Similar to the eye corneal limbus - Limbus is a framework to create Computer Vision pipelines within the context of Deep Learning and writen in terms of differentiable tensors message passing on top of Kornia and PyTorch.
You can create pipelines using limbus.Component
s as follows:
# define your components
c1 = Constant("c1", 1.)
c2 = Constant("c2", torch.ones(1, 3))
add = Adder("add")
show = Printer("print")
# connect the components
c1.outputs.out >> add.inputs.a
c2.outputs.out >> add.inputs.b
add.outputs.out >> show.inputs.inp
# create the pipeline and add its nodes
pipeline = Pipeline()
pipeline.add_nodes([c1, c2, add, show])
# run your pipeline
pipeline.run(1)
torch.allclose(add.outputs.out.value, torch.ones(1, 3) * 2.)
Example using the stack
torch method:
# define your components
c1 = Constant("c1", 0)
t1 = Constant("t1", torch.ones(1, 3))
t2 = Constant("t2", torch.ones(1, 3) * 2)
stack = Stack("stack")
show = Printer("print")
# connect the components
c1.outputs.out >> stack.inputs.dim
t1.outputs.out >> stack.inputs.tensors.select(0)
t2.outputs.out >> stack.inputs.tensors.select(1)
stack.outputs.out >> show.inputs.inp
# create the pipeline and add its nodes
pipeline = Pipeline()
pipeline.add_nodes([c1, t1, t2, stack, show])
# run your pipeline
pipeline.run(1)
torch.allclose(stack.outputs.out.value, torch.tensor([[1., 1., 1.],[2., 2., 2.]]))
Remember that the components can be run without the Pipeline
, e.g in the last example you can also run:
asyncio.run(asyncio.gather(c1(), t1(), t2(), stack(), show()))
Basically, Pipeline
objects allow you to control the execution flow, e.g. you can stop, pause, resume the execution, determine the number of executions to be run...
A higher level API on top of Pipeline
is App
allowing to encapsulate some code. E.g.:
class MyApp(App):
def create_components(self):
self.c1 = Constant("c1", 0)
self.t1 = Constant("t1", torch.ones(1, 3))
self.t2 = Constant("t2", torch.ones(1, 3) * 2)
self.stack = stack("stack")
self.show = Printer("print")
def connect_components(self):
self.c1.outputs.out >> self.stack.inputs.dim
self.t1.outputs.out >> self.stack.inputs.tensors.select(0)
self.t2.outputs.out >> self.stack.inputs.tensors.select(1)
self.stack.outputs.out >> self.show.inputs.inp
MyApp().run(1)
git clone https://github.com/kornia/limbus
cd limbus
source path.bash.inc
In order to regenerate the environment:
cd limbus
rm -rf .dev_env
Run pytest
and automatically will test: cov
, pydocstyle
, mypy
and flake8