UNITER | Research code for ECCV 2020 paper | Machine Learning library
kandi X-RAY | UNITER Summary
kandi X-RAY | UNITER Summary
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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Top functions reviewed by kandi - BETA
- 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
UNITER Key Features
UNITER Examples and Code Snippets
Community Discussions
Trending Discussions on UNITER
QUESTION
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 20:59This 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:
QUESTION
I have the following function that is trying to load a .ejs file with the following path.
...ANSWER
Answered 2020-Sep-23 at 16:39QUESTION
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 20:46SOLVED!
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.
QUESTION
ANSWER
Answered 2020-Jun-30 at 17:18Solution:
Move the "xmlbuilder": "^15.1.1" line to be inside the "dependencies"
Here is the updated package.json file
QUESTION
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 15:04this 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
QUESTION
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 16:58I 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"))
.
QUESTION
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 19:10For grails >= 3.3.0 you can mock domain classes using new Unit Test framework features. Implement DataTest and getDomainClassesToMock():
QUESTION
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 16:56Your datasource configuration is not being loaded because runtime.groovy
is not part of the scripts loaded by HibernateSpec
QUESTION
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 09:53It 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.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install UNITER
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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