Merge remote-tracking branch 'tfs/master' into HEAD

Author: FT-SNN Build Service

README.md

@@ -12,13 +12,12 @@ You can use Kaspersky Neuromorphic Platform to do the following:
 
 - Create spiking neural networks (SNNs) and train these on various types of input data, such as telemetry, events, images, 3D data, audio, and tactile data.
 - Convert artificial neural networks (ANNs) into spiking networks and train these.
-- Optimize the structure of the loaded neural networks.
 - Conduct applied research in the field of input data classification and other application domains of neural networks.
 - Develop new neural network topologies, for example, impulse analogs of convolutional neural networks that involve convolution in space and time.
 - Develop new models of synaptic plasticity.
 - Implement new neuron models.
 - Implement application solutions based on neuromorphic spiking neural networks in the field of robotic manipulators, Internet of Things, unmanned systems, human-machine interaction, wearable devices, and optimization planning.
-- Implement application solutions on devices with low power consumption or using neuromorphic processors.
+- Implement application solutions on devices with low power consumption using neuromorphic processors.
 
 You can use the C++ and Python languages to accomplish these tasks. The platform supports CPUs as well as the AltAI-1 neuromorphic processor unit designed for energy-efficient execution of neural networks in various types of intelligent devices.
 
@@ -93,199 +92,6 @@ To work with the platform, the following software must be installed on the devic
   - python3-tqdm
   - TensorFlow 2.13.1
 
-## Installing the platform
-
-For the development of application solutions on Linux, you can install the platform in one of the following ways:
-
-- Install deb packages.
-- Install packages for the development of application solutions in Python.
-
-When working with the platform source code on Linux or Windows, you can build the platform or an application solution using C++. The platform build can be used to develop the Kaspersky Neuromorphic Platform.
-
-### Installing deb packages
-
-_To install the deb packages:_
-
-1. To install deb packages containing CPU and `AltAI SNN` backend binaries, run the following commands as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-cpu-single-threaded-backend_<knp_version>_amd64.deb
-   dpkg -i <path-to-deb-package>/knp-cpu-multi-threaded-backend_<knp_version>_amd64.deb
-   dpkg -i <path-to-deb-package>/knp-altai-backend_<motiv_version>_amd64.deb
-   ```
-
-   When installing the `knp-altai-backend_<motiv_version>_amd64.deb` package, accept the AltAI-1 backends and `ANN2SNN` package Terms of Use. Your acceptance of the Terms of Use is a prerequisite for installing the package. The package installation process will be interrupted unless you accept the Terms of Use.
-
-1. To install the deb package with C ++ framework binary code, run the following command as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-cpp-framework_<knp_version>_amd64.deb
-   ```
-
-1. To install dev-deb packages, run the following commands as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-cpu-multi-threaded-backend-dev_<knp_version>_amd64.deb
-   dpkg -i <path-to-deb-package>/knp-cpu-single-threaded-backend-dev_<knp_version>_amd64.deb
-   dpkg -i <path-to-deb-package>/knp-altai-backend-dev_<motiv_version>_amd64.deb
-   dpkg -i <path-to-deb-package>/knp-cpp-framework-dev_<knp_version>_amd64.deb
-   ```
-
-   When installing the `knp-altai-backend-dev_<motiv_version>_amd64.deb` package, accept the AltAI-1 backends and `ANN2SNN` package Terms of Use. Your acceptance of the Terms of Use is a prerequisite for installing the package. The package installation process will be interrupted unless you accept the Terms of Use.
-
-1. To install the deb package with a Python framework for an `AltAI SNN` backend, run the following as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-python3-framework_<knp_version>_amd64.deb
-   ```
-
-1. To install the deb packages with `ANN2SNN` package and `AltAI ANN2SNN` backend binary code, run the following commands as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp_ann2snn.deb
-   ```
-
-   When installing the `knp_ann2snn.deb` package, accept the AltAI-1 backends and `ANN2SNN` package Terms of Use. Your acceptance of the Terms of Use is a prerequisite for installing the package. The package installation process will be interrupted unless you accept the Terms of Use.
-
-1. To install the deb package with platform usage examples, run the following command as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-examples_<knp_version>_amd64.deb
-   ```
-
-1. To install the deb package with the API reference guide, run the following command as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-documentation_<knp_version>_all.deb
-   ```
-
-where:
-
-- `<path-to-deb-package>` is the path to the deb package;
-- `<knp_version>` is the Kaspersky Neuromorphic Platform version.
-- `<motiv_version>` is the version of the backends for the AltAI-1 neuromorphic processor and the `ANN2SNN` package.
-
-### Installing Python development packages
-
-The following DEB or WHL packages must be installed for Python development:
-
-- deb packages:
-  - `knp-python3-framework_<knp_version>_amd64.deb`: a deb package containing a Python framework for an `AltAI SNN` backend.
-  - `knp_ann2snn.deb`: a deb package with the `ANN2SNN` package, `AltAI ANN2SNN` backend binary code for the AltAI-1 neuromorphic processor, and a component for placing the neural network on AltAI-1.
-- whl packages for installing from PyPI:
-  - `knp-<knp_version>-py3-none-any.whl`: a whl package containing a Python framework for an `AltAI SNN` backend.
-
-  - `knp_ann2snn_x86_64_<motiv_version>-py3-none-any.whl`: a whl package with the `ANN2SNN` package, `AltAI ANN2SNN` backend binary code for the AltAI-1 neuromorphic processor, and a component for placing the neural network on AltAI-1.
-
-    This package is installed on x86-based computers.
-
-  - `knp_ann2snn_aarch64-<motiv_version>-py3-none-any.whl`: a whl package with the `ANN2SNN` package and the `AltAI ANN2SNN` backend binary code for the AltAI-1 neuromorphic processor.
-
-    This package is installed on ARM-based computers.
-
-where:
-
-- `<knp_version>` is the version of Kaspersky Neuromorphic Platform.
-- `<motiv_version>` is the version of the backends for the AltAI-1 neuromorphic processor and the `ANN2SNN` package.
-
-_To install deb packages for Python development:_
-
-1. To install the deb package with a Python framework for an `AltAI SNN` backend, run the following as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp-python3-framework_<knp_version>_amd64.deb
-   ```
-
-1. To install the deb packages with `ANN2SNN` package and `AltAI ANN2SNN` backend binary code, run the following commands as root:
-
-   ```
-   dpkg -i <path-to-deb-package>/knp_ann2snn.deb
-   ```
-
-   When installing the `knp_ann2snn.deb` package, accept the AltAI-1 backends and `ANN2SNN` package Terms of Use. Your acceptance of the Terms of Use is a prerequisite for installing the package. The package installation process will be interrupted unless you accept the Terms of Use.
-
-where:
-
-- `<path-to-deb-package>` is the path to the deb package;
-- `<knp_version>` is the Kaspersky Neuromorphic Platform version.
-
-Use the `pip3` package manager to install whl packages from the PyPI platform.
-
-_To install the whl packages:_
-
-1. To install a whl package containing a Python framework for an `AltAI SNN` backend, run the following command:
-
-   ```
-   pip3 install --break-system-packages knp-<knp_version>-py3-none-any.whl
-   ```
-
-1. To install a whl package containing an `ANN2SNN` package and `AltAI ANN2SNN` backend binaries, do one of the following:
-
-   - To install a package on an x86-based computer, run:
-
-     ```
-     pip3 install --break-system-packages knp_ann2snn_x86_64_<motiv_version>-py3-none-any.whl
-     ```
-
-   - If you need to install a package on an ARM-based computer, run:
-
-     ```
-     pip3 install --break-system-packages knp_ann2snn_aarch64-<motiv_version>-py3-none-any.whl.whl
-     ```
-
-where:
-
-- `<knp_version>` is the version of Kaspersky Neuromorphic Platform.
-- `<motiv_version>` is the version of the backends for the AltAI-1 neuromorphic processor and the `ANN2SNN` package.
-
-### Scenario for building a platform project or an application solution
-
-You can build a platform or an application solution in C++. The platform build can be used when developing the Kaspersky Neuromorphic Platform.
-
-When developing application solutions, you can install the required deb packages instead of building the solution.
-
-You can also use the Docker image `knp-build-image` included in the platform distribution kit to build the platform or an application.
-
-A platform or application solution build script consists of the following stages:
-
-1. Obtaining the platform source code
-
-   You can get the platform source code in one of the following ways:
-
-   - Download the archive with the source code from the platform repository and unpack it to the working directory.
-   - Clone the platform repository.
-
-1. Defining the Boost_ROOT setting in Windows
-
-   In Windows, define the `Boost_ROOT` setting. To do this, create an environment variable or specify the path to the installed Boost library in the `CMakePresets.json` file located in the root directory with the platform source code.\
-   You can define the path to the installed Boost library as a CMake invocation parameter using the following command:
-
-   ```
-   cmake -DBOOST-ROOT=<path to installed Boost library>
-   ```
-
-1. Configuring the build settings for the application solution
-
-   In case of an application solution build, describe the build process in the `CMakeLists.txt` file. Specify the directory with the application to be built using the `add_subdirectory` function, specify the executable file using the `add_executable` function, and specify the platform libraries to be connected to the project using the `target_link_libraries` function. You can use the following libraries:
-
-   - `neuron_traits`
-   - `synapse_traits`
-   - `core`
-   - `meta`
-   - `devices`
-   - `backends`
-   - `framework`
-
-1. Configuring a platform or an application solution build
-
-   If you are building a platform or an application solution on Linux, configure the build using the CMake build system. For more details on configuring a build using CMake, refer to the <a href="https://cmake.org/documentation/">CMake documentation</a>.\
-   If you are building the platform or application solution in Windows, configure the build in Visual Studio. To do this, open the platform or application project by selecting the required `CMakeLists.txt` file and configure the cache. In case of an application solution build, select the `CMakeLists.txt` file of the application solution. In case of a platform build, select the `CMakeLists.txt` file located in the root directory with the platform source code.\
-   The first build configuration with CMake may take too long to complete and fail with network errors. If network errors occur, please run the build configuration again.
-
-1. Starting the build
-
-   Start the platform or application solution build. For more details on starting the build of projects, refer to the <a href="https://cmake.org/documentation/">CMake documentation</a> or the documentation of the integrated development environment being used.
-
 ## Trademark notices
 
 Registered trademarks and service marks are the property of their respective owners.
@@ -307,6 +113,5 @@ This is an open source project. If you are interested in making a code contribut
 
 ## License
 
-Copyright © 2024 AO Kaspersky Lab
+Copyright © 2025 AO Kaspersky Lab
 Licensed under the Apache 2.0 License. See the `LICENSE.txt` file in the root directory for details.
-.

azure-pipelines.yml

@@ -0,0 +1,95 @@
+# Starter pipeline
+# Start with a minimal pipeline that you can customize to build and deploy your code.
+# Add steps that build, run tests, deploy, and more:
+# https://aka.ms/yaml
+
+trigger:
+- master
+
+pool:
+  name: FT-SNN
+  demands: Agent.OS -equals Linux
+
+steps:
+- script: |
+   echo Set rebase
+   
+   git config pull.rebase true
+   
+   git remote add tfs -m master "https://hqrndtfs.avp.ru/tfs/DefaultCollection/FT-SNN/_git/knp_from_gh"
+   git remote add github  "git@github.com:KasperskyLab/knp.git"
+   
+   git config user.name "FT-SNN Build Service"
+   git config user.email "git@avp.ru"
+   
+   git remote -v
+  displayName: 'Change git settings'
+
+- script: 'git -c http.extraheader="AUTHORIZATION: bearer $(System.AccessToken)" fetch tfs master'
+  displayName: 'Fetch changes from the local TFS'
+
+- script: 'git merge tfs/master --allow-unrelated-histories'
+  displayName: 'Merge local changes from TFS'
+
+#- script: |
+#   pip3 install -r requirements.txt --break-system-packages
+#   git config --global http.version HTTP/1.1
+#  displayName: 'Setup additional requirements and configuration hacks'
+#  enabled: false
+
+# - task: CMake@1
+#   displayName: 'CMake GCC Configuration'
+#   inputs:
+#     workingDirectory: '$(Build.SourcesDirectory)'
+#     cmakeArgs: '-DBoost_ROOT=/usr/local/boost/1.84.0/ -DKNP_BUILD_TESTS=ON -DCMAKE_INSTALL_PREFIX="install" -DKNP_BUILD_DOCUMENTATION=ON -DKNP_ENABLE_COVERAGE=ON -DKNP_PYTHON_BUILD_WHEEL=ON -DCMAKE_C_COMPILER=gcc -DCMAKE_CXX_COMPILER=g++ -DCMAKE_BUILD_TYPE=Debug -B $(Build.BinariesDirectory) -S $(Build.SourcesDirectory)'
+#   enabled: false
+
+# - task: CMake@1
+#   displayName: 'GCC Build'
+#   inputs:
+#     cmakeArgs: '--build $(Build.BinariesDirectory) --parallel --clean-first'
+#   enabled: false
+
+# - script: 'ctest -V --output-junit linux_tests_result.xml'
+#   workingDirectory: '$(Build.BinariesDirectory)/knp/tests'
+#   failOnStderr: true
+#   displayName: 'CTest tests'
+#   enabled: false
+
+# - task: PublishTestResults@2
+#   displayName: 'Publish Test Results'
+#   inputs:
+#     testResultsFiles: '$(Build.BinariesDirectory)/knp/tests/linux_tests_result.xml'
+#   enabled: false
+
+# - task: ArchiveFiles@2
+#   displayName: 'Archive auto-generated documentation'
+#   inputs:
+#     rootFolderOrFile: '$(Build.BinariesDirectory)/doc_doxygen'
+#     archiveType: 7z
+#     sevenZipCompression: maximum
+#     archiveFile: '$(Build.ArtifactStagingDirectory)/$(Build.BuildId)_doc.7z'
+#   enabled: false
+
+# - task: DownloadSecureFile@1
+#   displayName: 'Download Titan1 SSH key'
+#   inputs:
+#     secureFile: 'titan1_service_id_rsa'
+
+# - script: |
+#    chmod 0600 $(ssh_private_key.secureFilePath) && \
+#    ssh -o StrictHostKeyChecking=no -i $(ssh_private_key.secureFilePath) svc_ft_publisher@titan1.avp.ru "mkdir -p /data/knp2/$(Build.BuildId)/" && \
+#    scp -r -o StrictHostKeyChecking=no -i $(ssh_private_key.secureFilePath) $(Build.BuildId)_doc.7z svc_ft_publisher@titan1.avp.ru:/data/knp2/$(Build.BuildId)/
+#   workingDirectory: '$(Build.ArtifactStagingDirectory)'
+#   displayName: 'Publish build to the Titan1 via SSH'
+#   enabled: false
+
+- task: DownloadSecureFile@1
+  displayName: 'Download Github deploy key'
+  inputs:
+    secureFile: 'github_deploy_key'
+
+- script: 
+   chmod 0600 $(github_deploy_key.secureFilePath) && \
+   GIT_SSH_COMMAND="ssh -o StrictHostKeyChecking=no -i $(github_deploy_key.secureFilePath)" git push -u github --all
+  displayName: 'Push to Github'

examples/mnist-client/README.md

@@ -87,7 +87,7 @@ The `visualize_network.cpp` program file contains implementations of the followi
 * `draw_annotated_subgraph` function that draws a network graph with inscriptions for node names or IDs.
 * `draw_subgraph` function that draws a connected subgraph.
 * `make_reverse_list` function that creates a reverse adjacency list where each node has a list of nodes to which it is adjacent.
-* `find_connected_set` function that fins an independent subgraph inside a network graph.
+* `find_connected_set` function that finds an independent subgraph inside a network graph.
 * `divide_graph_by_connectivity` function defined in the `visualize_network.h` file.
 * `print_connected_subset` function that prints the description of a network subgraph.
 * `print_network_description` function defined in the `visualize_network.h` file.
@@ -138,12 +138,9 @@ If you install the `knp-examples` package, the example binary file is located in
 
 `$ mnist-client`
 
-You can also build the example by using CMake. The example binary file will be located in the `/build/bin` directory. To execute the created binary file, run the following commands:
+You can also build the example by using CMake. The example binary file will be located in the `build/bin` directory. To execute the created binary file, run the following commands:
 
-```
-$ cd /build/bin
-$ mnist-client
-```
+`$ build/bin/mnist-client`
 
 
 # Information about third-party code