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kandi X-RAY | Lin Summary
Add the detectors module dependencies to your project and the dsl module as part of the lint classpath:.
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QUESTION
I want to train the model to sum the three inputs. So it is as simple as possible.
Firstly the weights are initialized randomly. It produces bad error estimate (approx. 0.5)
Then I initialize the weights with zeros. There are two options:
- the shape of the weights tensor is [1, 3]
- the shape of the weights tensor is [3]
When I choose the 1st option the model still works bad and can't learn this simple formula.
When I choose the 2nd option it works perfect with the error of 10e-12.
Why the result depends on the shape of the weights? Why do I need to initialize the model with zeros to solve this simple problem?
...ANSWER
Answered 2022-Apr-02 at 18:36First option doesn't learning because it fails with broadcasting: while out.shape == (1024, 1)
corresponding targets y
has shape of (1024, )
. MSELoss, as expected, computes mean of tensor (out - y)^2
, which in this case has shape (1024, 1024)
, clearly wrong objective for this task. At the same time, after applying 2-nd option tensor (out - y)^2
has size (1024, )
and mean of it corresponds to actual mse. Default approach, without explicit changing weights shape (through option 1 and 2), would work if set target shape to (1024, 1)
for example by y = y.unsqueeze(-1)
after definition of y
.
QUESTION
This is the following code I have for plotting a series of random points in gnuplot. I have no errors in gnuplot-iostream header.
...ANSWER
Answered 2022-Mar-16 at 17:15For debugging I used 5 points instead of 1000, so it was easier to see the first error:
QUESTION
I have a df
of this format, my goal is to find users who participate in more than one tournament and ultimately set their 'val' value to the one they first appear with. Initially, I was thinking I need to groupby
'tour' but then it needs some intersection but I'm not sure how to proceed. Alternatively, I can do pd.crosstab(df.user, df.tour)
but I'm not sure how to proceed either.
ANSWER
Answered 2022-Feb-26 at 18:37You can groupby
on 'user' and filter out groups with only 1 element, and then select the first one, like so:
QUESTION
I am trying to use the rtcclient Python package to authenticate and retrieve work items from my IBM RTC board. Specifically my goal is to run this command without errors:
...ANSWER
Answered 2022-Feb-23 at 07:28Check first if this was working with 0.6.0 (depending on your RTC version 6.x?; 7.x).
dixudx/rtcclient
issue 136 mentions:
v0.7.0 has introduced a change on authentication, refer to #133 for details (and issue 112), which may be not compatible with older Rational Team Concert. From your issue, it seems to be true. Sorry for this.
My suggestion is just sticking with older rtcclient version, such as
pip install rtcclient==0.6.0
.
QUESTION
I trained a neural network on MNIST using PyTorch:
...ANSWER
Answered 2022-Feb-15 at 09:52You do not need to change anything about your conv layer. Each layer computes gradients both w.r.t. parameters (for updates) and w.r.t. inputs (for "downstream" gradients by the chain rule). Therefore, all you need is to set your input image's x
gradient property to true:
QUESTION
I have installed a vanilla django-cms on a new server. I installed all requirements. It all went fine, up untill the point where I wanted to migrate to the database (Postgres).
So this is what I did :
- Tried reinstalling and installing it all again. Didn't change it.
- Used google to try and find people with the same error.
- Try editing the signals file on which the error(shown below) fires, but that meant rewriting it all, which still made it unresponsive.
Traceback:
...ANSWER
Answered 2021-Dec-15 at 16:29I found that answer to this problem. If you look at the documentation of Django. It has been Django from 2.0 to 3.0.
Do formerly it was :
QUESTION
When Trying to plot the linear regression of the data the output returns a horizontal line with a warning that the fit is rank-deficient. Can someone please explain how to display a proper linear regression?
Sample Data
...ANSWER
Answered 2022-Jan-27 at 20:42This isn't a ggplot
problem, but an lm
problem:
QUESTION
I'm currently stuck on a saving issue. I want to create levels for a game and I'd like to build and modify them in a pygame program, then save them in the form of a string in a .txt file. For now, I managed to open an existing file named "level_n.txt", delete the old level I want to overwrite, and write the new level matrix in the text file. At this point, everything works perfectly. If I modify the text file, close it, re-open it in the same program run, and print the level, the changes were saved.
Here is my problem : when I close my whole program and re-open it, the level isn't changed, and when I open the text file of the level manually, the changes aren't here either.
So from my perspective, it looks like python creates a copy of the file in the RAM, overwrites it, uses it, but when it closes, the text file doesn't save.
I've included the part where I write the text, and a level example just in case. (I've tried to write the text using w, w+, r+, a+, none of these solve my issue)
...ANSWER
Answered 2022-Jan-18 at 23:21Use the full path to the file instead of just the name of the file and it should work fine For example:
QUESTION
I want to make a program that detects duplicate words as in the following example:
"At least one value must be entered
entered in order to compute the average"
We can see that "entered" is repeated and I want to find a way to detect this type of cases. \
ANSWER
Answered 2022-Jan-14 at 21:49text = 'i like donkey donkey'
words = text.split(' ')
for i in range(0, len(words)):
count = 1;
for j in range(i+1, len(words)):
if(words[i] == (words[j])):
count = count + 1;
words[j] = '0';
if(count > 1 and words[i] != '0'):
print(words[i]);
# output -> donkey
QUESTION
I have these two files that run perfectly fine within GF shell
My GF codeTest.gf
...ANSWER
Answered 2022-Jan-05 at 07:46I will first give you three alternatives how to make the grammar work. Then I will explain the rest of the mysteries: why cc
works with your initial approach, but parsing/linearisation doesn't, and also how to actually use cc
from Python (just not with the PGF library).
In your example, you are opening DictEng
, so I assume that you would like your application to have a large lexicon.
If you want to be able to parse with a large lexicon, it needs to be a part of the abstract syntax of your grammar. The first mistake is the fact that you're opening DictEng as a resource, instead of extending. (See tutorial to refresh your memory.)
So if you want your abstract syntax to contain a lexicon entry called dog_N
, which you can give as an argument to the function MySentence
, you will need to modify your grammar as follows.
Abstract:
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