UNITER | Research code for ECCV 2020 paper | Machine Learning library

 by   ChenRocks Python Version: Current License: No License

kandi X-RAY | UNITER Summary

kandi X-RAY | UNITER Summary

UNITER is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. UNITER has no bugs, it has no vulnerabilities and it has low support. However UNITER build file is not available. You can download it from GitHub.

This is the official repository of UNITER (ECCV 2020). This repository currently supports finetuning UNITER on NLVR2, VQA, VCR, SNLI-VE, Image-Text Retrieval for COCO and Flickr30k, and Referring Expression Comprehensions (RefCOCO, RefCOCO+, and RefCOCO-g). Both UNITER-base and UNITER-large pre-trained checkpoints are released. UNITER-base pre-training with in-domain data is also available. Some code in this repo are copied/modified from opensource implementations made available by PyTorch, HuggingFace, OpenNMT, and Nvidia. The image features are extracted using BUTD.
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            kandi-support Support

              UNITER has a low active ecosystem.
              It has 720 star(s) with 106 fork(s). There are 17 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 45 open issues and 49 have been closed. On average issues are closed in 27 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of UNITER is current.

            kandi-Quality Quality

              UNITER has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              UNITER does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              UNITER releases are not available. You will need to build from source code and install.
              UNITER has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.
              UNITER saves you 3504 person hours of effort in developing the same functionality from scratch.
              It has 7501 lines of code, 342 functions and 50 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed UNITER and discovered the below as its top functions. This is intended to give you an instant insight into UNITER implemented functionality, and help decide if they suit your requirements.
            • Evaluate the given model
            • Helper function to decode a byte array
            • Gathers all the data from the torch
            • Encode enc
            • Validate the given model
            • Run MLM validation
            • Run the validation function
            • Run the validation
            • Collate input tensor
            • Save training meta data
            • Build optimizer
            • Concatenate training image
            • Perform the forward computation
            • Concatenate MLM layer
            • Forward attention layer
            • Perform a forward computation
            • Combine Tensors into Tensor
            • Re - collate input tensors
            • Process references within reference annotations
            • Instantiate a pretrained model from a pretrained model
            • Create daloaders from datasets
            • Perform multi - head attention
            • Re - evaluation function
            • Compute the prediction
            • Concatenate the RDF features
            • Broadcast tensors into memory
            Get all kandi verified functions for this library.

            UNITER Key Features

            No Key Features are available at this moment for UNITER.

            UNITER Examples and Code Snippets

            No Code Snippets are available at this moment for UNITER.

            Community Discussions

            QUESTION

            How deal with the UndefinedUnitError?
            Asked 2021-Mar-01 at 20:59

            I downloaded data from noaa and i wanted to calculate vertical velocity using the function vertical_velocity=metpy.calcmpcalc.vertical_velocity(omega,pressure,temperature). But something wrong when i dealing with the units of varibles.

            ...

            ANSWER

            Answered 2021-Mar-01 at 20:59

            This is a problem where the unit library MetPy uses (Pint) does not have the same rules about capitalization/case sensitivity as the UDUnits format used by the netCDF Climate and Forecasting Conventions for metadata. Fixing this is on MetPy's todo list, but some roadblocks have been encountered.

            The work-around right now is to change your units to something that Pint understands, like:

            Source https://stackoverflow.com/questions/66410797

            QUESTION

            Electron Project cannot file with correct path
            Asked 2020-Sep-23 at 16:39

            I have the following function that is trying to load a .ejs file with the following path.

            ...

            ANSWER

            Answered 2020-Sep-23 at 16:39

            I don't know if this will help but what I do is to build an absolute path using the path library (actually I use upath for cross platform compatibility because I often need to save the path to a file).

            Source https://stackoverflow.com/questions/64029085

            QUESTION

            Are there changes between OpenStack Xenial/Pike and Xenial/Queens that would prevent JuJu from creating openvswitch bridges?
            Asked 2020-Aug-19 at 20:46

            We've been running an OpenStack environment for the last 2 and a half years with a few hiccups along the way, but mostly with little downtime. Recently we've been trying to add a new piece of hardware to the stack as a nova-compute node to provide more CPU cores and RAM to our VMs. Unfortunately, for some reason, the install is not going well.

            We're running Xenial/Queens with JuJu and MaaS for deployment/provisioning. We were running Xenial/Pike until December when we upgraded. We're starting to suspect that the upgrade to Queens is what's causing the trouble as we were able to add new hardware before the upgrade. We even went as far as removing one of our existing machines that was acting as a nova-compute node and tried adding it back to the stack and it too is now exhibiting the same problems as our new hardware.

            The root cause of the problems seems to be with the neutron-openvswitch application. When we install the nova-compute charm via JuJu everything seems to go smoothly up until the (automatic) installation/configuration of the subordinate neutron-openvswitch charm. While watching the logs at a certain point during the install connectivity on our OpenStack admin network (10.10.30.0/24 on eno1) is lost. We're able to force the installation to proceed a bit further by adding a second connection on eno2 (a different external network), but the loss of connectivity on eno1 remains and the compute service isn't able to communicate with the rest of the stack.

            Looking at our other compute nodes in the stack that are functional, it looks like the admin network bridge (br-eno1) is not being created by the neutron-openvswitch charm. Some part of the process looks like it's taking down eno1 in preparation of creating the bridge, but then fails, leaving the machine unable to communicate on that interface with the rest of the stack.

            None of our configuration has changed since the upgrade to Queens, but perhaps there is some deprecation or change to the default configuration that came along with the Pike -> Queens upgrade we are unaware of? We've read through the release notes but can't seem to find anything that would explain this behavior.

            Any help would be greatly appreciated. I'm including a few segments of log files I think are relevant below but can provide anything else that might be needed. Thanks in advance!

            Broken server ifconfig

            ...

            ANSWER

            Answered 2020-Aug-19 at 20:46

            SOLVED!

            It turns out that after the upgrade to Queens JuJu was handing out a bad network config to this server. In addition, the OpenVSwitch install was assigning eno1 to br-data instead of creating br-eno1 like on my other servers. The steps to resolve the problem were:

            • Remove eno1 from the br-data bridge: ovs-vsctl del-port br-data eno1
            • Copy the functional config from another working server to this servers /etc/network/interfaces file and comment out the line that reads the (busted) cloud config file from /etc/network/interface.d/50-cloud-init.cfg
            • Update the IPs in the new interfaces file to those found in ifconfig for the eno1 and eno2 interfaces
            • Reboot
            • Profit

            I don't yet know exactly what caused JuJu to stop sending a proper network config after the upgrade.

            My final interfaces file looked like this. Anyone else copying this file will of course have to change all of their IPs.

            Source https://stackoverflow.com/questions/62179322

            QUESTION

            Cannot find module 'xmlbuilder' when trying to run Production version of Electron Project
            Asked 2020-Jun-30 at 17:18

            I have an electron program I am building to production. When I run the .exe created I get the following error.

            I have installed xmlbuilder using the following command

            npm install -g xmlbuilder

            Here is my package.json file as well.

            ...

            ANSWER

            Answered 2020-Jun-30 at 17:18

            Solution:

            Move the "xmlbuilder": "^15.1.1" line to be inside the "dependencies"

            Here is the updated package.json file

            Source https://stackoverflow.com/questions/62417712

            QUESTION

            Problems calling another class
            Asked 2020-Jun-25 at 15:04

            I have to use 2 classes to complete a sort of game,

            "Units" are the soldiers that fight in our fictitious war. Units will be defined by a class in python called Unit. For Nick Wars, our units will have the following properties:

            Team - A string indicating which team the unit belongs to. This will always either be "Red" or "Blue". Must be initialized. HP - hitpoints / health / energy / pep. The amount of damage a unit can sustain before being killed. Units can not regain or recover HP. Must be initialized. ATT - attack / strength. The amount of damage a unit can do in a single hit. Must be initialized. attack_timeout - The amount of time that must pass between attacks, measured in tick's (see methods below). Must be initialized. isDead - True if this unit is dead, False if it is living. Initializes to False. Methods:

            tick(self, opponents) - each time tick is called, we simulate one unit of time passing inside the game scenario. Any "automatic" behaviours of a unit are defined here (so, we are in essence programming the unit AI). The argument opponents is a list of all units which are valid attack targets. The following behaviours must be created if isDead is False. A dead unit performs none of these behaviours and immediately returns the integer value 0. If the list of opponents has any living units, this unit attacks the unit with the lowest HP (see the attack method). In this case, this method returns the integer value 0. If multiple units have the same HP, go with the first unit with that HP in the list of opposing units. If the list of opponents is empty or contains no living units, return this unit's attack value. This will be used later to calculate damage to the enemy's base. The above two actions can only occur if it has been the specified number of ticks since the last attack by this unit. How to keep try of this is left as an exercise to the reader. attack(self, other) - Called when this unit (self) attacks a defending unit (other). The defending unit has it's HP reduced by this unit's attack value. If this reduces the defending unit's HP to or past zero, set isDead to True.

            I've completed this part and it looks like this

            ...

            ANSWER

            Answered 2020-Jun-25 at 15:04

            this was pretty fun code to play around with! I had to make a few changes to get it to work, partly to understand what was happening and make the code a bit more pythonic. I made some assumptions about the intended purpose of various methods/how you wanted the attack priorities to work, but I'll explain everything and try justify it all.

            General Throughout I've switched from CamelCase to snake_case for variable names, and have passed the code through a linter to bring it in line with the Python PEP 8 style guide.

            Added the TooPoorError

            Source https://stackoverflow.com/questions/62492179

            QUESTION

            Can a parameter be used to set the unit attribute for a component?
            Asked 2019-Jul-03 at 16:58

            So far, using Wolfram System Modeler 4.3 and 5.1 the following minimal example would compile without errors:

            ...

            ANSWER

            Answered 2019-Jul-03 at 16:58

            I have been given feedback on Wolfram Community by someone from Wolfram MathCore regarding this issue:

            You are correct in that it's not in violation with the specification, although making it a constant makes more sense since you would invalidate all your static unit checking if you are allowed to change the unit after building the simulation. We filed an issue on the specification regarding this (Modelica Specification Issue # 2362).

            So, MatheCore is a bit ahead of the game in proposing a Modelica specification change that they have already implemented. ;-)

            Note: That in Wolfram System Modeler (12.0) using the annotation Evaluate = true will not cure the problem (cf. the comment above by @matth).

            As a workaround variables used to set the unit attribute should have constant variability, but can nevertheless by included in user dialogs to be interactively changed using annotation(Dialog(group = "GroupName")).

            Source https://stackoverflow.com/questions/56154630

            QUESTION

            How do I use Mock in Spock to do tests in Grails?
            Asked 2018-Jan-10 at 19:10

            I am trying use mock to the domains class but in findBy is not working, show that the class is null.

            At last time give this error:

            ...

            ANSWER

            Answered 2018-Jan-10 at 19:10

            For grails >= 3.3.0 you can mock domain classes using new Unit Test framework features. Implement DataTest and getDomainClassesToMock():

            Source https://stackoverflow.com/questions/48193391

            QUESTION

            grails 3.3.0: org.h2.jdbc.JdbcSQLException: Table "XYZ" not found in unit tests
            Asked 2017-Aug-09 at 08:03
            Summary

            I'm trying to create a new grails 3.3.0 application, with some simple domain classes.

            I'm also using the new HibernateSpec (coming with GORM 6.1.x) to create an in-memory H2 database for my unit test.

            I used this technique with previous versions of grails, but now with grails 3.3.0 I am getting a system failure.

            Hibernate seems to create the tables, but then, when I try to execute a query inside my unit test, it complains that the table cannot be found.

            Details This is my datasource configuration (in application.groovy): ...

            ANSWER

            Answered 2017-Aug-08 at 16:56

            Your datasource configuration is not being loaded because runtime.groovy is not part of the scripts loaded by HibernateSpec

            https://github.com/grails/gorm-hibernate5/blob/master/grails-plugin/src/main/groovy/grails/test/hibernate/HibernateSpec.groovy#L45

            Source https://stackoverflow.com/questions/45573674

            QUESTION

            Setting rate on AudioUnit subtype kAudioUnitSubType_NewTimePitch
            Asked 2017-Jun-26 at 09:53

            I'm trying to get/set the rate of an AudioUnit with subtype kAudioUnitSubType_NewTimePitch.

            The audio unit is added to an AUGraph, through an AUNode, which has the following component description:

            ...

            ANSWER

            Answered 2017-Jun-26 at 09:53

            It turns out the type of the Audio Unit was wrong.

            I changed for kAudioUnitType_FormatConverter for the type and kept the same subtype.

            Both get/set the tempo now works as expected.

            I'm still unclear about why I didn't get any error, neither on setting up the audio unit, nor when setting the value for the rate.

            Source https://stackoverflow.com/questions/44744683

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

            Vulnerabilities

            No vulnerabilities reported

            Install UNITER

            NOTE: Please run bash scripts/download_pretrained.sh $PATH_TO_STORAGE to get our latest pretrained checkpoints. This will download both the base and large models. We use NLVR2 as an end-to-end example for using this code base.
            Download processed data and pretrained models with the following command. bash scripts/download_nlvr2.sh $PATH_TO_STORAGE After downloading you should see the following folder structure: ├── ann │   ├── dev.json │   └── test1.json ├── finetune │   ├── nlvr-base │   └── nlvr-base.tar ├── img_db │   ├── nlvr2_dev │   ├── nlvr2_dev.tar │   ├── nlvr2_test │   ├── nlvr2_test.tar │   ├── nlvr2_train │   └── nlvr2_train.tar ├── pretrained │   └── uniter-base.pt └── txt_db    ├── nlvr2_dev.db    ├── nlvr2_dev.db.tar    ├── nlvr2_test1.db    ├── nlvr2_test1.db.tar    ├── nlvr2_train.db    └── nlvr2_train.db.tar
            Launch the Docker container for running the experiments. # docker image should be automatically pulled source launch_container.sh $PATH_TO_STORAGE/txt_db $PATH_TO_STORAGE/img_db \ $PATH_TO_STORAGE/finetune $PATH_TO_STORAGE/pretrained The launch script respects $CUDA_VISIBLE_DEVICES environment variable. Note that the source code is mounted into the container under /src instead of built into the image so that user modification will be reflected without re-building the image. (Data folders are mounted into the container separately for flexibility on folder structures.)
            Run finetuning for the NLVR2 task. # inside the container python train_nlvr2.py --config config/train-nlvr2-base-1gpu.json # for more customization horovodrun -np $N_GPU python train_nlvr2.py --config $YOUR_CONFIG_JSON
            Run inference for the NLVR2 task and then evaluate. # inference python inf_nlvr2.py --txt_db /txt/nlvr2_test1.db/ --img_db /img/nlvr2_test/ \ --train_dir /storage/nlvr-base/ --ckpt 6500 --output_dir . --fp16 # evaluation # run this command outside docker (tested with python 3.6) # or copy the annotation json into mounted folder python scripts/eval_nlvr2.py ./results.csv $PATH_TO_STORAGE/ann/test1.json The above command runs inference on the model we trained. Feel free to replace --train_dir and --ckpt with your own model trained in step 3. Currently we only support single GPU inference.
            Customization # training options python train_nlvr2.py --help command-line argument overwrites JSON config files JSON config overwrites argparse default value. use horovodrun to run multi-GPU training --gradient_accumulation_steps emulates multi-gpu training
            Misc. # text annotation preprocessing bash scripts/create_txtdb.sh $PATH_TO_STORAGE/txt_db $PATH_TO_STORAGE/ann # image feature extraction (Tested on Titan-Xp; may not run on latest GPUs) bash scripts/extract_imgfeat.sh $PATH_TO_IMG_FOLDER $PATH_TO_IMG_NPY # image preprocessing bash scripts/create_imgdb.sh $PATH_TO_IMG_NPY $PATH_TO_STORAGE/img_db In case you would like to reproduce the whole preprocessing pipeline.

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