{
    "info": {
        "author": "Ravindra Marella",
        "author_email": "mv.ravindra007@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 1 - Planning",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "A framework for quickly creating machine learning models using Estimator API of TensorFlow.\n\n<!-- TOC depthFrom:2 depthTo:3 withLinks:1 updateOnSave:1 orderedList:0 -->\n\n- [Installation](#installation)\n- [Getting Started](#getting-started)\n\t- [Example: CNN MNIST Classifier](#example-cnn-mnist-classifier)\n\t- [Model Function](#model-function)\n- [License](#license)\n\n<!-- /TOC -->\n\n\n## Installation\n\n[Install TensorFlow]:\n\n```sh\npip install tensorflow\n```\n\nand run:\n\n```sh\npip install estimator\n```\n\nIt is recommended to use a [virtual environment].\n\n\n## Getting Started\n\n```py\nfrom estimator import Model\nimport tensorflow as tf\n\n# Define the network architecture - layers, number of units, activations etc.\ndef network(inputs):\n    hidden = tf.layers.Dense(units=64, activation=tf.nn.relu)(inputs)\n    outputs = tf.layers.Dense(units=10)(hidden)\n    return outputs\n\n# Configure the learning process - loss, optimizer, evaluation metrics etc.\nmodel = Model(network,\n              loss='sparse_softmax_cross_entropy',\n              optimizer=('GradientDescent', 0.001),\n              metrics=['accuracy'])\n\n# Train the model using training data\nmodel.train(x_train, y_train, epochs=30, batch_size=128)\n\n# Evaluate the model performance on test or validation data\nloss_and_metrics = model.evaluate(x_test, y_test)\n\n# Use the model to make predictions for new data\npredictions = model.predict(x)\n# or call the model directly\npredictions = model(x)\n```\n\nMore configuration options are available:\n\n```py\nmodel = Model(network,\n              loss='sparse_softmax_cross_entropy',\n              optimizer=optimizer('GradientDescent', 0.001),\n              metrics=['accuracy'],\n              model_dir='/tmp/my_model')\n```\n\nYou can also use custom functions for loss and metrics:\n\n```py\ndef custom_loss(labels, outputs):\n    pass\n\ndef custom_metric(labels, outputs):\n    pass\n\nmodel = Model(network,\n              loss=custom_loss,\n              optimizer=('GradientDescent', 0.001),\n              metrics=['accuracy', custom_metric])\n```\n\n### Example: CNN MNIST Classifier\n\nThis example is based on the [MNIST example] of TensorFlow:\n\n```py\nfrom estimator import Model, GradientDescent, TRAIN\nimport tensorflow as tf\n\ndef network(x, mode):\n    x = tf.reshape(x, [-1, 28, 28, 1])\n    x = tf.layers.Conv2D(filters=32, kernel_size=[5, 5], padding='same', activation=tf.nn.relu)(x)\n    x = tf.layers.MaxPooling2D(pool_size=[2, 2], strides=2)(x)\n    x = tf.layers.Conv2D(filters=64, kernel_size=[5, 5], padding='same', activation=tf.nn.relu)(x)\n    x = tf.layers.MaxPooling2D(pool_size=[2, 2], strides=2)(x)\n    x = tf.layers.Flatten()(x)\n    x = tf.layers.Dense(units=1024, activation=tf.nn.relu)(x)\n    x = tf.layers.Dropout(rate=0.4)(x, training=mode == TRAIN)\n    x = tf.layers.Dense(units=10)(x)\n    return x\n\n# Configure the learning process\nmodel = Model(network,\n              loss='sparse_softmax_cross_entropy',\n              optimizer=('GradientDescent', 0.001))\n```\n\n`mode` parameter specifies whether the model is used for training, evaluation or prediction.\n\n### Model Function\n\nTo have more control, you may configure the model inside a function using `Estimator` class:\n\n```py\nfrom estimator import Estimator, PREDICT\nimport tensorflow as tf\n\ndef model(features, labels, mode):\n    # Define the network architecture\n    hidden = tf.layers.Dense(units=64, activation=tf.nn.relu)(features)\n    outputs = tf.layers.Dense(units=10)(hidden)\n    predictions = tf.argmax(outputs, axis=1)\n    # In prediction mode, simply return predictions without configuring learning process\n    if mode == PREDICT:\n        return predictions\n\n    # Configure the learning process for training and evaluation modes\n    loss = tf.losses.sparse_softmax_cross_entropy(labels, outputs)\n    optimizer = tf.train.GradientDescentOptimizer(0.001)\n    accuracy = tf.metrics.accuracy(labels, predictions)\n    return dict(loss=loss,\n                optimizer=optimizer,\n                metrics={'accuracy': accuracy})\n\n# Create the model using model function\nmodel = Estimator(model)\n\n# Train the model\nmodel.train(x_train, y_train, epochs=30, batch_size=128)\n```\n\n\n## License\n\n[MIT][license]\n\n\n[license]: /LICENSE\n[virtual environment]: https://docs.python.org/3/library/venv.html\n[MNIST example]: https://www.tensorflow.org/tutorials/layers#building_the_cnn_mnist_classifier\n[Install TensorFlow]: https://www.tensorflow.org/install/",
        "description_content_type": "text/markdown",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/AppliedDeepLearning/estimator",
        "keywords": "estimator tensorflow neural-network deep-learning machine-learning",
        "license": "MIT",
        "maintainer": "",
        "maintainer_email": "",
        "name": "estimator",
        "package_url": "https://pypi.org/project/estimator/",
        "platform": "",
        "project_url": "https://pypi.org/project/estimator/",
        "project_urls": {
            "Homepage": "https://github.com/AppliedDeepLearning/estimator"
        },
        "release_url": "https://pypi.org/project/estimator/0.0.10/",
        "requires_dist": null,
        "requires_python": "",
        "summary": "A framework for quickly creating machine learning models using Estimator API of TensorFlow.",
        "version": "0.0.10"
    },
    "last_serial": 3850385,
    "releases": {
        "0.0.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "207e16bb7744e1240dce49d860d1570c",
                    "sha256": "017a55d841c103f88abbea8d49d7180c60f4818f097c6c0753b344c205f7d377"
                },
                "downloads": -1,
                "filename": "estimator-0.0.0.tar.gz",
                "has_sig": false,
                "md5_digest": "207e16bb7744e1240dce49d860d1570c",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 4913,
                "upload_time": "2018-04-17T21:29:24",
                "url": "https://files.pythonhosted.org/packages/04/4b/da24b46e543f0d799fd02c7c2c393a87fdcd04100e114cbb875f275eebb0/estimator-0.0.0.tar.gz"
            }
        ],
        "0.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "323d2d52945519c20ba56fc27792fb93",
                    "sha256": "9456adf35a9553773764eb3ac2337c4269fa12aa22979f2d90bc55ff922f3c4f"
                },
                "downloads": -1,
                "filename": "estimator-0.0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "323d2d52945519c20ba56fc27792fb93",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 4915,
                "upload_time": "2018-04-17T21:57:19",
                "url": "https://files.pythonhosted.org/packages/51/39/db87f2105bc1df8180a2db0e2205ea9efb99e83a75da374f87ed94b6744d/estimator-0.0.1.tar.gz"
            }
        ],
        "0.0.10": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "2cd6e15127ee705f01ccf2188c0b9b52",
                    "sha256": "aefd7d76940d283deefee1497f15487cd0521463e33f2f4c05507883af834bd6"
                },
                "downloads": -1,
                "filename": "estimator-0.0.10.tar.gz",
                "has_sig": false,
                "md5_digest": "2cd6e15127ee705f01ccf2188c0b9b52",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 6054,
                "upload_time": "2018-05-10T12:42:06",
                "url": "https://files.pythonhosted.org/packages/c3/d2/62b223dc958401a6a7245c09dfe3975118f12798c1238ab9542ccb2e0e13/estimator-0.0.10.tar.gz"
            }
        ],
        "0.0.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "b4a0228c63bb707f7d47ad05d99d0185",
                    "sha256": "984c95512a473ec71f016cd6629fbe989dcdbb335851f36a2e7c6292372ea61b"
                },
                "downloads": -1,
                "filename": "estimator-0.0.2.tar.gz",
                "has_sig": false,
                "md5_digest": "b4a0228c63bb707f7d47ad05d99d0185",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5242,
                "upload_time": "2018-04-18T18:04:09",
                "url": "https://files.pythonhosted.org/packages/ab/ad/8c32f38fe35036146b94cdff206c0df101f075372b80b7bd30e4419f01bb/estimator-0.0.2.tar.gz"
            }
        ],
        "0.0.3": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "a2d4a9c000ce3129dc16fc8a10bd60a5",
                    "sha256": "0495c0764346913415ddcb070c4a1ed9d5b41332c327615114d181a782203dc9"
                },
                "downloads": -1,
                "filename": "estimator-0.0.3.tar.gz",
                "has_sig": false,
                "md5_digest": "a2d4a9c000ce3129dc16fc8a10bd60a5",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5258,
                "upload_time": "2018-04-30T17:33:10",
                "url": "https://files.pythonhosted.org/packages/db/b2/346c9950f59da8a52752ec34b317c8e4e26df13189006dcb8e40e8face20/estimator-0.0.3.tar.gz"
            }
        ],
        "0.0.4": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "d52c47adc4383c6762995730cbbd2824",
                    "sha256": "b30850efd1295db95dfc9f60c4af947252473de64849c5f849b22969e0bb07dd"
                },
                "downloads": -1,
                "filename": "estimator-0.0.4.tar.gz",
                "has_sig": false,
                "md5_digest": "d52c47adc4383c6762995730cbbd2824",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5265,
                "upload_time": "2018-05-07T08:25:58",
                "url": "https://files.pythonhosted.org/packages/a6/d6/d14246fd85a718bce79982b03017637367b85419f69d02e1b9f37232052b/estimator-0.0.4.tar.gz"
            }
        ],
        "0.0.5": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "d8421c7ddacc9182109c48ccb74f1df6",
                    "sha256": "7a3d162c2176399bf4d1f7d598feedb797d43ea9c98a607ced5a8549a1a81991"
                },
                "downloads": -1,
                "filename": "estimator-0.0.5.tar.gz",
                "has_sig": false,
                "md5_digest": "d8421c7ddacc9182109c48ccb74f1df6",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5854,
                "upload_time": "2018-05-07T16:43:54",
                "url": "https://files.pythonhosted.org/packages/95/05/31af274c23544f257da0c7e26830682b821d63d21dc838c0e06f01708f4b/estimator-0.0.5.tar.gz"
            }
        ],
        "0.0.6": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "9cc9518f342f27ed5fe2882fdf03b94b",
                    "sha256": "2822e5e3200694a313c486023a6adb1e043c65ebd60836157e9436bbdd77720a"
                },
                "downloads": -1,
                "filename": "estimator-0.0.6.tar.gz",
                "has_sig": false,
                "md5_digest": "9cc9518f342f27ed5fe2882fdf03b94b",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5875,
                "upload_time": "2018-05-08T16:25:57",
                "url": "https://files.pythonhosted.org/packages/64/f2/62cbf66cc6d485c6d89e47c42f8148e6fc1178d86e5b870491ca0f467448/estimator-0.0.6.tar.gz"
            }
        ],
        "0.0.7": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "6431c2d24a0813cbf3b898cf1ca71cc3",
                    "sha256": "4a5a6f032e0cec93bfd1bb2fe4c3305327bf321c5b4fef88f85f4c7f7c588065"
                },
                "downloads": -1,
                "filename": "estimator-0.0.7.tar.gz",
                "has_sig": false,
                "md5_digest": "6431c2d24a0813cbf3b898cf1ca71cc3",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5888,
                "upload_time": "2018-05-08T18:34:11",
                "url": "https://files.pythonhosted.org/packages/84/9f/5c9456b1c10bd0a246533787ebdad15366228d5156effe93e25c6ead1934/estimator-0.0.7.tar.gz"
            }
        ],
        "0.0.8": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "5a395839cb9ad0530e1f7cd4080dfd7b",
                    "sha256": "9115f2f23d50f537967e106b1e4d8f36ef3461cf516e095ff4fbb05d30afe9d7"
                },
                "downloads": -1,
                "filename": "estimator-0.0.8.tar.gz",
                "has_sig": false,
                "md5_digest": "5a395839cb9ad0530e1f7cd4080dfd7b",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5942,
                "upload_time": "2018-05-09T08:24:16",
                "url": "https://files.pythonhosted.org/packages/3e/1d/771d55afa33b046f7f4abd48b91eaf9d105939ca9741349f9d937ea37a36/estimator-0.0.8.tar.gz"
            }
        ],
        "0.0.9": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "aa437f4e1711cf4351da023187c6fea8",
                    "sha256": "0a550cdf62d23eab40d0f331687d74658a193509a70b9246979b9f08255e8093"
                },
                "downloads": -1,
                "filename": "estimator-0.0.9.tar.gz",
                "has_sig": false,
                "md5_digest": "aa437f4e1711cf4351da023187c6fea8",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 6016,
                "upload_time": "2018-05-10T07:24:26",
                "url": "https://files.pythonhosted.org/packages/f2/e3/7dea22d6cdae91acb1d82cacd1304259e9302307c162061e2eeffbf40a27/estimator-0.0.9.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "2cd6e15127ee705f01ccf2188c0b9b52",
                "sha256": "aefd7d76940d283deefee1497f15487cd0521463e33f2f4c05507883af834bd6"
            },
            "downloads": -1,
            "filename": "estimator-0.0.10.tar.gz",
            "has_sig": false,
            "md5_digest": "2cd6e15127ee705f01ccf2188c0b9b52",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 6054,
            "upload_time": "2018-05-10T12:42:06",
            "url": "https://files.pythonhosted.org/packages/c3/d2/62b223dc958401a6a7245c09dfe3975118f12798c1238ab9542ccb2e0e13/estimator-0.0.10.tar.gz"
        }
    ]
}