mirror of
https://github.com/deepfakes/faceswap
synced 2025-06-07 10:43:27 -04:00
* model_refactor (#571) * original model to new structure * IAE model to new structure * OriginalHiRes to new structure * Fix trainer for different resolutions * Initial config implementation * Configparse library added * improved training data loader * dfaker model working * Add logging to training functions * Non blocking input for cli training * Add error handling to threads. Add non-mp queues to queue_handler * Improved Model Building and NNMeta * refactor lib/models * training refactor. DFL H128 model Implementation * Dfaker - use hashes * Move timelapse. Remove perceptual loss arg * Update INSTALL.md. Add logger formatting. Update Dfaker training * DFL h128 partially ported * Add mask to dfaker (#573) * Remove old models. Add mask to dfaker * dfl mask. Make masks selectable in config (#575) * DFL H128 Mask. Mask type selectable in config. * remove gan_v2_2 * Creating Input Size config for models Creating Input Size config for models Will be used downstream in converters. Also name change of image_shape to input_shape to clarify ( for future models with potentially different output_shapes) * Add mask loss options to config * MTCNN options to config.ini. Remove GAN config. Update USAGE.md * Add sliders for numerical values in GUI * Add config plugins menu to gui. Validate config * Only backup model if loss has dropped. Get training working again * bugfixes * Standardise loss printing * GUI idle cpu fixes. Graph loss fix. * mutli-gpu logging bugfix * Merge branch 'staging' into train_refactor * backup state file * Crash protection: Only backup if both total losses have dropped * Port OriginalHiRes_RC4 to train_refactor (OriginalHiRes) * Load and save model structure with weights * Slight code update * Improve config loader. Add subpixel opt to all models. Config to state * Show samples... wrong input * Remove AE topology. Add input/output shapes to State * Port original_villain (birb/VillainGuy) model to faceswap * Add plugin info to GUI config pages * Load input shape from state. IAE Config options. * Fix transform_kwargs. Coverage to ratio. Bugfix mask detection * Suppress keras userwarnings. Automate zoom. Coverage_ratio to model def. * Consolidation of converters & refactor (#574) * Consolidation of converters & refactor Initial Upload of alpha Items - consolidate convert_mased & convert_adjust into one converter -add average color adjust to convert_masked -allow mask transition blur size to be a fixed integer of pixels and a fraction of the facial mask size -allow erosion/dilation size to be a fixed integer of pixels and a fraction of the facial mask size -eliminate redundant type conversions to avoid multiple round-off errors -refactor loops for vectorization/speed -reorganize for clarity & style changes TODO - bug/issues with warping the new face onto a transparent old image...use a cleanup mask for now - issues with mask border giving black ring at zero erosion .. investigate - remove GAN ?? - test enlargment factors of umeyama standard face .. match to coverage factor - make enlargment factor a model parameter - remove convert_adjusted and referencing code when finished * Update Convert_Masked.py default blur size of 2 to match original... description of enlargement tests breakout matrxi scaling into def * Enlargment scale as a cli parameter * Update cli.py * dynamic interpolation algorithm Compute x & y scale factors from the affine matrix on the fly by QR decomp. Choose interpolation alogrithm for the affine warp based on an upsample or downsample for each image * input size input size from config * fix issues with <1.0 erosion * Update convert.py * Update Convert_Adjust.py more work on the way to merginf * Clean up help note on sharpen * cleanup seamless * Delete Convert_Adjust.py * Update umeyama.py * Update training_data.py * swapping * segmentation stub * changes to convert.str * Update masked.py * Backwards compatibility fix for models Get converter running * Convert: Move masks to class. bugfix blur_size some linting * mask fix * convert fixes - missing facehull_rect re-added - coverage to % - corrected coverage logic - cleanup of gui option ordering * Update cli.py * default for blur * Update masked.py * added preliminary low_mem version of OriginalHighRes model plugin * Code cleanup, minor fixes * Update masked.py * Update masked.py * Add dfl mask to convert * histogram fix & seamless location * update * revert * bugfix: Load actual configuration in gui * Standardize nn_blocks * Update cli.py * Minor code amends * Fix Original HiRes model * Add masks to preview output for mask trainers refactor trainer.__base.py * Masked trainers converter support * convert bugfix * Bugfix: Converter for masked (dfl/dfaker) trainers * Additional Losses (#592) * initial upload * Delete blur.py * default initializer = He instead of Glorot (#588) * Allow kernel_initializer to be overridable * Add ICNR Initializer option for upscale on all models. * Hopefully fixes RSoDs with original-highres model plugin * remove debug line * Original-HighRes model plugin Red Screen of Death fix, take #2 * Move global options to _base. Rename Villain model * clipnorm and res block biases * scale the end of res block * res block * dfaker pre-activation res * OHRES pre-activation * villain pre-activation * tabs/space in nn_blocks * fix for histogram with mask all set to zero * fix to prevent two networks with same name * GUI: Wider tooltips. Improve TQDM capture * Fix regex bug * Convert padding=48 to ratio of image size * Add size option to alignments tool extract * Pass through training image size to convert from model * Convert: Pull training coverage from model * convert: coverage, blur and erode to percent * simplify matrix scaling * ordering of sliders in train * Add matrix scaling to utils. Use interpolation in lib.aligner transform * masked.py Import get_matrix_scaling from utils * fix circular import * Update masked.py * quick fix for matrix scaling * testing thus for now * tqdm regex capture bugfix * Minor ammends * blur size cleanup * Remove coverage option from convert (Now cascades from model) * Implement convert for all model types * Add mask option and coverage option to all existing models * bugfix for model loading on convert * debug print removal * Bugfix for masks in dfl_h128 and iae * Update preview display. Add preview scaling to cli * mask notes * Delete training_data_v2.py errant file * training data variables * Fix timelapse function * Add new config items to state file for legacy purposes * Slight GUI tweak * Raise exception if problem with loaded model * Add Tensorboard support (Logs stored in model directory) * ICNR fix * loss bugfix * convert bugfix * Move ini files to config folder. Make TensorBoard optional * Fix training data for unbalanced inputs/outputs * Fix config "none" test * Keep helptext in .ini files when saving config from GUI * Remove frame_dims from alignments * Add no-flip and warp-to-landmarks cli options * Revert OHR to RC4_fix version * Fix lowmem mode on OHR model * padding to variable * Save models in parallel threads * Speed-up of res_block stability * Automated Reflection Padding * Reflect Padding as a training option Includes auto-calculation of proper padding shapes, input_shapes, output_shapes Flag included in config now * rest of reflect padding * Move TB logging to cli. Session info to state file * Add session iterations to state file * Add recent files to menu. GUI code tidy up * [GUI] Fix recent file list update issue * Add correct loss names to TensorBoard logs * Update live graph to use TensorBoard and remove animation * Fix analysis tab. GUI optimizations * Analysis Graph popup to Tensorboard Logs * [GUI] Bug fix for graphing for models with hypens in name * [GUI] Correctly split loss to tabs during training * [GUI] Add loss type selection to analysis graph * Fix store command name in recent files. Switch to correct tab on open * [GUI] Disable training graph when 'no-logs' is selected * Fix graphing race condition * rename original_hires model to unbalanced
301 lines
13 KiB
Python
301 lines
13 KiB
Python
#!/usr/bin/env python3
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""" Default configurations for faceswap
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Extends out configparser funcionality
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by checking for default config updates
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and returning data in it's correct format """
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import logging
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import os
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import sys
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from collections import OrderedDict
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from configparser import ConfigParser
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logger = logging.getLogger(__name__) # pylint: disable=invalid-name
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class FaceswapConfig():
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""" Config Items """
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def __init__(self, section):
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""" Init Configuration """
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logger.debug("Initializing: %s", self.__class__.__name__)
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self.configfile = self.get_config_file()
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self.config = ConfigParser(allow_no_value=True)
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self.defaults = OrderedDict()
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self.config.optionxform = str
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self.section = section
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self.set_defaults()
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self.handle_config()
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logger.debug("Initialized: %s", self.__class__.__name__)
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def set_defaults(self):
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""" Override for plugin specific config defaults
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Should be a series of self.add_section() and self.add_item() calls
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e.g:
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section = "sect_1"
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self.add_section(title=section,
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info="Section 1 Information")
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self.add_item(section=section,
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title="option_1",
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datatype=bool,
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default=False,
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info="sect_1 option_1 information")
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"""
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raise NotImplementedError
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@property
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def config_dict(self):
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""" Collate global options and requested section into a dictionary
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with the correct datatypes """
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conf = dict()
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for sect in ("global", self.section):
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if sect not in self.config.sections():
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continue
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for key in self.config[sect]:
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if key.startswith(("#", "\n")): # Skip comments
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continue
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conf[key] = self.get(sect, key)
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return conf
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def get(self, section, option):
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""" Return a config item in it's correct format """
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logger.debug("Getting config item: (section: '%s', option: '%s')", section, option)
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datatype = self.defaults[section][option]["type"]
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if datatype == bool:
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func = self.config.getboolean
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elif datatype == int:
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func = self.config.getint
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elif datatype == float:
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func = self.config.getfloat
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else:
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func = self.config.get
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retval = func(section, option)
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if isinstance(retval, str) and retval.lower() == "none":
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retval = None
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logger.debug("Returning item: (type: %s, value: %s)", datatype, retval)
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return retval
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def get_config_file(self):
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""" Return the config file from the calling folder """
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dirname = os.path.dirname(sys.modules[self.__module__].__file__)
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folder, fname = os.path.split(dirname)
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retval = os.path.join(os.path.dirname(folder), "config", "{}.ini".format(fname))
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logger.debug("Config File location: '%s'", retval)
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return retval
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def add_section(self, title=None, info=None):
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""" Add a default section to config file """
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logger.debug("Add section: (title: '%s', info: '%s')", title, info)
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if None in (title, info):
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raise ValueError("Default config sections must have a title and "
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"information text")
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self.defaults[title] = OrderedDict()
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self.defaults[title]["helptext"] = info
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def add_item(self, section=None, title=None, datatype=str,
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default=None, info=None, rounding=None, min_max=None, choices=None):
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""" Add a default item to a config section
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For int or float values, rounding and min_max must be set
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This is for the slider in the GUI. The min/max values are not enforced:
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rounding: sets the decimal places for floats or the step interval for ints.
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min_max: tuple of min and max accepted values
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For str values choices can be set to validate input and create a combo box
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in the GUI
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"""
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logger.debug("Add item: (section: '%s', title: '%s', datatype: '%s', default: '%s', "
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"info: '%s', rounding: '%s', min_max: %s, choices: %s)",
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section, title, datatype, default, info, rounding, min_max, choices)
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choices = list() if not choices else choices
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if None in (section, title, default, info):
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raise ValueError("Default config items must have a section, "
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"title, defult and "
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"information text")
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if not self.defaults.get(section, None):
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raise ValueError("Section does not exist: {}".format(section))
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if datatype not in (str, bool, float, int):
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raise ValueError("'datatype' must be one of str, bool, float or "
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"int: {} - {}".format(section, title))
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if datatype in (float, int) and (rounding is None or min_max is None):
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raise ValueError("'rounding' and 'min_max' must be set for numerical options")
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if not isinstance(choices, (list, tuple)):
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raise ValueError("'choices' must be a list or tuple")
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self.defaults[section][title] = {"default": default,
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"helptext": info,
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"type": datatype,
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"rounding": rounding,
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"min_max": min_max,
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"choices": choices}
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def check_exists(self):
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""" Check that a config file exists """
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if not os.path.isfile(self.configfile):
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logger.debug("Config file does not exist: '%s'", self.configfile)
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return False
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logger.debug("Config file exists: '%s'", self.configfile)
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return True
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def create_default(self):
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""" Generate a default config if it does not exist """
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logger.debug("Creating default Config")
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for section, items in self.defaults.items():
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logger.debug("Adding section: '%s')", section)
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self.insert_config_section(section, items["helptext"])
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for item, opt in items.items():
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logger.debug("Adding option: (item: '%s', opt: '%s'", item, opt)
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if item == "helptext":
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continue
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self.insert_config_item(section,
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item,
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opt["default"],
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opt)
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self.save_config()
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def insert_config_section(self, section, helptext, config=None):
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""" Insert a section into the config """
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logger.debug("Inserting section: (section: '%s', helptext: '%s', config: '%s')",
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section, helptext, config)
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config = self.config if config is None else config
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helptext = self.format_help(helptext, is_section=True)
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config.add_section(section)
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config.set(section, helptext)
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logger.debug("Inserted section: '%s'", section)
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def insert_config_item(self, section, item, default, option,
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config=None):
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""" Insert an item into a config section """
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logger.debug("Inserting item: (section: '%s', item: '%s', default: '%s', helptext: '%s', "
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"config: '%s')", section, item, default, option["helptext"], config)
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config = self.config if config is None else config
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helptext = option["helptext"]
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helptext += self.set_helptext_choices(option)
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helptext += "\n[Default: {}]".format(default)
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helptext = self.format_help(helptext, is_section=False)
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config.set(section, helptext)
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config.set(section, item, str(default))
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logger.debug("Inserted item: '%s'", item)
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@staticmethod
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def set_helptext_choices(option):
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""" Set the helptext choices """
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choices = ""
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if option["choices"]:
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choices = "\nChoose from: {}".format(option["choices"])
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elif option["type"] == bool:
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choices = "\nChoose from: True, False"
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elif option["type"] == int:
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cmin, cmax = option["min_max"]
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choices = "\nSelect an integer between {} and {}".format(cmin, cmax)
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elif option["type"] == float:
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cmin, cmax = option["min_max"]
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choices = "\nSelect a decimal number between {} and {}".format(cmin, cmax)
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return choices
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@staticmethod
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def format_help(helptext, is_section=False):
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""" Format comments for default ini file """
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logger.debug("Formatting help: (helptext: '%s', is_section: '%s')", helptext, is_section)
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helptext = '# {}'.format(helptext.replace("\n", "\n# "))
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if is_section:
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helptext = helptext.upper()
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else:
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helptext = "\n{}".format(helptext)
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logger.debug("formatted help: '%s'", helptext)
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return helptext
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def load_config(self):
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""" Load values from config """
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logger.info("Loading config: '%s'", self.configfile)
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self.config.read(self.configfile)
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def save_config(self):
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""" Save a config file """
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logger.info("Updating config at: '%s'", self.configfile)
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f_cfgfile = open(self.configfile, "w")
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self.config.write(f_cfgfile)
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f_cfgfile.close()
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def validate_config(self):
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""" Check for options in default config against saved config
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and add/remove as appropriate """
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logger.debug("Validating config")
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if self.check_config_change():
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self.add_new_config_items()
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self.check_config_choices()
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logger.debug("Validated config")
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def add_new_config_items(self):
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""" Add new items to the config file """
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logger.debug("Updating config")
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new_config = ConfigParser(allow_no_value=True)
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for section, items in self.defaults.items():
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self.insert_config_section(section, items["helptext"], new_config)
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for item, opt in items.items():
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if item == "helptext":
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continue
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if section not in self.config.sections():
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logger.debug("Adding new config section: '%s'", section)
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opt_value = opt["default"]
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else:
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opt_value = self.config[section].get(item, opt["default"])
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self.insert_config_item(section,
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item,
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opt_value,
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opt,
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new_config)
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self.config = new_config
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self.config.optionxform = str
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self.save_config()
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logger.debug("Updated config")
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def check_config_choices(self):
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""" Check that config items are valid choices """
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logger.debug("Checking config choices")
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for section, items in self.defaults.items():
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for item, opt in items.items():
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if item == "helptext" or not opt["choices"]:
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continue
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opt_value = self.config.get(section, item)
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if opt_value.lower() == "none" and any(choice.lower() == "none"
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for choice in opt["choices"]):
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continue
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if opt_value not in opt["choices"]:
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default = str(opt["default"])
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logger.warning("'%s' is not a valid config choice for '%s': '%s'. Defaulting "
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"to: '%s'", opt_value, section, item, default)
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self.config.set(section, item, default)
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logger.debug("Checked config choices")
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def check_config_change(self):
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""" Check whether new default items have been added or removed
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from the config file compared to saved version """
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if set(self.config.sections()) != set(self.defaults.keys()):
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logger.debug("Default config has new section(s)")
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return True
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for section, items in self.defaults.items():
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opts = [opt for opt in items.keys() if opt != "helptext"]
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exists = [opt for opt in self.config[section].keys()
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if not opt.startswith(("# ", "\n# "))]
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if set(exists) != set(opts):
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logger.debug("Default config has new item(s)")
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return True
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logger.debug("Default config has not changed")
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return False
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def handle_config(self):
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""" Handle the config """
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logger.debug("Handling config")
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if not self.check_exists():
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self.create_default()
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self.load_config()
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self.validate_config()
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logger.debug("Handled config")
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