pipseq 0.0.2
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Description:
pipseq 0.0.2
pipseq
Developer Guide
Setup
# create conda environment
$ mamba env create -f env.yml
# update conda environment
$ mamba env update -n pipseq --file env.yml
Install
pip install -e .
# install from pypi
pip install pipseq
nbdev
# activate conda environment
$ conda activate pipseq
# make sure the pipseq package is installed in development mode
$ pip install -e .
# make changes under nbs/ directory
# ...
# compile to have changes apply to the pipseq package
$ nbdev_prepare
Publishing
# publish to pypi
$ nbdev_pypi
# publish to conda
$ nbdev_conda --build_args '-c conda-forge'
$ nbdev_conda --mambabuild --build_args '-c conda-forge -c dsm-72'
Usage
Installation
Install latest from the GitHub
repository:
$ pip install git+https://github.com/dsm-72/pipseq.git
or from conda
$ conda install -c dsm-72 pipseq
or from pypi
$ pip install pipseq
Documentation
Documentation can be found hosted on GitHub
repository
pages. Additionally you can find
package manager specific guidelines on
conda and
pypi respectively.
PyTorch Documentation:
TorchData
How to Package PyTorch
Models
torch.monitor.Event
torchvision
torchvision.Datasets.VisionDataset
torchvision.utils.flow_to_image
PyTorch Models to Consider:
Diffusion Video
AutoEncoders
ConvLSTM
AutoEncoder
Recurrent All Pairs Field Transforms for Optical
Flow
Optical Flow Toolbox
(mmflow)
torchvision.models.optical_flow.raft
License:
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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