floydhub / Dockerfiles
Licence: apache-2.0
Deep Learning Dockerfiles
Programming Languages
python 139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Dockerfiles
Deep Dream In PytorchPytorch implementation of the DeepDream computer vision algorithm
Stars: ✭ 90 (-40%)
Mutual labels: torch
LaiaLaia: A deep learning toolkit for HTR based on Torch
Stars: ✭ 109 (-27.33%)
Mutual labels: torch
TorchsampleHigh-Level Training, Data Augmentation, and Utilities for Pytorch
Stars: ✭ 1,731 (+1054%)
Mutual labels: torch
Grad Cam🌈 📷 Gradient-weighted Class Activation Mapping (Grad-CAM) Demo
Stars: ✭ 91 (-39.33%)
Mutual labels: torch
TorchelieTorchélie is a set of utility functions, layers, losses, models, trainers and other things for PyTorch.
Stars: ✭ 98 (-34.67%)
Mutual labels: torch
Ti PoolingTI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks
Stars: ✭ 119 (-20.67%)
Mutual labels: torch
Torch Srgantorch implementation of srgan
Stars: ✭ 76 (-49.33%)
Mutual labels: torch
Samplernn torchTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
Stars: ✭ 146 (-2.67%)
Mutual labels: torch
Pytorch gbw lmPyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset
Stars: ✭ 101 (-32.67%)
Mutual labels: torch
Tf texture netTensorFlow implementation of DmitryUlyanov/texture_nets
Stars: ✭ 96 (-36%)
Mutual labels: torch
CycleganSoftware that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+7188.67%)
Mutual labels: torch
Beauty.torchUnderstanding facial beauty with deep learning.
Stars: ✭ 90 (-40%)
Mutual labels: torch
Prediction FlowDeep-Learning based CTR models implemented by PyTorch
Stars: ✭ 138 (-8%)
Mutual labels: torch
Pytorch ContainersTorch Containers simplified in PyTorch
Stars: ✭ 85 (-43.33%)
Mutual labels: torch
DeepnudecliDeepNude Command Line Version With Watermark Removed
Stars: ✭ 112 (-25.33%)
Mutual labels: torch
Skip Thoughts.torchPorting of Skip-Thoughts pretrained models from Theano to PyTorch & Torch7
Stars: ✭ 146 (-2.67%)
Mutual labels: torch
Synthesize3dviadepthorsil[CVPR 2017] Generation and reconstruction of 3D shapes via modeling multi-view depth maps or silhouettes
Stars: ✭ 141 (-6%)
Mutual labels: torch
Dockerfiles
Collection of Dockerfiles useful for NLP and Deep Learning. To download the docker images
visit: floydhub's Docker Hub.
How to update framework
- Dockerfiles are generated using two inputs:
matrix.yml and jinja template file inside ./dl/FRAMEWORK directory. matrix.yml provides variable values for jinja template files.
- The
$render list in matrix.yml controls what version of the framework to render.
- For each version config in
matrix.yml, any key starts with _ are global keys, which will get automatically injected into each variant config for that version.
-
Most of the cases, you only need to update ./dl/FRAMEWORK/matrix.yml to generate a set of dockerfiles for a new version of a framework. If not, you will need to update the jinja file to account for build step changes.
-
Install floydker: cd floydker && pipenv shell && pipenv install.
-
Render dockerfiles: cd .. && floydker render ..
-
Commit new docker images to git and push: git commit -a.
Naming conventions
Dockerfiles are organized into the following directory structure:
CATEGORY/PROJECT_NAME/VERSION/Dockerfile-ENV
CATEGORY/PROJECT_NAME/VERSION/Dockerfile-ENV.gpu
Automated build scripts will generate the following tags for images based on
the above dockerfile paths:
floydhub/PROJECT_NAME:VERSION-ENV
floydhub/PROJECT_NAME:VERSION-ENV-gpu
Contains docker images for popular deep learning frameworks including: Tensorflow, PyTorch and Torch.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at
[email protected].
