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        "author": "Narasimha Prasanna HN",
        "author_email": "narasimhaprasannahn@gmail.com",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "# bzCompute\n\nbzCompute is a computation graph library with built-in support for domain-decomposition and prallel computation. The library can be used for expressing and executing large number of mathematical and text-processing operations using Data-Flow graphs, (Educational version of tensorflow), written in pure python code with numpy support.\n\n### Examples :\nThe educational project supports limited number of text-processing and mathematical operations that are normally used frequently.\n**Look at examples folder for various examples**\n\n### Parallel Computation : \nThe librabry supports both sequential and parallel computation on graphs. Domain Decomposition is the computation technique used to provide task-level parallelism by creating replicas of computation graphs . The library creates a Master-worker setup, where the MasterSession creates specified number of worker sessions, each worker-session is a thread. These threads can be pre-forked to memory or can be created on demand. Each worker is automatically assigned a name. The results are collected. Domain decomposition is manily used for running multiple replicas of data-flow graphs on different inputs, check out *examples*.\n\n### Supported Sessions : \nThe library supports three types of sessions as of now : \n\n  * **SequentialSession** : SequentialSession executes computation graph in a sequential order, leaving parallelism to OS and Hardware.\n  *  **MasterSession** : Creates a master session for parallel computation, can be used for domain-decomposition, by specifying number of worker threads.\n  *  **StringSession** : It is a variant of SequentialSession for executing a computation graph composed of strign operations. \n\n### Supported Operations : \nbzCompute supports many operations as of now, the library also provides support for defining custom operations as per the requirements.\n\n##### Numerical Operations :\nLook at *pyCompute/KernelOperations.py* to obtain list of all supported operations\n\n#### Text-Processing Operations : \nLook at *pyCompute/text_processing/StringOperations.py* for all supported string operations.\n\n\n\n",
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        "name": "pycompute",
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        "summary": "A computation graph library with support for parallelism , numerical and string computations.",
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