autogen.py

# -*- coding: utf-8 -*-
'''
General documentation architecture:

Home
Index

- Getting started
    Getting started with the sequential model
    Getting started with the functional api
    Examples
    FAQ
    Installation guide

- Models
    About Keras models
        explain when one should use Sequential or functional API
        explain compilation step
        explain weight saving, weight loading
        explain serialization, deserialization
    Sequential
    Model (functional API)

- Layers
    About Keras layers
        explain common layer functions: get_weights, set_weights, get_config
        explain input_shape
        explain usage on non-Keras tensors
    Core layers
    Convolutional
    Recurrent
    Embeddings
    Normalization
    Advanced activations
    Noise

- Preprocessing
    Image preprocessing
    Text preprocessing
    Sequence preprocessing

Objectives
Optimizers
Activations
Callbacks
Datasets
Backend
Initializations
Regularizers
Constraints
Visualization
Scikit-learn API

'''
from __future__ import print_function
from __future__ import unicode_literals

import re
import inspect
import os
import shutil
import sys
if sys.version[0] == '2':
    reload(sys)
    sys.setdefaultencoding('utf8')

from keras.layers import convolutional
from keras.layers import pooling
from keras.layers import local
from keras.layers import recurrent
from keras.layers import core
from keras.layers import noise
from keras.layers import normalization
from keras.layers import advanced_activations
from keras.layers import embeddings
from keras.layers import wrappers
from keras import optimizers
from keras import callbacks
from keras import models
from keras.engine import topology
from keras import objectives
from keras import backend
from keras import constraints
from keras import activations
from keras import regularizers
from keras.utils import io_utils


EXCLUDE = {
    'Optimizer',
    'Wrapper',
    'get_session',
    'set_session',
    'CallbackList',
}

PAGES = [
    {
        'page': 'models/sequential.md',
        'functions': [
            models.Sequential.compile,
            models.Sequential.fit,
            models.Sequential.evaluate,
            models.Sequential.predict,
            models.Sequential.predict_classes,
            models.Sequential.predict_proba,
            models.Sequential.train_on_batch,
            models.Sequential.test_on_batch,
            models.Sequential.predict_on_batch,
            models.Sequential.fit_generator,
            models.Sequential.evaluate_generator,
            models.Sequential.predict_generator,
        ],
    },
    {
        'page': 'models/model.md',
        'functions': [
            models.Model.compile,
            models.Model.fit,
            models.Model.evaluate,
            models.Model.predict,
            models.Model.train_on_batch,
            models.Model.test_on_batch,
            models.Model.predict_on_batch,
            models.Model.fit_generator,
            models.Model.evaluate_generator,
            models.Model.predict_generator,
            models.Model.get_layer,
        ]
    },
    {
        'page': 'layers/core.md',
        'classes': [
            core.Dense,
            core.Activation,
            core.Dropout,
            core.SpatialDropout2D,
            core.SpatialDropout3D,
            core.Flatten,
            core.Reshape,
            core.Permute,
            core.RepeatVector,
            topology.Merge,
            core.Lambda,
            core.ActivityRegularization,
            core.Masking,
            core.Highway,
            core.MaxoutDense,
            core.TimeDistributedDense,
        ],
    },
    {
        'page': 'layers/convolutional.md',
        'classes': [
            convolutional.Convolution1D,
            convolutional.AtrousConvolution1D,
            convolutional.Convolution2D,
            convolutional.AtrousConvolution2D,
            convolutional.SeparableConvolution2D,
            convolutional.Deconvolution2D,
            convolutional.Convolution3D,
            convolutional.Cropping1D,
            convolutional.Cropping2D,
            convolutional.Cropping3D,
            convolutional.UpSampling1D,
            convolutional.UpSampling2D,
            convolutional.UpSampling3D,
            convolutional.ZeroPadding1D,
            convolutional.ZeroPadding2D,
            convolutional.ZeroPadding3D,
        ],
    },
    {
        'page': 'layers/pooling.md',
        'classes': [
            pooling.MaxPooling1D,
            pooling.MaxPooling2D,
            pooling.MaxPooling3D,
            pooling.AveragePooling1D,
            pooling.AveragePooling2D,
            pooling.AveragePooling3D,
            pooling.GlobalMaxPooling1D,
            pooling.GlobalAveragePooling1D,
            pooling.GlobalMaxPooling2D,
            pooling.GlobalAveragePooling2D,
        ],
    },
    {
        'page': 'layers/local.md',
        'classes': [
            local.LocallyConnected1D,
            local.LocallyConnected2D,
        ],
    },
    {
        'page': 'layers/recurrent.md',
        'classes': [
            recurrent.Recurrent,
            recurrent.SimpleRNN,
            recurrent.GRU,
            recurrent.LSTM,
        ],
    },
    {
        'page': 'layers/embeddings.md',
        'classes': [
            embeddings.Embedding,
        ],
    },
    {
        'page': 'layers/normalization.md',
        'classes': [
            normalization.BatchNormalization,
        ],
    },
    {
        'page': 'layers/advanced-activations.md',
        'all_module_classes': [advanced_activations],
    },
    {
        'page': 'layers/noise.md',
        'all_module_classes': [noise],
    },
    {
        'page': 'layers/wrappers.md',
        'all_module_classes': [wrappers],
    },

    {
        'page': 'optimizers.md',
        'all_module_classes': [optimizers],
    },
    {
        'page': 'callbacks.md',
        'all_module_classes': [callbacks],
    },
    {
        'page': 'backend.md',
        'all_module_functions': [backend],
    },
    {
        'page': 'io_utils.md',
        'classes': [
            io_utils.HDF5Matrix
        ],
    },
]

ROOT = 'http://keras.io/'


def get_earliest_class_that_defined_member(member, cls):
    ancestors = get_classes_ancestors([cls])
    result = None
    for ancestor in ancestors:
        if member in dir(ancestor):
            result = ancestor
    if not result:
        return cls
    return result


def get_classes_ancestors(classes):
    ancestors = []
    for cls in classes:
        ancestors += cls.__bases__
    filtered_ancestors = []
    for ancestor in ancestors:
        if ancestor.__name__ in ['object']:
            continue
        filtered_ancestors.append(ancestor)
    if filtered_ancestors:
        return filtered_ancestors + get_classes_ancestors(filtered_ancestors)
    else:
        return filtered_ancestors


def get_function_signature(function, method=True):
    signature = inspect.getargspec(function)
    defaults = signature.defaults
    if method:
        args = signature.args[1:]
    else:
        args = signature.args
    if defaults:
        kwargs = zip(args[-len(defaults):], defaults)
        args = args[:-len(defaults)]
    else:
        kwargs = []
    st = '%s.%s(' % (function.__module__, function.__name__)
    for a in args:
        st += str(a) + ', '
    for a, v in kwargs:
        if type(v) == str:
            v = '\'' + v + '\''
        st += str(a) + '=' + str(v) + ', '
    if kwargs or args:
        return st[:-2] + ')'
    else:
        return st + ')'


def get_class_signature(cls):
    try:
        class_signature = get_function_signature(cls.__init__)
        class_signature = class_signature.replace('__init__', cls.__name__)
    except:
        # in case the class inherits from object and does not
        # define __init__
        class_signature = cls.__module__ + '.' + cls.__name__ + '()'
    return class_signature


def class_to_docs_link(cls):
    module_name = cls.__module__
    assert module_name[:6] == 'keras.'
    module_name = module_name[6:]
    link = ROOT + module_name.replace('.', '/') + '#' + cls.__name__.lower()
    return link


def class_to_source_link(cls):
    module_name = cls.__module__
    assert module_name[:6] == 'keras.'
    path = module_name.replace('.', '/')
    path += '.py'
    line = inspect.getsourcelines(cls)[-1]
    link = 'https://github.com/fchollet/keras/blob/master/' + path + '#L' + str(line)
    return '[[source]](' + link + ')'


def code_snippet(snippet):
    result = '```python\n'
    result += snippet + '\n'
    result += '```\n'
    return result


def process_class_docstring(docstring):
    docstring = re.sub(r'\n    # (.*)\n',
                       r'\n    __\1__\n\n',
                       docstring)

    docstring = re.sub(r'    ([^\s\\]+):(.*)\n',
                       r'    - __\1__:\2\n',
                       docstring)

    docstring = docstring.replace('    ' * 5, '\t\t')
    docstring = docstring.replace('    ' * 3, '\t')
    docstring = docstring.replace('    ', '')
    return docstring


def process_function_docstring(docstring):
    docstring = re.sub(r'\n    # (.*)\n',
                       r'\n    __\1__\n\n',
                       docstring)
    docstring = re.sub(r'\n        # (.*)\n',
                       r'\n        __\1__\n\n',
                       docstring)

    docstring = re.sub(r'    ([^\s\\]+):(.*)\n',
                       r'    - __\1__:\2\n',
                       docstring)

    docstring = docstring.replace('    ' * 6, '\t\t')
    docstring = docstring.replace('    ' * 4, '\t')
    docstring = docstring.replace('    ', '')
    return docstring

print('Cleaning up existing sources directory.')
if os.path.exists('sources'):
    shutil.rmtree('sources')

print('Populating sources directory with templates.')
for subdir, dirs, fnames in os.walk('templates'):
    for fname in fnames:
        new_subdir = subdir.replace('templates', 'sources')
        if not os.path.exists(new_subdir):
            os.makedirs(new_subdir)
        if fname[-3:] == '.md':
            fpath = os.path.join(subdir, fname)
            new_fpath = fpath.replace('templates', 'sources')
            shutil.copy(fpath, new_fpath)

print('Starting autogeneration.')
for page_data in PAGES:
    blocks = []
    classes = page_data.get('classes', [])
    for module in page_data.get('all_module_classes', []):
        module_classes = []
        for name in dir(module):
            if name[0] == '_' or name in EXCLUDE:
                continue
            module_member = getattr(module, name)
            if inspect.isclass(module_member):
                cls = module_member
                if cls.__module__ == module.__name__:
                    if cls not in module_classes:
                        module_classes.append(cls)
        module_classes.sort(key=lambda x: id(x))
        classes += module_classes

    for cls in classes:
        subblocks = []
        signature = get_class_signature(cls)
        subblocks.append('<span style="float:right;">' + class_to_source_link(cls) + '</span>')
        subblocks.append('### ' + cls.__name__ + '\n')
        subblocks.append(code_snippet(signature))
        docstring = cls.__doc__
        if docstring:
            subblocks.append(process_class_docstring(docstring))
        blocks.append('\n'.join(subblocks))

    functions = page_data.get('functions', [])
    for module in page_data.get('all_module_functions', []):
        module_functions = []
        for name in dir(module):
            if name[0] == '_' or name in EXCLUDE:
                continue
            module_member = getattr(module, name)
            if inspect.isfunction(module_member):
                function = module_member
                if module.__name__ in function.__module__:
                    if function not in module_functions:
                        module_functions.append(function)
        module_functions.sort(key=lambda x: id(x))
        functions += module_functions

    for function in functions:
        subblocks = []
        signature = get_function_signature(function, method=False)
        signature = signature.replace(function.__module__ + '.', '')
        subblocks.append('### ' + function.__name__ + '\n')
        subblocks.append(code_snippet(signature))
        docstring = function.__doc__
        if docstring:
            subblocks.append(process_function_docstring(docstring))
            blocks.append('\n\n'.join(subblocks))

    mkdown = '\n----\n\n'.join(blocks)
    # save module page.
    # Either insert content into existing page,
    # or create page otherwise
    page_name = page_data['page']
    path = os.path.join('sources', page_name)
    if os.path.exists(path):
        template = open(path).read()
        assert '{{autogenerated}}' in template, ('Template found for ' + path +
                                                 ' but missing {{autogenerated}} tag.')
        mkdown = template.replace('{{autogenerated}}', mkdown)
        print('...inserting autogenerated content into template:', path)
    else:
        print('...creating new page with autogenerated content:', path)
    subdir = os.path.dirname(path)
    if not os.path.exists(subdir):
        os.makedirs(subdir)
    open(path, 'w').write(mkdown)