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Updated to use kp instead of komputepy for module name

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This commit is contained in:
Alejandro Saucedo 2020-11-02 21:57:10 +00:00
parent b23e04e1a4
commit 991cfdcbcc
5 changed files with 11 additions and 11 deletions
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2
docs/conf.py
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@ -18,7 +18,7 @@
# -- Project information ----------------------------------------------------- # -- Project information -----------------------------------------------------
import sys import sys
import os import os
import komputepy import kp
project = 'Vulkan Kompute' project = 'Vulkan Kompute'
copyright = '2020, The Institute for Ethical AI & Machine Learning' copyright = '2020, The Institute for Ethical AI & Machine Learning'

10
docs/overview/python-package.rst
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@ -12,9 +12,9 @@ Below is a diagram that provides insights on the relationship between Vulkan Kom
Manager Manager
------- -------
The Kompute Manager provides a high level interface to simplify interaction with underlying :class:`komputepy.Sequence` of Operations. The Kompute Manager provides a high level interface to simplify interaction with underlying :class:`kp.Sequence` of Operations.
.. autoclass:: komputepy.Manager .. autoclass:: kp.Manager
:members: :members:
@ -23,7 +23,7 @@ Sequence
The Kompute Sequence consists of batches of Kompute Operations, which are executed on a respective GPU queue. The execution of sequences can be synchronous or asynchronous, and it can be coordinated through its respective Vulkan Fence. The Kompute Sequence consists of batches of Kompute Operations, which are executed on a respective GPU queue. The execution of sequences can be synchronous or asynchronous, and it can be coordinated through its respective Vulkan Fence.
.. autoclass:: komputepy.Sequence .. autoclass:: kp.Sequence
:members: :members:
@ -32,13 +32,13 @@ Tensor
The Kompute Tensor is the atomic unit in Kompute, and it is used primarily for handling Host and GPU Device data. The Kompute Tensor is the atomic unit in Kompute, and it is used primarily for handling Host and GPU Device data.
.. autoclass:: komputepy.Tensor .. autoclass:: kp.Tensor
:members: :members:
TensorType TensorType
------- -------
.. automodule:: komputepy .. automodule:: kp
:members: :members:

2
python/src/main.cpp
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@ -5,7 +5,7 @@
namespace py = pybind11; namespace py = pybind11;
PYBIND11_MODULE(komputepy, m) { PYBIND11_MODULE(kp, m) {
py::enum_<kp::Tensor::TensorTypes>(m, "TensorTypes", "Enum with GPU memory types for Tensor.") py::enum_<kp::Tensor::TensorTypes>(m, "TensorTypes", "Enum with GPU memory types for Tensor.")
.value("device", kp::Tensor::TensorTypes::eDevice, "Tensor holding data in GPU memory.") .value("device", kp::Tensor::TensorTypes::eDevice, "Tensor holding data in GPU memory.")

2
python/test/test_kompute.py
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@ -1,5 +1,5 @@
from komputepy import Tensor, Manager, Sequence from kp import Tensor, Manager, Sequence
def test_opmult(): def test_opmult():
""" """

6
setup.py
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@ -65,12 +65,12 @@ class CMakeBuild(build_ext):
subprocess.check_call(['cmake', '--build', '.'] + build_args, cwd=self.build_temp) subprocess.check_call(['cmake', '--build', '.'] + build_args, cwd=self.build_temp)
setup( setup(
name='komputepy', name='kp',
version='0.0.1', version='0.0.1',
author='Alejandro Saucedo', author='Alejandro Saucedo',
description='Blazing fast, mobile-enabled, asynchronous, and optimized for advanced GPU processing usecases.', description='Vulkan Kompute: Blazing fast, mobile-enabled, asynchronous, and optimized for advanced GPU processing usecases.',
long_description='', long_description='',
ext_modules=[CMakeExtension('komputepy')], ext_modules=[CMakeExtension('kp')],
cmdclass=dict(build_ext=CMakeBuild), cmdclass=dict(build_ext=CMakeBuild),
zip_safe=False, zip_safe=False,
) )