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
