adding class definition inline
I'm trying to serve a pytorch model in a flask app. This code was working when I ran this on a jupyter notebook earlier but now I'm running this within a v... | (This is a partial answer)
I don't think
```
torch.save(model,'model.pt')
```
works from the command prompt, or when a model is saved from one script running as
```
'__main__'
```
and loaded from another.
The reason is that torch must be automatically loading the module that was used to save the file, and it ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Is this matter? ERROR: pip's dependency resolver does not currently take into account all the packages that are installed
I have cuda 12 and in a fresh conda environment with python 3.11 I ran
```
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
```
However, it shows:... | The error message you are seeing is related to incomplete package dependencies. It’s important to address this because, in some cases, missing dependencies can cause issues with the installed packages and their functionality.
To address this issue, I recommend running the following command:
```
pip3 install --upgrade... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to avoid "CUDA out of memory" in PyTorch
I think it's a pretty common message for PyTorch users with low GPU memory:
```
RuntimeError: CUDA out of memory. Tried to allocate X MiB (GPU X; X GiB total capacity; X GiB already allocated; X MiB free; X cached)
```
I tried to process an image by loading eac... | Although
```
import torch
torch.cuda.empty_cache()
```
provides a good alternative for clearing the occupied cuda memory and we can also manually clear the not in use variables by using,
```
import gc
del variables
gc.collect()
```
But still after using these commands, the error might appear again because pytorch... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch : How to properly create a list of nn.Linear()
I have created a class that has nn.Module as subclass.
In my class, I have to create N number of linear transformation, where N is given as class parameters.
I therefore proceed as follow :
```
self.list_1 = []
for i in range(N):
self.list_1.ap... | You can use
```
nn.ModuleList
```
to wrap your list of linear layers as explained
here
```
self.list_1 = nn.ModuleList(self.list_1)
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Iterating over subsets from torch.utils.data.random_split
I am currently loading a folder with AI training data in it. The subfolders represent the label names with the corresponding images inside. This works well by using pyTorch's ImageFolder loader.
```
def load_dataset():
data_path = 'C:/example_folder/'
... | You need to apply
```
random_split
```
to a
```
Dataset
```
not a
```
DataLoader
```
. The dataset used to define the
```
DataLoader
```
is available in the
```
DataLoader.dataset
```
member.
For example you could do
```
train_dataset, test_dataset = torch.utils.data.random_split(full_dataset.datas... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | UserWarning: Using a target size (torch.Size([1])) that is different to the input size (torch.Size([1, 1]))
I have this code:
```
actual_loes_score_g = actual_loes_score_t.to(self.device, non_blocking=True)
predicted_loes_score_g = self.model(input_g)
loss_func = nn.L1Loss()
loss_g = loss_func(
predicted_loes_s... | ```
predicted_loes_score_g = tensor([[-24.9374]], grad_fn=<AddmmBackward0>)
```
which is size [1,1]
```
actual_loes_score_g = tensor([20.], dtype=torch.float64)
```
which is size [1]
You need to either remove a dimension from your prediction or add a dimension to your target. I would recommend the latter because ... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | SSLCertVerificationError when downloading pytorch datasets via torchvision
I am having trouble downloading the CIFAR-10 dataset from pytorch. Mostly it seems like some SSL error which I don't really know how to interpret. I have also tried changing the root to various other folders but none of them works. I was wonder... | Turn off the ssl verification.
```
import ssl
ssl._create_default_https_context = ssl._create_unverified_context
``` |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Huggingface: How do I find the max length of a model?
Given a transformer model on huggingface, how do I find the maximum input sequence length?
For example, here I want to truncate to the max_length of the model:
```
tokenizer(examples["text"], padding="max_length", truncation=True)
```
How do I find the value o... | Perhaps late, but if you haven't found a solution, I think you can use the tokenizer of that model.
For instance:
```
>>> MODEL = "google/flan-t5-xl"
>>> tokenizer = AutoTokenizer.from_pretrained(MODEL)
>>> tokenizer.model_max_length
512
>>> MODEL = "facebook/bart-base"
>>> tokenizer = AutoTokenizer.from_pretrained(M... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to get the size of a Hugging Face pretrained model?
I keep getting a
```
CUDA out of memory
```
error when trying to fine-tune a Hugging Face pretrained XML Roberta model. So, the first thing I want to find out is the size of the pretrained model.
```
model = XLMRobertaForCausalLM.from_pretrained('xlm-roberta... | Size is a little ambiguous here so here's both the answers for
1. Size (No. of parameters) of a model.
Use the
```
.num_parameters()
```
function, e.g.
```
from transformers import MarianMTModel
model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-en-de")
model.num_parameters()
```
[out]:
```
74410496... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | AttributeError: 'numpy.ndarray' object has no attribute 'unsqueeze'
I'm running a training code using
```
pyhtorch
```
and
```
numpy
```
.
This is the
```
plot_example
```
function:
```
def plot_example(low_res_folder, gen):
files=os.listdir(low_res_folder)
gen.eval()
for ... | Make sure image is a tensor in the shape of [batch size, channels, height, width] before entering any Pytorch layers.
Here you have
```
image=np.asarray(image)
```
I would remove this numpy conversion and keep it a torch.tensor.
Or if you really want it to be a numpy array, then right before it enters your generato... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | 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... | EDIT:
As of Pytorch version 1.0,
```
torch.inverse
```
now supports batches of tensors. See
here
. So you can simply use the built-in function
```
torch.inverse
```
OLD ANSWER
There are plans to implement batched inverse soon. For discussion, see for example
issue 7500
or
issue 9102
. However, as of the ti... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | PyTorch - Getting the 'TypeError: pic should be PIL Image or ndarray. Got <class 'numpy.ndarray'>' error
I am getting the error
```
TypeError: pic should be PIL Image or ndarray. Got <class 'numpy.ndarray'>
```
when I try to load
a non-image dataset
through the
```
DataLoader
```
. The v... | This happens because of the transformation you use:
```
self.transform = transforms.Compose([transforms.ToTensor()])
```
As you can see in the
documentation
,
```
torchvision.transforms.ToTensor
```
converts a PIL Image or
```
numpy.ndarray
```
to tensor. So if you want to use this transformation, your data... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | Do you need to put EOS and BOS tokens in autoencoder transformers?
I'm starting to wrap my head around the transformer architecture, but there are some things that I am not yet able to grasp.
In decoder-free transformers, such as BERT, the tokenizer includes always the tokens CLS and SEP before and after a sentence. ... | First, a little about BERT -
BERT word embeddings allow for multiple vector representations for the same word, based on the context in which the word was used. In this sense, BERT embeddings are
context-dependent
. BERT explicitly takes the index position of each word in the sentence while calculating its embedding. T... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | How to replace infs to avoid nan gradients in PyTorch
I need to compute
```
log(1 + exp(x))
```
and then use automatic differentiation on it. But for too large
```
x
```
, it outputs
```
inf
```
because of the exponentiation:
```
>>> x = torch.tensor([0., 1., 100.], requires_grad=True)
>>> x.exp().log1p()
... | A workaround I've found is to manually implement a
```
Log1PlusExp
```
function with its backward counterpart. Yet it does not explain the bad behavior of
```
torch.where
```
in the question.
```
>>> class Log1PlusExp(torch.autograd.Function):
... """Implementation of x ↦ log(1 + exp(x))."""
... @stati... |
You are a PyTorch debugging assistant. Given an error message or problem description, explain the root cause and provide a fix. | overlaying the ground truth mask on an image
In my project, I extracted frames from a video and in another folder I have ground truth for each frame.
I want to map the ground truth image of each frame of a video (in my case, it is saliency prediction ground truth) on its related frame image. As an example I have the f... | I need to do similar things pretty often. In my favorite StackOverflow fashion, here is a script that you can copy and paste. I hope the code itself is self-explanatory. There are a few things that you can tune and try (e.g., color maps, overlay styles). It uses
```
multiprocessing.Pool
```
for faster batch-process... |
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