tensorflow-cmake | Integrate TensorFlow with CMake projects | Build Tool library
kandi X-RAY | tensorflow-cmake Summary
kandi X-RAY | tensorflow-cmake Summary
tensorflow-cmake is a Shell library typically used in Utilities, Build Tool, Tensorflow, OpenCV applications. tensorflow-cmake has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
Integrate TensorFlow with CMake projects effortlessly
Integrate TensorFlow with CMake projects effortlessly
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Quality
Security
License
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Support
tensorflow-cmake has a low active ecosystem.
It has 312 star(s) with 87 fork(s). There are 23 watchers for this library.
It had no major release in the last 6 months.
There are 25 open issues and 22 have been closed. On average issues are closed in 25 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of tensorflow-cmake is current.
Quality
tensorflow-cmake has 0 bugs and 0 code smells.
Security
tensorflow-cmake has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tensorflow-cmake code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
tensorflow-cmake is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
tensorflow-cmake releases are not available. You will need to build from source code and install.
Installation instructions, examples and code snippets are available.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tensorflow-cmake
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of tensorflow-cmake
tensorflow-cmake Key Features
No Key Features are available at this moment for tensorflow-cmake.
tensorflow-cmake Examples and Code Snippets
No Code Snippets are available at this moment for tensorflow-cmake.
Community Discussions
Trending Discussions on tensorflow-cmake
QUESTION
When running with Bazel, where should I save .pb graphs for Tensorflow?
Asked 2018-Jun-01 at 09:16
Directory structure:
...ANSWER
Answered 2018-Jun-01 at 09:16Silly oversight... I entered the full path. From this:
status = ReadBinaryProto(tf::Env::Default(), "graph.pb", &graph_def);
To this:
status = ReadBinaryProto(tf::Env::Default(), "/home//path/to/graph.pb", &graph_def);
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tensorflow-cmake
Follow the instructions for installing Bazel. Install dependencies and clone TensorFlow from its git repository:.
The TensorFlow runtime library requires both Protobuf and Eigen. However, specific versions are required, and these may clash with currently installed versions of either software. Therefore, two options are provided:. Choose the option that best fits your needs; you may mix these options as well, installing one to /usr/local, while keeping the other confined in the current project. In the following instructions, be sure to replace <EXECUTABLE_NAME> with the name of your executable. Additionally, all generated CMake files should generally be placed in your CMake modules directory, which is commonly <PROJECT_ROOT>/cmake/Modules.
Install the packages to a directory on your computer, which will overwrite / clash with any previous versions installed in that directory (but allow multiple projects to reference them). The default directory is /usr/local, but any may be specified to avoid clashing. This is the recommended option.
Add the packages as external dependencies, allowing CMake to download and build them inside the project directory, not affecting any current versions. This will never result in clashing, but the build process of your project may be lengthened.
If Bazel fails to build the TensorFlow library, stating error: Could not find compiler "gcc" in PATH, you may have to execute the following:.
The TensorFlow runtime library requires both Protobuf and Eigen. However, specific versions are required, and these may clash with currently installed versions of either software. Therefore, two options are provided:. Choose the option that best fits your needs; you may mix these options as well, installing one to /usr/local, while keeping the other confined in the current project. In the following instructions, be sure to replace <EXECUTABLE_NAME> with the name of your executable. Additionally, all generated CMake files should generally be placed in your CMake modules directory, which is commonly <PROJECT_ROOT>/cmake/Modules.
Install the packages to a directory on your computer, which will overwrite / clash with any previous versions installed in that directory (but allow multiple projects to reference them). The default directory is /usr/local, but any may be specified to avoid clashing. This is the recommended option.
Add the packages as external dependencies, allowing CMake to download and build them inside the project directory, not affecting any current versions. This will never result in clashing, but the build process of your project may be lengthened.
If Bazel fails to build the TensorFlow library, stating error: Could not find compiler "gcc" in PATH, you may have to execute the following:.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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