Metadata-Version: 2.1
Name: tensorflow_model_analysis
Version: 0.12.1
Summary: A library for analyzing TensorFlow models
Home-page: https://www.tensorflow.org/tfx/model_analysis
Author: Google LLC
Author-email: tensorflow-extended-dev@googlegroups.com
License: Apache 2.0
Download-URL: https://pypi.org/project/tensorflow-model-analysis
Description: <!-- See: www.tensorflow.org/tfx/model_analysis/ -->
        
        # TensorFlow Model Analysis
        
        [![Python](https://img.shields.io/pypi/pyversions/tensorflow-model-analysis.svg?style=plastic)](https://github.com/tensorflow/model-analysis)
        [![PyPI](https://badge.fury.io/py/tensorflow-model-analysis.svg)](https://badge.fury.io/py/tensorflow-model-analysis)
        [![Documentation](https://img.shields.io/badge/api-reference-blue.svg)](https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma)
        
        *TensorFlow Model Analysis* (TFMA) is a library for evaluating TensorFlow models.
        It allows users to evaluate their models on large amounts of data in a
        distributed manner, using the same metrics defined in their trainer. These
        metrics can be computed over different slices of data and visualized in Jupyter
        notebooks.
        
        ![TFMA Slicing Metrics Browser](https://raw.githubusercontent.com/tensorflow/model-analysis/master/g3doc/images/tfma-slicing-metrics-browser.gif)
        
        Caution: TFMA may introduce backwards incompatible changes before version 1.0.
        
        ## Installation
        
        The recommended way to install TFMA is using the
        [PyPI package](https://pypi.org/project/tensorflow-model-analysis/):
        
        <pre class="devsite-terminal devsite-click-to-copy">
        pip install tensorflow-model-analysis
        </pre>
        
        Currently, TFMA requires that TensorFlow is installed but does not have an
        explicit dependency on the TensorFlow PyPI package. See the
        [TensorFlow install guides](https://www.tensorflow.org/install/) for instructions.
        
        To enable TFMA visualization in Jupyter Notebook:
        
        <pre class="prettyprint">
          <code class="devsite-terminal">jupyter nbextension enable --py widgetsnbextension</code>
          <code class="devsite-terminal">jupyter nbextension install --py --symlink tensorflow_model_analysis</code>
          <code class="devsite-terminal">jupyter nbextension enable --py tensorflow_model_analysis</code>
        </pre>
        
        Note: If Jupyter notebook is already installed in your home directory, add
        `--user` to these commands. If Jupyter is installed as root, or using a virtual
        environment, the parameter `--sys-prefix` might be required.
        
        ### Dependencies
        
        [Apache Beam](https://beam.apache.org/) is required to run distributed analysis.
        By default, Apache Beam runs in local mode but can also run in distributed mode
        using [Google Cloud Dataflow](https://cloud.google.com/dataflow/). TFMA is
        designed to be extensible for other Apache Beam runners.
        
        ## Getting Started
        
        For instructions on using TFMA, see the [get started
        guide](https://github.com/tensorflow/model-analysis/blob/master/g3doc/get_started.md) and try out
        the extensive [end-to-end example](https://github.com/tensorflow/tfx/blob/master/examples/chicago_taxi/README.md).
        
        ## Compatible Versions
        
        The following table is the TFMA package versions that are compatible with each
        other. This is determined by our testing framework, but other *untested*
        combinations may also work.
        
        |tensorflow-model-analysis  |tensorflow          |apache-beam[gcp]|
        |---------------------------|--------------------|----------------|
        |GitHub master              |1.12                |2.10.0          |
        |0.12.1                     |1.12                |2.10.0          |
        |0.12.0                     |1.12                |2.10.0          |
        |0.11.0                     |1.11                |2.8.0           |
        |0.9.2                      |1.9                 |2.6.0           |
        |0.9.1                      |1.10                |2.6.0           |
        |0.9.0                      |1.9                 |2.5.0           |
        |0.6.0                      |1.6                 |2.4.0           |
        
        ## Questions
        
        Please direct any questions about working with TFMA to
        [Stack Overflow](https://stackoverflow.com) using the
        [tensorflow-model-analysis](https://stackoverflow.com/questions/tagged/tensorflow-model-analysis)
        tag.
        
Keywords: tensorflow model analysis tfx
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 2 :: Only
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=2.7,<3
Description-Content-Type: text/markdown
