def init_options(): opts = utils.Options() opts.add( name='choices', required='True' ) return opts
def init_options(): """The method that defines the Model's parameters. When a class overrides this method, it should build a nnb.utils.Options' instance with the parameters specifications. This instance should be returned by this method. To access the nnb.utils.Options instance returned by this method, use the options property. For example: import nnb class FooModel(nnb.Model): @staticmethod def init_options(): opts = nnb.utils.Options() opts.add( name='bar_param', value_type=int, required=True ) return opts f = FooModel() #ValueError! Should pass the bar_param parameter f = FooModel(bar_param=2.3) #ValueError! bar_param should be an int f = FooModel(bar_param=2) #OK! If this method is not overriden, and empty nnb.utils.Options instance will be used. For more info on options, see the nnb.utils.Options documentation. """ return utils.Options()
def init_options(): opts = utils.Options() opts.add( name="slice", required=True ) return opts
def init_options(): ops = utils.Options() ops.add( name="insize", value_type=int, required=True ) ops.add( name="outsize", value_type=int, required=True ) ops.add( name="init", value_type=init.Initializer, value=init.XavierInitializer() ) ops.add( name='W', ) ops.add( name='b', ) ops.add( name='activation_func', value=T.nnet.sigmoid ) return ops
def init_options(): ops = utils.Options() ops.add( name="insize", required=True, value_type=int, ) ops.add( name="outsize", required=True, value_type=int, ) ops.add( name="init", value_type=init.Initializer, value=init.XavierInitializer() ) ops.add( name="W_softmax", value_type=np.ndarray, ) ops.add( name="b_softmax", value_type=np.ndarray, ) return ops
def init_options(): opts = utils.Options() opts.add( name='axis', value=0, value_type=int ) return opts
def init_options(): opts = utils.Options() opts.add( name='dataset', required=True, value_type=[np.ndarray, list] ) opts.add( name='trainer', required=True, value_type=nnb.train.Trainer ) opts.add( name='eval_dataset', value_type=[np.ndarray, list] ) opts.add( name='eval_interval', value=1, value_type=int ) opts.add( name='max_no_improve', value_type=int ) opts.add( name='epochs_num', value_type=int ) opts.add( name='permute_train', value=True, value_type=bool ) opts.add( name='custom_procedures', value=[], value_type=list ) opts.add( name='batch_size', value_type=int ) opts.add( name='eval_model' ) opts.add( name='eval_model_is_cost', value=False ) opts.add( name='plot', value_type=bool, value=False ) return opts
def init_options(): """Method that declares initialization parameters of the Trainer A class that extends the nnb.train.Trainer class should override this method to set initialization parameters of the Trainer. This method should always be static. This method should return a nnb.utils.Options instance. For more info on this class, see its documentation. """ return utils.Options()
def init_options(): ops = utils.Options() ops.add( name="comp_model", value_type=Model ) ops.add( name="insize", value_type=int ) return ops
def init_options(): opts = utils.Options() opts.add( name='fn', required=True ) opts.add( name='params', value=[], value_type=list ) return opts
def init_options(): opts = utils.Options() opts.add(name='stride', value_type=int, value=1) opts.add(name='window', value_type=int, required=True) opts.add(name='insize', value_type=int, required=True) opts.add(name='outsize', value_type=int, required=True) opts.add(name='activation_func', value=nnb.activation.sigmoid) opts.add(name='W', value_type=np.ndarray) opts.add(name='b', value_type=np.ndarray) opts.add(name='init', value_type=init.Initializer, value=init.XavierInitializer()) return opts
def init_options(): opts = utils.Options() opts.add( name="ndim", required=True ) opts.add( name="dtype", value=theano.config.floatX ) opts.add( name="name", value="input" ) return opts
def init_options(): ops = utils.Options() ops.add( name='insize', value_type=int, required=True, ) ops.add( name='outsize', value_type=int, required=True, ) ops.add( name='W', value_type=np.ndarray, ) ops.add( name='b', value_type=np.ndarray, ) ops.add( name='W_h', value_type=np.ndarray, ) ops.add( name='activation_func', value=T.nnet.sigmoid ) ops.add( name='init', value_type=init.Initializer, value=init.XavierInitializer() ) return ops
def init_options(): opts = utils.Options() opts.add(name='insize', required=True, value_type=int) opts.add(name='outsize', value_type=int) opts.add(name='init', value_type=init.Initializer, value=init.XavierInitializer()) opts.add(name='Wi', value_type=np.ndarray) opts.add(name='Wf', value_type=np.ndarray) opts.add(name='Wc', value_type=np.ndarray) opts.add(name='Wo', value_type=np.ndarray) opts.add(name='Ui', value_type=np.ndarray) opts.add(name='Uf', value_type=np.ndarray) opts.add(name='Uc', value_type=np.ndarray) opts.add(name='Uo', value_type=np.ndarray) opts.add(name='Vo', value_type=np.ndarray) opts.add(name='bi', value_type=np.ndarray) opts.add(name='bf', value_type=np.ndarray) opts.add(name='bc', value_type=np.ndarray) opts.add(name='bo', value_type=np.ndarray) return opts
def init_options(): ops = utils.Options() ops.add( name='model', value_type=Model, ) ops.add( name='h0', value_type=[np.ndarray, list], ) ops.add( name='insize', value_type=int, ) ops.add( name='outsize', value_type=int, ) return ops