Merge branch 'master' into imjoy

Author: FynnBe

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 20.2.0-alpha.5
+current_version = 20.2.0-alpha.6
 parse = (?P<year>\d+)\.(?P<month>\d+)\.(?P<number>\d+)(\-(?P<release>[a-z]+)(\.(?P<build>\d+))?)?
 serialize = 
 	{year}.{month}.{number}-{release}.{build}

README.md

@@ -1,36 +1,26 @@
 # tiktorch
-[![CircleCI](https://circleci.com/gh/ilastik/tiktorch.svg?style=svg)](https://circleci.com/gh/ilastik/tiktorch)
+[![CircleCI](https://circleci.com/gh/ilastik/tiktorch.svg?style=shield)](https://circleci.com/gh/ilastik/tiktorch)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 
-Wrappers for Pytorch
+## Installation
+To install tiktorch and start server run:
+```
+conda create -n tiktorch-server-env -c ilastik-forge -c conda-forge -c pytorch tiktorch
 
-## tiktorch specification
+conda activate tiktorch-server-env
 
-Models saved for tiktorch must follow this specification:
+tiktorch-server
+```
 
-A folder containing the files
+## Development environment
 
-- `model.py`: python file that defines the model.
-- `state.nn`: state dict of the model, as obtained by `torch.save(model.state_dict(), 'state.nn')`
-- `tiktorch_config.yml`: yaml file with metadata
+To create development environment run:
 
-The config must contain the following keys:
+```
+conda env create --name tiktorch-env --file ./environment.yml
+```
 
-- `input_shape`: shape of valid network input, must be either CHW (2D) or CDHW (3D)
-- `output_shape`: shape of network output given input with `input_shape`; same format
-- `dynamic_input_shape`: TODO explain
-- `model_class_name`: name of the model class in `model.py`
-- `model_init_kwargs`: keyword arguments to build model
-- `torch_version`: torch version used to train this model
-
-In addition, the config may contain the following keys:
-
-- `description`: Description of the pre-trained model
-- `data_source`: URL of the data used for pre-training
-
-TODO explain how to generate with tiktorch.
-
-Possible extensions:
-
-- specification for training set-up
-- specifiying additional python modules necessary to run the model
-- load model saved via `torch.save(model, path)` instead of state dict
+Run tests:
+```
+pytest
+```

conda-recipe/meta.yaml

@@ -16,7 +16,7 @@ build:
   number: {{ GIT_DESCRIBE_NUMBER }}
   script: python -m pip install --no-deps --ignore-installed .
   string: np{{CONDA_NPY}}py{{CONDA_PY}}_{{PKG_BUILDNUM}}_h{{PKG_HASH}}_g{{GIT_FULL_HASH[:7]}}
-  entrypoints:
+  entry_points:
     - tiktorch-server = tiktorch.server.base:main
 
 requirements:
@@ -29,6 +29,8 @@ requirements:
     - numpy >=1.14
     - python-bioimage-io
     - pytorch-bioimage-io
+    - grpcio=1.16.0
+    - protobuf=3.11.4
     - pyyaml
     - paramiko
     - inferno

environment.yml

@@ -23,6 +23,7 @@ dependencies:
   - conda-build
   - anaconda-client
   - bump2version
+  - pre_commit
   - pip:
       - pytest-grpc==0.7.0
       - git+https://github.com/bioimage-io/python-bioimage-io#egg=pybio # bump

setup.py

@@ -11,7 +11,7 @@
 
 setup(
     name="tiktorch",
-    version="20.2.0-alpha.5",
+    version="20.2.0-alpha.6",
     description="Tiktorch client/server",
     long_description=long_description,
     long_description_content_type="text/markdown",