entropy | Strange keyboard with a left hand numpad | Keyboard library
kandi X-RAY | entropy Summary
kandi X-RAY | entropy Summary
Strange keyboard with a left hand numpad
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of entropy
entropy Key Features
entropy Examples and Code Snippets
Community Discussions
Trending Discussions on entropy
QUESTION
I'm training a transformer model for text generation.
let's assume:
...ANSWER
Answered 2021-Jun-10 at 19:24Use torch.BCELoss()
instead (Binary cross entropy). This expects input and target to be the same size but they can be any size, and should fall within the range [0,1]. It performs cross-entropy loss element-wise.
QUESTION
We are using GetAwaiter().GetResult()
because PowerShell's Cmdlet.ProcessRecord()
does not support async/await.
ANSWER
Answered 2021-Jun-10 at 00:18According to the documentation of the ValueTask
struct:
The following operations should never be performed on a
ValueTask
instance:• Awaiting the instance multiple times.
• CallingAsTask
multiple times.
• Using.Result
or.GetAwaiter().GetResult()
when the operation hasn't yet completed, or using them multiple times.
• Using more than one of these techniques to consume the instance.If you do any of the above, the results are undefined.
What you can do is to convert the ValueTask
to a Task
, by using the AsTask
method:
QUESTION
ITU T.81 states the following:
B.1.1.2 Markers Markers serve to identify the various structural parts of the compressed data formats. Most markers start marker segments containing a related group of parameters; some markers stand alone. All markers are assigned two-byte codes: an X’FF’ byte followed by a byte which is not equal to 0 or X’FF’ (see Table B.1). Any marker may optionally be preceded by any number of fill bytes, which are bytes assigned code X’FF’. NOTE – Because of this special code-assignment structure, markers make it possible for a decoder to parse the compressed data and locate its various parts without having to decode other segments of image data. "
B.1.1.5 Entropy-coded data segments An entropy-coded data segment contains the output of an entropy-coding procedure. It consists of an integer number of bytes, whether the entropy-coding procedure used is Huffman or arithmetic.
NOTES
(1) Making entropy-coded segments an integer number of bytes is performed as follows: for Huffman coding, 1-bits are used, if necessary, to pad the end of the compressed data to complete the final byte of a segment. For arithmetic coding, byte alignment is performed in the procedure which terminates the entropy-coded segment (see D.1.8).
(2) In order to ensure that a marker does not occur within an entropy-coded segment, any X’FF’ byte generated by either a Huffman or arithmetic encoder, or an X’FF’ byte that was generated by the padding of 1-bits described in NOTE 1 above, is followed by a “stuffed” zero byte (see D.1.6 and F.1.2.3).
And in many other places where well known Stuff_0() function is also named.
Not sure where standard ITU T.87 stands in regard to the encoding escape sequence 0xFF 0x00 specified by standard ITU T.81:
- Standard ITU T.87 it self that do not specify this but expects it. Where Standard test samples are incorrectly formed, clearly do not have encoding escape sequence 0xFF 0x00 in encoded streams. For example 0xFF 0x7F, 0xFF 0x2F, and other sequences can be found in encoded streams of .jsl test samples : namelly "T8C0E3.JLS". And no one saw it all these years;
- Or if Standard ITU T.87 actually overrides the ITU T.81 regarding this rule for encoded streams and doesn't allow encoding of escape sequence;
In decoder we could make logic to detect decoder errors when 0xFF and !0x00 is to actually use that byte and not skip it if component is not fully decoded. But what if jls file do not have escape sequence and we encounter 0xFF 0x00 sequence should we skip 0x00 byte or not?
Would like some clarification on subject of standard ITU T.87 JPEG-LS encoding, and what is the correct procedure. Should we, or shouldn't we, encode escape sequnce 0xFF 0x00 in encoded streams?
...ANSWER
Answered 2021-Jun-09 at 23:32The answer : ITU T.87 - ANNEX A - point A1 - pass 3
Marker segments are inserted in the data stream as specified in Annex D. In order to provide for easy detection of marker segments, a single byte with the value X'FF' in a coded image data segment shall be followed with the insertion of a single bit '0'. This inserted bit shall occupy the most significant bit of the next byte. If the X'FF' byte is followed by a single bit '1', then the decoder shall treat the byte which follows as the second byte of a marker, and process it in accordance with Annex C. If a '0' bit was inserted by the encoder, the decoder shall discard the inserted bit, which does not form part of the data stream to be decoded.
NOTE 2 – This marker segment detection procedure differs from the one specified in CCITT Rec. T.81 | ISO/IEC 10918-1.
JPEG-LS T.87 overrides T.81 JPEG Standard for encoded data stream to have byte 0xFF followed by byte with value between 0x00 and 0x7F (inclusive).
QUESTION
my data
how do I increase the accuracy of the model, if some of my models when run produce results like the one below `
...ANSWER
Answered 2021-Jun-09 at 05:44There are several ways to achieve this:
Look at the data. Are they in the best shape for the algorithm? Regarding NaN, Covariance and so on? Are they normalized, are the categorical ones translated well? This is a question too far-reaching for a forum.
Look at the problem and the different algorithm suitable for this problem. Maybe
- Logistic Regression
- SVN
- XGBoost
- ....
- Try hyper parameter tuning with RandomisedsearvCV or GridSearchCV
This is quite high-level.
QUESTION
I run my Android app (based on Java), and it works. Next, I add to my app code:
FirebaseFirestore fdb = FirebaseFirestore.getInstance();
This code I got from the official Android site https://firebase.google.com/docs/firestore/quickstart
App runs, but next the running device shows the message "app has stopped".
I use a device simulator available in Android Studio.
It is my first Android app, and I can't understand what is going.
----Trace------ 2021-06-08 20:57:30.186 7155-7155/? D/AndroidRuntime: >>>>>> START com.android.internal.os.RuntimeInit uid 2000 <<<<<< 2021-06-08 20:57:30.188 7155-7155/? D/AndroidRuntime: CheckJNI is ON 2021-06-08 20:57:30.210 7155-7155/? W/art: Unexpected CPU variant for X86 using defaults: x86 2021-06-08 20:57:30.214 7155-7155/? D/ICU: No timezone override file found: /data/misc/zoneinfo/current/icu/icu_tzdata.dat 2021-06-08 20:57:30.229 7155-7155/? E/memtrack: Couldn't load memtrack module (No such file or directory) 2021-06-08 20:57:30.229 7155-7155/? E/android.os.Debug: failed to load memtrack module: -2 2021-06-08 20:57:30.230 7155-7155/? I/Radio-JNI: register_android_hardware_Radio DONE 2021-06-08 20:57:30.239 7155-7155/? D/AndroidRuntime: Calling main entry com.android.commands.am.Am
...ANSWER
Answered 2021-Jun-09 at 03:39At the end of your log, just before the initial crash. there is a warning:
Default FirebaseApp failed to initialize because no default options were found. This usually means that com.google.gms:google-services was not applied to your gradle project.
simply adding com.google.gms:google-services
should fix any issues you have, if you have issues, ensure your Gradle cache is cleared or run without the build cache
--no-build-cache
QUESTION
Can I use AdaBoost with random forest as a base classifier? I searched on the internet and I didn't find anyone who does it.
Like in the following code; I try to run it but it takes a lot of time:
...ANSWER
Answered 2021-Apr-07 at 11:30No wonder you have not actually seen anyone doing it - it is an absurd and bad idea.
You are trying to build an ensemble (Adaboost) which in itself consists of ensemble base classifiers (RFs) - essentially an "ensemble-squared"; so, no wonder about the high computation time.
But even if it was practical, there are good theoretical reasons not to do it; quoting from my own answer in Execution time of AdaBoost with SVM base classifier:
Adaboost (and similar ensemble methods) were conceived using decision trees as base classifiers (more specifically, decision stumps, i.e. DTs with a depth of only 1); there is good reason why still today, if you don't specify explicitly the
base_classifier
argument, it assumes a value ofDecisionTreeClassifier(max_depth=1)
. DTs are suitable for such ensembling because they are essentially unstable classifiers, which is not the case with SVMs, hence the latter are not expected to offer much when used as base classifiers.On top of this, SVMs are computationally much more expensive than decision trees (let alone decision stumps), which is the reason for the long processing times you have observed.
The argument holds for RFs, too - they are not unstable classifiers, hence there is not any reason to actually expect performance improvements when using them as base classifiers for boosting algorithms, like Adaboost.
QUESTION
I would like to know how to put two or more Elements sit next to each other with overflow. I can do it if I change the width of the slide-screen for example 1500px or bigger. I need to hide the second image to make a slide with javascript later. Please teach me how to solve this problem or teach me another way to do it if there is...
HTML
...ANSWER
Answered 2021-Jun-06 at 02:38you can use the max-width
css property, which will hide the image once it reaches a certain width.
QUESTION
I have a GAN that returns a predicted torch.tensor
. To guide this network, I have a loss function which is a summation of binary cross entropy loss (BCELoss
) and Wasserstein distance. However, in order to calculate Wasserstein distance, I am using scipy.stats.wasserstein_distance
function from SciPy
library. As you might know, this function requires two NumPy
arrays as input. So, to use this function, I am converting my predicted tensor and ground-truth tensor to NumPy
arrays as follows
ANSWER
Answered 2021-Jun-03 at 18:49Adding an object that is not a tensor that requires_grad to your loss is essentially adding a constant. The derivative of a constant is zero, so this added term is not doing anything to your network's weights.
tl;dr: You need to rewrite the loss computation in pytorch (or just find an existing implementation, there's numerous on the internets).
QUESTION
I'm making a gallery and I want each photo to go fullscreen when you click on it like this:
Currently, I have a click handler on each image that adds a class zoom
to the clicked image. The CSS selectors I wrote only blow the image up and don't have it centered on the full page like in the example. Here is my code:
ANSWER
Answered 2021-Jun-03 at 05:38I suggest look at intensejs library: https://github.com/tholman/intense-images
It's fast and easy implementation that will fit your needs.
QUESTION
I am building a simple gallery using Javascript and CSS but can't seem to get the image to fit full frame. Here is what it looks like right now:
...ANSWER
Answered 2021-Jun-02 at 20:26Add this code to your css
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install entropy
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page