nmt | TensorFlow Neural Machine Translation Tutorial | Translation library

 by   tensorflow Python Version: Current License: Apache-2.0

kandi X-RAY | nmt Summary

kandi X-RAY | nmt Summary

nmt is a Python library typically used in Utilities, Translation, Deep Learning, Pytorch, Tensorflow, Neural Network, Transformer applications. nmt has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However nmt build file is not available. You can download it from GitHub.

Sequence-to-sequence (seq2seq) models (Sutskever et al., 2014, Cho et al., 2014) have enjoyed great success in a variety of tasks such as machine translation, speech recognition, and text summarization. This tutorial gives readers a full understanding of seq2seq models and shows how to build a competitive seq2seq model from scratch. We focus on the task of Neural Machine Translation (NMT) which was the very first testbed for seq2seq models with wild success. The included code is lightweight, high-quality, production-ready, and incorporated with the latest research ideas. We achieve this goal by:.

            kandi-support Support

              nmt has a medium active ecosystem.
              It has 6232 star(s) with 1976 fork(s). There are 253 watchers for this library.
              It had no major release in the last 6 months.
              There are 251 open issues and 175 have been closed. On average issues are closed in 89 days. There are 24 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of nmt is current.

            kandi-Quality Quality

              nmt has 0 bugs and 0 code smells.

            kandi-Security Security

              nmt has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              nmt code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              nmt is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              nmt releases are not available. You will need to build from source code and install.
              nmt has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              nmt saves you 2275 person hours of effort in developing the same functionality from scratch.
              It has 4972 lines of code, 199 functions and 26 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed nmt and discovered the below as its top functions. This is intended to give you an instant insight into nmt implemented functionality, and help decide if they suit your requirements.
            • Creates an embedding
            • Create a pretrained embedding
            • Create a embedding variable
            • Get the embedding device
            • Train model
            • Trains the model
            • Adds a summary
            • Loads inference data from a file
            • Load hparams
            • Convert tokens to bytes
            • Check if the vocab is valid
            • Calculate ROUGE - 1 score
            • Add arguments to the given parser
            • Evaluate a given metric
            • Load hparams from file
            • Gets summary summary
            • Print hparams
            • Calculate RCS summary level
            • Create hparams
            • Build the decoder cell
            • Builds the decoder cell
            • Compute the BLEU distance between two sequences
            • Decodes and evaluates a model
            • Set training or inference
            • Builds GNMT encoder
            • Builds the graph
            Get all kandi verified functions for this library.

            nmt Key Features

            No Key Features are available at this moment for nmt.

            nmt Examples and Code Snippets

            nmt-wizard,Using the launcher,Server
            Pythondot img1Lines of Code : 119dot img1License : Permissive (MIT)
            copy iconCopy
            export LAUNCHER_CONFIG=${PWD}/settings.ini
            FLASK_APP=main.py flask run [--host=]
            $ curl -X GET ''
                "demogpu02": {
                    "capacity": 1,
                    "name": "OVH-hosted extra training server",
            VAG-NMT,Run the Code,Results
            Pythondot img2Lines of Code : 99dot img2License : Permissive (Apache-2.0)
            copy iconCopy
            nohup python nmt_monomodal_beam_DE.py --data_path ./path/to/data --trained_model_path ./path/to/save/model --sr en --tg de &
            nohup python nmt_monomodal_beam_FR.py --data_path ./path/to/data --trained_model_path ./path/to/save/model --sr en --tg   
            nmt-wizard,Services configuration
            Pythondot img3Lines of Code : 72dot img3License : Permissive (MIT)
            copy iconCopy
                "name": "my-service",  // The short name the user will select.
                "description": "My service",  // Display name of the service.
                "module": "services.XXX",  // Name of the Python module managing the service.
                "variables": { // Non-Service  
            ludwig - train nmt
            Pythondot img4Lines of Code : 12dot img4License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            """Sample ludwig training code for training an NMT model (en -> fr) on WMT15 (https://www.statmt.org/wmt15/).
            The dataset is rather large (8GB), which can take several minutes to preprocess.
            import logging
            import shutil
            from ludwig.api impo  

            Community Discussions


            test/make/TestMake.gmk: No such file or directory when compile the jdk 12
            Asked 2022-Apr-03 at 17:02

            I am tried to compile the JDK 12(wget -c https://hg.openjdk.java.net/jdk/jdk12/archive/tip.tar.gz) in my own MacBook Pro 2019 with Intel Chip(macOS Monterey 12.3.1). Fisrt step I run the configure command:



            Answered 2022-Apr-03 at 17:02

            The errors look like they might be from missing rules:

            Source https://stackoverflow.com/questions/71726566


            What is 'serviceability memory category' of Native Memory Tracking?
            Asked 2022-Jan-17 at 13:38

            I have an java app (JDK13) running in a docker container. Recently I moved the app to JDK17 (OpenJDK17) and found a gradual increase of memory usage by docker container.

            During investigation I found that the 'serviceability memory category' NMT grows constantly (15mb per an hour). I checked the page https://docs.oracle.com/en/java/javase/17/troubleshoot/diagnostic-tools.html#GUID-5EF7BB07-C903-4EBD-A9C2-EC0E44048D37 but this category is not mentioned there.

            Could anyone explain what this serviceability category means and what can cause such gradual increase? Also there are some additional new memory categories comparing to JDK13. Maybe someone knows where I can read details about them.

            Here is the result of command jcmd 1 VM.native_memory summary



            Answered 2022-Jan-17 at 13:38

            Unfortunately (?), the easiest way to know for sure what those categories map to is to look at OpenJDK source code. The NMT tag you are looking for is mtServiceability. This would show that "serviceability" are basically diagnostic interfaces in JDK/JVM: JVMTI, heap dumps, etc.

            But the same kind of thing is clear from observing that stack trace sample you are showing mentions ThreadStackTrace::dump_stack_at_safepoint -- that is something that dumps the thread information, for example for jstack, heap dump, etc. If you have a suspicion for the memory leak in that code, you might try to build a MCVE demonstrating it, and submitting the bug against OpenJDK, or showing it to a fellow OpenJDK developer. You probably know better what your application is doing to cause thread dumps, focus there.

            That being said, I don't see any obvious memory leaks in StackFrameInfo, neither can I reproduce any leak with stress tests, so maybe what you are seeing is "just" thread dumping over the larger and larger thread stacks. Or you capture it when thread dump is happening. Or... It is hard to say without the MCVE.

            Update: After playing with MCVE, I realized that it reproduces with 17.0.1, but not with either mainline development JDK, or JDK 18 EA, or JDK 17.0.2 EA. I tested with 17.0.2 EA before, so was not seeing it, dang. Bisection between 17.0.1 and 17.0.2 EA shows it was fixed with JDK-8273902 backport. 17.0.2 releases this week, so the bug should disappear after you upgrade.

            Source https://stackoverflow.com/questions/70709971


            Subquery returned more than 1 value - Error Message
            Asked 2022-Jan-10 at 16:19

            I'm getting the error message:

            Subquery returned more than 1 value. This is not permitted when the subquery follows =,!=,<,<=,>,=> or when the subquery is used as an expression.

            Below is a small subset of a larger query, but the part of the query to determine the Test_Col value is essentially where I'm running into this issue. The query by itself works, but when I use it as a subquery within the larger query, I get this error message in SQL Server. Any ideas on where I'm going wrong?



            Answered 2022-Jan-09 at 05:25

            In SQL Server DB if your subquery is written after the select command where we wrote field name list, then your subquery must be return only one record and only one field, else you will get an error. In your script, you wrote subquery before the from command, after this Loan_Num,. I did a little research on your subquery. Your subquery will return more than 1 record in most cases. The reason is that you wrote group by nml.hprop and after the where command you wrote this condition nml.hprop in (2380, 3348). I would have written this query for you myself, but I don't know your business logic and what need you. If your subquery must return more than 1 record, so you must join this subquery to the main query, using inner join or left join, you can not write this subquery on the field list.

            Source https://stackoverflow.com/questions/70633642


            How to strip a certain piece of text from each line of a text file?
            Asked 2021-Dec-30 at 00:15

            I have downloaded the tab-separated tatoeba dataset with English-German sentence pairs to train an NMT model on it. Unfortunately each line ends with all sorts of additional information:



            Answered 2021-Dec-28 at 17:32

            The idea of using split is correct but assigning directly in this way in a for loop will not change the list elements.

            You should also avoid using split as a variable name when it is already the name of an inbuilt method.

            A list comprehension will do the job:

            Source https://stackoverflow.com/questions/70510297


            What is the difference between MarianMT and OpusMT?
            Asked 2021-Dec-18 at 14:43

            I'm currently comparing various pre-trained NMT models and can't help but wonder what the difference between MarianMT and OpusMT is. According to OpusMT's Github it is based on MarianMT. However in the Huggingface transformers implementation all pretrained MarianMT models start with "Helsinki-NLP/opus-mt". So I thought it was the same, but even though they're roughly the same size, they yield different translation results.

            If someone could please shed some light on what the differences are I would be very thankful.



            Answered 2021-Dec-18 at 14:43

            Marian is an open-source tool for training and serving neural machine translation, mostly developed at the University of Edinburgh, Adam Mickiewicz University in Poznań and at Microsoft. It is implemented in C++ and is heavily optimized for MT, unlike PyTorch-based Huggingface Transformers that aim for generality rather than efficiency in a specific use case.

            The NLP group at the University of Helsinki trained many translation models using Marian on parallel data collected at Opus, and open-sourced those models. Later, they also did a conversion of the trained model into Huggingface Transformers and made them available via the Huggingface Hub.

            MarianMT is a class in Huggingface Transformers for imported Marian models. You can train a model in Marian and convert it yourself. OpusMT models are Marian models trained on the Opus data in Helsinki converted to the PyTorch models. If you search the Huggingface Hub for Marian, you will find other MarianMT models than those from Helsinki.

            Source https://stackoverflow.com/questions/70367816


            Java Collectors Streaming filter and .toMap when detecting case insensitve duplicates for various types
            Asked 2021-Dec-14 at 19:30

            I have a data structure that collates potential case insensitive naming clashes.

            • caseInsensitiveDuplicates

            • Think of the nested maps as a way of doing a compound key.

            • The integer represents a type of data that may have duplicates,

            • the first String is the uppercase version of the string

            • the set that follows could contain any number of versions.. .. so JEREMY: ['Jeremy', 'jeremy','JEREMY'] etc is plausible data.

            The goal is to identify when the Set contains more than one entry. Upper and lowercase versions of data can co-exist, and I have to identify those cases. Hence this data structure.

            • so the data N1 and n1 will be two entries keyed on the uppercase N1, and I am looking to get that back in the results.

            There is a call to filter this via Streams:

            • I have to work on EntrySet to keep keys/values together. I know that much.
            • I want to return the same data structure I started out with (the type of caseInsensitiveDuplicates)
            • I know I need to filter on the size exceeding 1.

            (My actual code has an enum where Integer is, and a custom class where String is within the Set on the line where it's declared. See code below).

            From initial data like so:



            Answered 2021-Nov-10 at 15:36

            I could not figure out how to do this without resorting to building it manually. If someone else comes up with the correct way to do this with Streams, I will accept that as the answer.

            Have revised this solution, thanks to @Holger for the following tips:

            • entrySet().forEach(…) -> functional style: forEach((k,v) -> ...)
            • computeIfAbsent
            • map.keySet().size() == 0 -> abridged map.isEmpty()

            Source https://stackoverflow.com/questions/69897038


            Save each iteration in a new line
            Asked 2021-Aug-01 at 17:23

            friends! I have the following code:



            Answered 2021-Aug-01 at 17:23
            import requests
            from bs4 import BeautifulSoup
            patterns = [
            def main(url):
                with requests.Session() as req:
                    for pat in patterns:
                        r = req.get(url.format(pat))
                        soup = BeautifulSoup(r.text, 'lxml')
                        name = soup.select_one('.nmt').text
                        goal = [x.text for x in soup.select('.f, .irregular')]
                        print(f"{name} --> {', '.join(goal)}")

            Source https://stackoverflow.com/questions/68610554


            How can i transtale name, address text in english language without changing the pronunciation in GCP translate api using python
            Asked 2021-Jun-10 at 09:41

            I a trying to translate name of person and address from Indian language to English. I want to keep the pronunciation intact. for example "सौरव" needs to change to "sourab". Is there a parameter in google translate using python to do this. There are some html prameter but is there something for python.
            Set google translate don't translate name



            Answered 2021-Jun-02 at 18:24

            Sourav. I was able to replicate the issue, when running your code the result was:

            Source https://stackoverflow.com/questions/67806753


            Reason for adding 1 to word index for sequence modeling
            Asked 2021-Apr-28 at 11:18

            I notice in many of the tutorials 1 is added to the word_index. For example considering a sample code snippet inspired from Tensorflow's tutorial for NMT https://www.tensorflow.org/tutorials/text/nmt_with_attention :



            Answered 2021-Apr-28 at 11:18

            According to the documentation: layers.Embedding: the largest integer in the input should be smaller than the vocabulary size / input_dim.

            input_dim: Integer. Size of the vocabulary, i.e. maximum integer index + 1.

            That's why

            Source https://stackoverflow.com/questions/67293182


            Revolut visa Debit card not detected by libnfc6
            Asked 2021-Apr-08 at 08:03

            Trying to read various payment cards using PN532 NFC RFID Module. libnfc6 sucessfully polls most of the nfc cards and even mobile payment method is detected, but none of my Revolut cards are detected by nfc-poll app.

            libnfc was compiled locally from libnfc-1.8.0 git tag.

            My current polling setup:



            Answered 2021-Apr-08 at 08:03

            Buying new PN532 NFC RFID Module solved the issue.

            Source https://stackoverflow.com/questions/66868180

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install nmt

            You can download it from GitHub.
            You can use nmt like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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