compression | Data compression in TensorFlow | Machine Learning library
kandi X-RAY | compression Summary
kandi X-RAY | compression Summary
TensorFlow Compression (TFC) contains data compression tools for TensorFlow. You can use this library to build your own ML models with end-to-end optimized data compression built in. It's useful to find storage-efficient representations of your data (images, features, examples, etc.) while only sacrificing a tiny fraction of model performance. It can compress any floating point tensor to a much smaller sequence of bits. Specifically, the entropy model classes in this library simplify the process of designing rate–distortion optimized codes. During training, they act like likelihood models. Once training is completed, they encode floating point tensors into optimal bit sequences by automating the design of probability tables and calling a range coder implementation behind the scenes. Range coding (a.k.a. arithmetic coding) is exposed to TensorFlow models with a set of flexible TF ops written in C++. These include an optional "overflow" functionality that embeds an Elias gamma code into the range encoded bit sequence, making it possible to encode the entire set of signed integers rather than just a finite range. The main novelty of the learned approach over traditional transform coding is the stochastic minimization of the rate-distortion Lagrangian, and using nonlinear transforms implemented by neural networks. For an introduction to this, consider our paper on nonlinear transform coding, or watch @jonycgn's talk on learned image compression.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
- Parse command line arguments
- Parse num_steps
- Call the convolutional function
- Computes the correlation between inputs
- Computes the correlation matrix
- Pad the given iterable with fill
- Run the neural network
- Estimate Entropy
- Quantize inputs
- Evaluate a trained model
- Plot Jacobian
- Plot the synthesis of the model
- Compress an image
- Plot quantization
- Train a model
- Builds a FactorizedPriorInfo
- Build the kernel
- Compress bottleneck
- Estimate the upper tail of a distribution
- Lower the likelihood of a distribution
- Create tensors
- Decompress the given string
- Decompresses given strings
- Plot the prior
- Decompress a sequence of strings
- Train a training step
compression Key Features
compression Examples and Code Snippets
Lines of Code : 29
License : No License
Copyimport WebSocket, { WebSocketServer } from 'ws';
const wss = new WebSocketServer({
port: 8080,
perMessageDeflate: {
zlibDeflateOptions: {
// See zlib defaults.
chunkSize: 1024,
memLevel: 7,
level: 3
},
zlibInf var compression = require('compression')
var express = require('express')
var app = express()
app.use(compression({ filter: shouldCompress }))
function shouldCompress (req, res) {
if (req.headers['x-no-compression']) {
// don't compress respo public void createCompactedTopicWithCompression(String topicName) throws Exception {
Properties props = new Properties();
props.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
try (Admin admin = Admin.creat private Integer pathCompressionFind(Integer node) {
DisjointSetInfo setInfo = nodes.get(node);
Integer parent = setInfo.getParentNode();
if (parent.equals(node)) {
return node;
} else {
Integer def _validate_compression(compression):
valid_compressions = [COMPRESSION_AUTO, COMPRESSION_NONE]
if compression not in valid_compressions:
raise ValueError(f"Invalid `compression` argument: {compression}. "
f"Must be one Community Discussions
Trending Discussions on compression
QUESTION
I am using a company-hosted (Bitbucket) git repository that is accessible via HTTPS. Accessing it (e.g. git fetch) worked using macOS 11 (Big Sur), but broke after an update to macOS 12 Monterey.
*
After the update of macOS to 12 Monterey my previous git setup broke. Now I am getting the following error message:
...ANSWER
Answered 2021-Nov-02 at 07:12Unfortunately I can't provide you with a fix, but I've found a workaround for that exact same problem (company-hosted bitbucket resulting in exact same error).
I also don't know exactly why the problem occurs, but my best guess would be that the libressl library shipped with Monterey has some sort of problem with specific (?TLSv1.3) certs. This guess is because the brew-installed openssl v1.1 and v3 don't throw that error when executed with /opt/homebrew/opt/openssl/bin/openssl s_client -connect ...:443
To get around that error, I've built git from source built against different openssl and curl implementations:
- install
autoconf,opensslandcurlwith brew (I think you can select the openssl lib you like, i.e. v1.1 or v3, I chose v3) - clone git version you like, i.e.
git clone --branch v2.33.1 https://github.com/git/git.git cd gitmake configure(that is why autoconf is needed)- execute
LDFLAGS="-L/opt/homebrew/opt/openssl@3/lib -L/opt/homebrew/opt/curl/lib" CPPFLAGS="-I/opt/homebrew/opt/openssl@3/include -I/opt/homebrew/opt/curl/include" ./configure --prefix=$HOME/git(here LDFLAGS and CPPFLAGS include the libs git will be built against, the right flags are emitted by brew on install success of curl and openssl; --prefix is the install directory of git, defaults to/usr/localbut can be changed) make install- ensure to add the install directory's subfolder
/binto the front of your$PATHto "override" the default git shipped by Monterey - restart terminal
- check that
git versionshows the new version
This should help for now, but as I already said, this is only a workaround, hopefully Apple fixes their libressl fork ASAP.
QUESTION
git gc
error: Could not read 0000000000000000000000000000000000000000
Enumerating objects: 147323, done.
Counting objects: 100% (147323/147323), done.
Delta compression using up to 4 threads
Compressing objects: 100% (36046/36046), done.
Writing objects: 100% (147323/147323), done.
Total 147323 (delta 91195), reused 147323 (delta 91195), pack-reused 0
ANSWER
Answered 2022-Mar-28 at 14:18This error is harmless in the sense that it does not indicate a broken repository. It is a bug that was introduced in Git 2.35 and that should be fixed in later releases.
The worst that can happen is that git gc does not prune all objects that are referenced from reflogs.
The error is triggered by an invocation of git reflog expire --all that git gc does behind the scenes.
The trigger are empty reflog files in the .git/logs directory structure that were left behind after a branch was deleted. As a workaround you can remove these empty files. This command lets you find them and check their size:
QUESTION
I need help debugging Webpack's Compression Plugin.
SUMMARY OF PROBLEM
- Goal is to enable asset compression and reduce my app's bundle size. Using the Brotli algorithm as the default, and gzip as a fallback for unsupported browsers.
- I expected a content-encoding field within an asset's Response Headers. Instead, they're loaded without the field. I used the Chrome dev tools' network tab to confirm this. For context, see the following snippet:
- No errors show in my browser or IDE when running locally.
WHAT I TRIED
- Using different implementations for the compression plugin. See below list of approaches:
- (With Webpack Chain API)
ANSWER
Answered 2021-Sep-30 at 14:59It's not clear which server is serving up these assets. If it's Express, looking at the screenshot with the header X-Powered-By, https://github.com/expressjs/compression/issues/71 shows that Brotli support hasn't been added to Express yet.
There might be a way to just specify the header for content-encoding manually though.
QUESTION
Is the Shannon-Fano coding as described in Fano's paper The Transmission of Information (1952) really ambiguous?
In Detail:3 papers
Claude E. Shannon published his famous paper A Mathematical Theory of Communication in July 1948. In this paper he invented the term bit as we know it today and he also defined what we call Shannon entropy today. And he also proposed an entropy based data compression algorithm in this paper. But Shannon's algorithm was so weak, that under certain circumstances the "compressed" messages could be even longer than in fix length coding. A few month later (March 1949) Robert M. Fano published an improved version of Shannons algorithm in the paper The Transmission of Information. 3 years after Fano (in September 1952) his student David A. Huffman published an even better version in his paper A Method for the Construction of Minimum-Redundancy Codes. Hoffman Coding is more efficient than its two predecessors and it is still used today. But my question is about the algorithm published by Fano which usually is called Shannon-Fano-Coding.
The algorithm
This description is based on the description from Wikipedia. Sorry, I did not fully read Fano's paper. I only browsed through it. It is 37 pages long and I really tried hard to find a passage where he talks about the topic of my question, but I could not find it. So, here is how Shannon-Fano encoding works:
- Count how often each character appears in the message.
- Sort all characters by frequency, characters with highest frequency on top of the list
- Divide the list into two parts, such that the sums of frequencies in both parts are as equal as possible. Add the bit
0to one part and the bit1to the other part. - Repeat step 3 on each part that contains 2 or more characters until all parts consist of only 1 character.
- Concatenate all bits from all rounds. This is the Shannon-Fano-code of that character.
An example
Let's execute this on a really tiny example (I think it's the smallest message where the problem appears). Here is the message to encode:
ANSWER
Answered 2022-Mar-08 at 19:00To directly answer your question, without further elaboration about how to break ties, two different implementations of Shannon-Fano could produce different codes of different lengths for the same inputs.
As @MattTimmermans noted in the comments, Shannon-Fano does not always produce optimal prefix-free codings the way that, say, Huffman coding does. It might therefore be helpful to think of it less as an algorithm and more of a heuristic - something that likely will produce a good code but isn't guaranteed to give an optimal solution. Many heuristics suffer from similar issues, where minor tweaks in the input or how ties are broken could result in different results. A good example of this is the greedy coloring algorithm for finding vertex colorings of graphs. The linked Wikipedia article includes an example in which changing the order in which nodes are visited by the same basic algorithm yields wildly different results.
Even algorithms that produce optimal results, however, can sometimes produce different optimal results based on tiebreaks. Take Huffman coding, for example, which works by repeatedly finding the two lowest-weight trees assembled so far and merging them together. In the event that there are three or more trees at some intermediary step that are all tied for the same weight, different implementations of Huffman coding could produce different prefix-free codes based on which two they join together. The resulting trees would all be equally "good," though, in that they'd all produce outputs of the same length. (That's largely because, unlike Shannon-Fano, Huffman coding is guaranteed to produce an optimal encoding.)
That being said, it's easy to adjust Shannon-Fano so that it always produces a consistent result. For example, you could say "in the event of a tie, choose the partition that puts fewer items into the top group," at which point you would always consistently produce the same coding. It wouldn't necessarily be an optimal encoding, but, then again, since Shannon-Fano was never guaranteed to do so, this is probably not a major concern.
If, on the other hand, you're interested in the question of "when Shannon-Fano has to break a tie, how do I decide how to break the tie to produce the optimal solution?," then I'm not sure of a way to do this other than recursively trying both options and seeing which one is better, which in the worst case leads to exponentially-slow runtimes. But perhaps someone else here can find a way to do that>
QUESTION
Why does this .c file #include itself?
vsimple.c
...ANSWER
Answered 2022-Feb-18 at 07:48The file includes itself so the same source code can be used to generate 4 different sets of functions for specific values of the macro USIZE.
The #include directives are actually enclosed in an #ifndef, which limits the recursion to a single level:
QUESTION
I want to select elements from an array based on some test. Currently, I am trying to do that with a compression, and I would like to write it as a tacit function. (I'm very new to APL, so feel free to suggest other options.) Below is a minimal (not-)working example.
The third line below shows that I can use the testing function f on vec and then do the compression, and the fifth line shows I can apply the identity function to vec (as expected). So based on my understanding of the train documentation, I should be able to make a fork from f and ⊢ with / as the center prong. Below shows that this does not work, and I presume it is because Dyalog is interpreting the sixth and eighth lines as doing an f-reduce. Is there a way to indicate that I want a compression train and not a reduce? (and/or is there a better way to do this altogether?)
ANSWER
Answered 2022-Feb-18 at 07:42Yes, by making / an operand, it is forced to behave as a function. As per APL Wiki, applying ⊢ atop the result of / solves the problem:
QUESTION
I have to decompress some gzip text in .NET 6 app, however, on a string that is 20,627 characters long, it only decompresses about 1/3 of it. The code I am using code works for this string in .NET 5 or .NETCore 3.1 As well as smaller compressed strings.
...ANSWER
Answered 2022-Feb-01 at 10:43Just confirmed that the article linked in the comments below the question contains a valid clue on the issue.
Corrected code would be:
QUESTION
I have upgraded my angular to angular 13. when I run to build SSR it gives me following error.
...ANSWER
Answered 2022-Jan-22 at 05:29I just solve this issue by correcting the RxJS version to 7.4.0. I hope this can solve others issue as well.
QUESTION
was looking at this V8 design doc where it has a section for Constant Pool Entries
it says
Constant pools are used to store heap objects and small integers that are referenced as constants in generated bytecode. and
... Small integers and the strong referenced oddball type’s have bytecodes to load them directly and do not go into the constant pool.
So I am confused: are small integers pooled or not?
My understanding is that it is not worth it pooling small integers if sizeof(int) < sizeof(int *) - because it is cheaper to just copy the actual integer instead of copying the pointer that points to the integer in the constant pool. Also variables that hold integers can be optimised to be stored directly in CPU registers and skip being allocated in memory first.
Also, are they located on the V8 heap or the stack? My understanding had always been that smis are just be the immediate values allocated on the stack instead of being a pointer + an integer allocated on heap. Also if you take a heap snapshot using chrome devtool you cannot find smis in the heap snapshot - only heap number such as big integers or double like 3.14 are on the heap until I saw this article https://v8.dev/blog/pointer-compression#value-tagging-in-v8
JavaScript values in V8 are represented as objects and allocated on the V8 heap, no matter if they are objects, arrays, numbers or strings. This allows us to represent any value as a pointer to an object.
Now I am just baffled - are smis also allocated on the heap?
...ANSWER
Answered 2022-Jan-17 at 12:37V8 developer here.
are small integers pooled or not?
They are not (at least not right now). That said, this is a small implementation detail and could be done either way: it would totally be possible to use the constant pool for Smis. I suppose the decision to build special machinery for Smis (instead of reusing the general-purpose constant pool) was made because things turned out to be more efficient that way.
it is not worth it pooling small integers if
sizeof(int) < sizeof(int *)
The details are different (a Smi is not an int, and constant pool slots are referenced by index rather than C++ pointer), but this reasoning does go in the right direction: avoiding indirections can save time and memory.
are smis also allocated on the heap?
Yes, everything is allocated on the heap. The stack is only useful for temporary (and sufficiently small) things; that's largely unrelated to the type of thing.
The "trick" of Smis is that they're not stored as separate objects: when you have an object that refers to a Smi, such as let foo = {smi: 42}, then the value 42 can be smi-encoded and stored directly inside the "foo" object (whereas if the value was 42.5, then the object would store a pointer to a separate "HeapNumber"). But since the object is on the heap, so is the Smi.
@DanielCruz
What I understand [...] is that constant small integers are pooled. Variable small integers are not.
Nope. Any literal that occurs in source code is "constant". Whether you use let or const for your variables has nothing to do with this.
QUESTION
I have a Python 3 application running on CentOS Linux 7.7 executing SSH commands against remote hosts. It works properly but today I encountered an odd error executing a command against a "new" remote server (server based on RHEL 6.10):
encountered RSA key, expected OPENSSH key
Executing the same command from the system shell (using the same private key of course) works perfectly fine.
On the remote server I discovered in /var/log/secure that when SSH connection and commands are issued from the source server with Python (using Paramiko) sshd complains about unsupported public key algorithm:
userauth_pubkey: unsupported public key algorithm: rsa-sha2-512
Note that target servers with higher RHEL/CentOS like 7.x don't encounter the issue.
It seems like Paramiko picks/offers the wrong algorithm when negotiating with the remote server when on the contrary SSH shell performs the negotiation properly in the context of this "old" target server. How to get the Python program to work as expected?
Python code
...ANSWER
Answered 2022-Jan-13 at 14:49Imo, it's a bug in Paramiko. It does not handle correctly absence of server-sig-algs extension on the server side.
Try disabling rsa-sha2-* on Paramiko side altogether:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install compression
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
