<filename>train_code_v2/theano_toolkit/parameters.py<gh_stars>0
from theano.tensor.shared_randomstreams import RandomStreams
import theano.tensor as T
import theano
import random
import numpy as np
from collections import OrderedDict
import cPickle as pickle

import inspect


class Parameters():

    def __init__(self):
        self.__dict__['params'] = {}

    def __setattr__(self, name, array):
        params = self.__dict__['params']
        if name not in params:
            params[name] = theano.shared(
                value=np.asarray(
                    array,
                    dtype=theano.config.floatX
                ),
                borrow=True,
                name=name
            )
        else:
            print "%s already assigned" % name
            params[name].set_value(np.asarray(
                array,
                dtype=theano.config.floatX
            ))

    def __setitem__(self, name, array):
        self.__setattr__(name, array)

    def __getitem__(self, name):
        return self.__getattr__(name)

    def __getattr__(self, name):
        params = self.__dict__['params']
        return self.params[name]

    def remove(self, name):
        del self.__dict__['params'][name]

    def values(self):
        params = self.__dict__['params']
        return params.values()

    def save(self, filename):
        params = self.__dict__['params']
        with open(filename, 'wb') as f:
            pickle.dump({p.name: p.get_value() for p in params.values()}, f, 2)

    def load(self, filename):
        params = self.__dict__['params']
        loaded = pickle.load(open(filename, 'rb'))
        for k in params:
            if k in loaded:
                params[k].set_value(loaded[k])
            else:
                print "%s does not exist." % k

    def __enter__(self):
        _, _, _, env_locals = inspect.getargvalues(
            inspect.currentframe().f_back)
        self.__dict__['_env_locals'] = env_locals.keys()

    def __exit__(self, type, value, traceback):
        _, _, _, env_locals = inspect.getargvalues(
            inspect.currentframe().f_back)
        prev_env_locals = self.__dict__['_env_locals']
        del self.__dict__['_env_locals']
        for k in env_locals.keys():
            if k not in prev_env_locals:
                self.__setattr__(k, env_locals[k])
                env_locals[k] = self.__getattr__(k)
        return True

    def parameter_count(self):
        import operator
        params = self.__dict__['params']
        count = 0
        for p in params.values():
            shape = p.get_value().shape
            if len(shape) == 0:
                count += 1
            else:
                count += reduce(operator.mul, shape)
        return count


if __name__ == "__main__":
    P = Parameters()

    with P:
        test = np.zeros((5,))

    print P.values()

<filename>train_code_v2/theano_toolkit/parameters.py<gh_stars>0
from theano.tensor.shared_randomstreams import RandomStreams
import theano.tensor as T
import theano
import random
import numpy as np
from collections import OrderedDict
import cPickle as pickle

import inspect


class Parameters():

    def __init__(self):
        self.__dict__['params'] = {}

    def __setattr__(self, name, array):
        params = self.__dict__['params']
        if name not in params:
            params[name] = theano.shared(
                value=np.asarray(
                    array,
                    dtype=theano.config.floatX
                ),
                borrow=True,
                name=name
            )
        else:
            print "%s already assigned" % name
            params[name].set_value(np.asarray(
                array,
                dtype=theano.config.floatX
            ))

    def __setitem__(self, name, array):
        self.__setattr__(name, array)

    def __getitem__(self, name):
        return self.__getattr__(name)

    def __getattr__(self, name):
        params = self.__dict__['params']
        return self.params[name]

    def remove(self, name):
        del self.__dict__['params'][name]

    def values(self):
        params = self.__dict__['params']
        return params.values()

    def save(self, filename):
        params = self.__dict__['params']
        with open(filename, 'wb') as f:
            pickle.dump({p.name: p.get_value() for p in params.values()}, f, 2)

    def load(self, filename):
        params = self.__dict__['params']
        loaded = pickle.load(open(filename, 'rb'))
        for k in params:
            if k in loaded:
                params[k].set_value(loaded[k])
            else:
                print "%s does not exist." % k

    def __enter__(self):
        _, _, _, env_locals = inspect.getargvalues(
            inspect.currentframe().f_back)
        self.__dict__['_env_locals'] = env_locals.keys()

    def __exit__(self, type, value, traceback):
        _, _, _, env_locals = inspect.getargvalues(
            inspect.currentframe().f_back)
        prev_env_locals = self.__dict__['_env_locals']
        del self.__dict__['_env_locals']
        for k in env_locals.keys():
            if k not in prev_env_locals:
                self.__setattr__(k, env_locals[k])
                env_locals[k] = self.__getattr__(k)
        return True

    def parameter_count(self):
        import operator
        params = self.__dict__['params']
        count = 0
        for p in params.values():
            shape = p.get_value().shape
            if len(shape) == 0:
                count += 1
            else:
                count += reduce(operator.mul, shape)
        return count


if __name__ == "__main__":
    P = Parameters()

    with P:
        test = np.zeros((5,))

    print P.values()
