Prepare PythonWrapper for next release

pull/53/head
Christophe Favergeon 3 years ago
parent 89610e31cb
commit 1edf36dff6

@ -11,9 +11,9 @@ The signal processing chain can thus be tested and developed in a Python environ
A tutorial is also available but with less details than this README: A tutorial is also available but with less details than this README:
https://developer.arm.com/documentation/102463/latest/ https://developer.arm.com/documentation/102463/latest/
This wrapper is also containing the scripts for the new CMSIS-DSP [Synchronous Data Flow](https://github.com/ARM-software/CMSIS-DSP/blob/main/SDFTools/README.md) (SDF) framework. This wrapper is also containing the scripts for the new CMSIS-DSP compute graph framework (CG).
SDF is also including some nodes to communicate with Modelica using the VHT Modelica blocks developed as part of our [VHT-SystemModeling](https://github.com/ARM-software/VHT-SystemModeling) demos. CG is also including some nodes to communicate with Modelica using the VHT Modelica blocks developed as part of our [VHT-SystemModeling](https://github.com/ARM-software/VHT-SystemModeling) demos.

@ -19,11 +19,11 @@ from cmsisdsp_svm import *
__version__ = cmsisdsp.version.__version__ __version__ = cmsisdsp.version.__version__
# CMSIS-DSP Version used to build the wrapper # CMSIS-DSP Version used to build the wrapper
cmsis_dsp_version="1.12.0" cmsis_dsp_version="1.12.1"
# CMSIS-DSP Commit hash used to build the wrapper # CMSIS-DSP Commit hash used to build the wrapper
commit_hash="7a8b3da85e97808b6b467377c93d447cfa6a6a6d" commit_hash="89610e31cbb3c67067f5bfbcacb338fd7910023e"
# True if development version of CMSIS-DSP used # True if development version of CMSIS-DSP used
# (So several CMSIS-DSP versions may have same version number hence the commit hash) # (So several CMSIS-DSP versions may have same version number hence the commit hash)

@ -606,7 +606,7 @@ class Graph():
# consumer to consume it. # consumer to consume it.
# When we select a node for scheduling later we try # When we select a node for scheduling later we try
# to minimize the occupancy number of all FIFOs by # to minimize the occupancy number of all FIFOs by
# selecting the schedulign which is giving the # selecting the scheduling which is giving the
# minimum maximum occupancy number after the run. # minimum maximum occupancy number after the run.
bMax = 1.0*np.array(initB) / normV bMax = 1.0*np.array(initB) / normV
@ -617,7 +617,7 @@ class Graph():
evolutionTime = 0 evolutionTime = 0
# While there are remaining nodes to schedule # While there are remaining nodes to schedule
while (n != zeroVec).any(): while (n != zeroVec).any():
# Look for the best mode to schedule # Look for the best node to schedule
# which is the one giving the minimum FIFO increase # which is the one giving the minimum FIFO increase
# None selected # None selected

@ -1 +1,2 @@
__version__ = "1.6.0" # Python wrapper version
__version__ = "1.7.0"

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