def __init__(self, network_class, **overrides): '''Set up an experiment by parsing arguments and building a network. The only input this constructor needs is the Python class of the network to build. Other configuration---for example, creating the appropriate trainer class---typically takes place by parsing command-line argument values, or by a call to train(...). Any keyword arguments provided to the constructor will be used to override values passed on the command line. (Typically this is used to provide experiment-specific default values for command line arguments that have no global defaults, e.g., network architecture.) ''' self.args, self.kwargs = climate.parse_args(**overrides) if 'activation' in self.kwargs: warnings.warn( 'please use --hidden-activation instead of --activation', DeprecationWarning) self.kwargs['hidden_activation'] = self.kwargs.pop('activation') if self.kwargs.get('help_activation'): print(HELP_ACTIVATION) sys.exit(0) if self.kwargs.get('help_optimize'): print(HELP_OPTIMIZE) sys.exit(0) assert network_class is not feedforward.Network, \ 'use a concrete theanets.Network subclass ' \ 'like theanets.{Autoencoder,Regressor,...}' self.network = network_class(**self.kwargs)
def __init__(self, network_class, **overrides): '''Set up an experiment -- build a network and a trainer. The only input this constructor needs is the Python class of the network to build. Other configuration---for example, creating the appropriate trainer class---typically takes place by parsing command-line argument values. Datasets also need to be added to the experiment, either : - manually, by calling add_dataset(...), or - at runtime, by providing data to the run(train_data, valid_data) method. Datasets are typically provided as numpy arrays, but they can also be provided as callables, as described in the dataset module. Any keyword arguments provided to the constructor will be used to override values passed on the command line. (Typically this is used to provide experiment-specific default values for command line arguments that have no global defaults, e.g., network architecture.) ''' self.trainers = [] self.datasets = {} self.args, self.kwargs = climate.parse_args(**overrides) if 'activation' in self.kwargs: warnings.warn( 'please use --hidden-activation instead of --activation', DeprecationWarning) activation = self.kwargs.pop('activation') if not self.kwargs.get('hidden_activation'): self.kwargs['hidden_activation'] = activation if self.kwargs.get('help_activation'): print(HELP_ACTIVATION) sys.exit(0) if self.kwargs.get('help_optimize'): print(HELP_OPTIMIZE) sys.exit(0) kw = {} kw.update(self.kwargs) self.network = self._build_network(network_class, **kw) kw = {} kw.update(self.kwargs) self._build_trainers(**kw)
import os, sys import transform import util from transform import transformFFT import numpy as np import re from scipy.signal import blackmanharris as blackmanharris import climate if __name__ == "__main__": if len(sys.argv) > -1: climate.add_arg('--db', help="the dataset path") climate.add_arg('--feature_path', help="the path where to save the features") kwargs = climate.parse_args() db = None if kwargs.__getattribute__('db'): db = kwargs.__getattribute__('db') # else: # db='/home/marius/Documents/Database/iKala/' if kwargs.__getattribute__('feature_path'): feature_path = kwargs.__getattribute__('feature_path') else: feature_path = os.path.join(db, 'transforms', 't1') assert os.path.isdir( db ), "Please input the directory for the iKala dataset with --db path_to_iKala" tt = None for f in os.listdir(os.path.join(db, "Wavfile")):