code
stringlengths
3
6.57k
get_config()
dict(list(base_config.items()
list(config.items()
from_config(cls, config)
config.pop('implementation')
cls(**config)
GRUCell(Layer)
use (see [activations](../activations.md)
applied (ie. "linear" activation: `a(x)
step (see [activations](../activations.md)
inputs (see [initializers](../initializers.md)
state (see [initializers](../initializers.md)
vector (see [initializers](../initializers.md)
matrix (see [regularizer](../regularizers.md)
matrix (see [regularizer](../regularizers.md)
vector (see [regularizer](../regularizers.md)
matrix (see [constraints](../constraints.md)
matrix (see [constraints](../constraints.md)
vector (see [constraints](../constraints.md)
super(GRUCell, self)
__init__(**kwargs)
activations.get(activation)
activations.get(recurrent_activation)
initializers.get(kernel_initializer)
initializers.get(recurrent_initializer)
initializers.get(bias_initializer)
regularizers.get(kernel_regularizer)
regularizers.get(recurrent_regularizer)
regularizers.get(bias_regularizer)
constraints.get(kernel_constraint)
constraints.get(recurrent_constraint)
constraints.get(bias_constraint)
min(1., max(0., dropout)
min(1., max(0., recurrent_dropout)
build(self, input_shape)
self.add_weight(shape=(input_dim, self.units * 3)
self.add_weight(shape=(self.units * 3,)
call(self, inputs, states, training=None)
_generate_dropout_ones(inputs, K.shape(inputs)
_generate_dropout_ones(inputs, self.units)
K.dot(inputs_z, self.kernel_z)
K.dot(inputs_r, self.kernel_r)
K.dot(inputs_h, self.kernel_h)
K.bias_add(x_z, self.bias_z)
K.bias_add(x_r, self.bias_r)
K.bias_add(x_h, self.bias_h)
K.dot(inputs, self.kernel)
K.bias_add(matrix_x, self.bias)
self.recurrent_activation(x_z + recurrent_z)
self.recurrent_activation(x_r + recurrent_r)
self.activation(x_h + recurrent_h)
get_config(self)
activations.serialize(self.activation)
activations.serialize(self.recurrent_activation)
initializers.serialize(self.kernel_initializer)
initializers.serialize(self.recurrent_initializer)
initializers.serialize(self.bias_initializer)
regularizers.serialize(self.kernel_regularizer)
regularizers.serialize(self.recurrent_regularizer)
regularizers.serialize(self.bias_regularizer)
constraints.serialize(self.kernel_constraint)
constraints.serialize(self.recurrent_constraint)
constraints.serialize(self.bias_constraint)
super(GRUCell, self)
get_config()
dict(list(base_config.items()
list(config.items()
GRU(RNN)
use (see [activations](../activations.md)
applied (ie. "linear" activation: `a(x)
step (see [activations](../activations.md)
inputs (see [initializers](../initializers.md)
state (see [initializers](../initializers.md)
vector (see [initializers](../initializers.md)
matrix (see [regularizer](../regularizers.md)
matrix (see [regularizer](../regularizers.md)
vector (see [regularizer](../regularizers.md)
layer (its "activation")
matrix (see [constraints](../constraints.md)
matrix (see [constraints](../constraints.md)
vector (see [constraints](../constraints.md)
Boolean (default False)
Boolean (default False)
Boolean (default False)
K.backend()
super(GRU, self)
regularizers.get(activity_regularizer)
call(self, inputs, mask=None, training=None, initial_state=None)
super(GRU, self)
units(self)
activation(self)
recurrent_activation(self)
use_bias(self)
kernel_initializer(self)
recurrent_initializer(self)
bias_initializer(self)
kernel_regularizer(self)
recurrent_regularizer(self)
bias_regularizer(self)
kernel_constraint(self)