Python activations.serialize方法代码示例

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        if self.kernel_initializer in {'complex'}:
            ki = self.kernel_initializer
        else:
            ki = initializers.serialize(self.kernel_initializer)
        config = {
            'units': self.units,
            'activation': activations.serialize(self.activation),
            'use_bias': self.use_bias,
            'init_criterion': self.init_criterion,
            'kernel_initializer': ki,
            'bias_initializer': initializers.serialize(self.bias_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'bias_regularizer': regularizers.serialize(self.bias_regularizer),
            'activity_regularizer': regularizers.serialize(self.activity_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint),
            'seed': self.seed,
        }
        base_config = super(ComplexDense, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'projection_units': self.projection_units,
                  'activation': activations.serialize(self.activation),
                  'recurrent_activation': activations.serialize(self.recurrent_activation),
                  'projection_activation': activations.serialize(self.projection_activation),
                  'use_bias': self.use_bias,
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'recurrent_initializer': initializers.serialize(self.recurrent_initializer),
                  'projection_initializer': initializers.serialize(self.projection_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'unit_forget_bias': self.unit_forget_bias,
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer),
                  'projection_regularizer': regularizers.serialize(self.projection_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'recurrent_constraint': constraints.serialize(self.recurrent_constraint),
                  'projection_constraint': constraints.serialize(self.projection_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'dropout': self.dropout,
                  'recurrent_dropout': self.recurrent_dropout,
                  'implementation': self.implementation}
        base_config = super(NASCell, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {
            'rank': self.rank,
            'filters': self.filters,
            'kernel_size': self.kernel_size,
            'strides': self.strides,
            'padding': self.padding,
            'data_format': self.data_format,
            'dilation_rate': self.dilation_rate,
            'activation': activations.serialize(self.activation),
            'use_bias': self.use_bias,
            'kernel_initializer': initializers.serialize(self.kernel_initializer),
            'bias_initializer': initializers.serialize(self.bias_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'bias_regularizer': regularizers.serialize(self.bias_regularizer),
            'activity_regularizer': regularizers.serialize(self.activity_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint)
        }
        base_config = super(_Conv, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        if self.kernel_initializer == 'quaternion':
            ki = self.kernel_init
        else:
            ki = initializers.serialize(self.kernel_initializer)
        config = {
            'units': self.units,
            'activation': activations.serialize(self.activation),
            'use_bias': self.use_bias,
            'init_criterion': self.init_criterion,
            'kernel_initializer': ki,
            'bias_initializer': initializers.serialize(self.bias_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'bias_regularizer': regularizers.serialize(self.bias_regularizer),
            'activity_regularizer': regularizers.serialize(self.activity_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint),
            'seed': self.seed,
        }
        base_config = super(QuaternionDense, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'recurrent_clip_min': self.recurrent_clip_min,
                  'recurrent_clip_max': self.recurrent_clip_max,
                  'activation': activations.serialize(self.activation),
                  'use_bias': self.use_bias,
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'recurrent_initializer': initializers.serialize(self.recurrent_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'recurrent_constraint': constraints.serialize(self.recurrent_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'dropout': self.dropout,
                  'recurrent_dropout': self.recurrent_dropout,
                  'implementation': self.implementation}
        base_config = super(IndRNNCell, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'depth': self.depth,
                  'activation': activations.serialize(self.activation),
                  'recurrent_activation': activations.serialize(self.recurrent_activation),
                  'cell_activation': activations.serialize(self.cell_activation),
                  'use_bias': self.use_bias,
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'recurrent_initializer': initializers.serialize(self.recurrent_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'unit_forget_bias': self.unit_forget_bias,
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'recurrent_constraint': constraints.serialize(self.recurrent_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'dropout': self.dropout,
                  'recurrent_dropout': self.recurrent_dropout,
                  'implementation': self.implementation}
        base_config = super(NestedLSTMCell, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'window_size': self.window_size,
                  'stride': self.strides[0],
                  'return_sequences': self.return_sequences,
                  'go_backwards': self.go_backwards,
                  'stateful': self.stateful,
                  'unroll': self.unroll,
                  'use_bias': self.use_bias,
                  'dropout': self.dropout,
                  'activation': activations.serialize(self.activation),
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'activity_regularizer': regularizers.serialize(self.activity_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'input_dim': self.input_dim,
                  'input_length': self.input_length}
        base_config = super(QRNN, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {
            'filters': self.filters,
            'kernel_size': self.kernel_size,
            'kernel_initializer': initializers.serialize(self.kernel_initializer),
            'activation': activations.serialize(self.activation),
            'padding': self.padding,
            'strides': self.strides,
            'data_format': self.data_format,
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'bias_regularizer': regularizers.serialize(self.bias_regularizer),
            'activity_regularizer':
                regularizers.serialize(self.activity_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint),
            'use_bias': self.use_bias}
        base_config = super(CosineConvolution2D, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'output_dim': self.output_dim,
                  'window_size': self.window_size,
                  'init': self.init.get_config(),
                  'stride': self.strides[0],
                  'activation': activations.serialize(self.activation),
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'activity_regularizer': regularizers.serialize(self.activy_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'use_bias': self.use_bias,
                  'input_dim': self.input_dim,
                  'input_length': self.input_length}
        base_config = super(GCNN, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'learn_mode': self.learn_mode,
                  'test_mode': self.test_mode,
                  'use_boundary': self.use_boundary,
                  'use_bias': self.use_bias,
                  'sparse_target': self.sparse_target,
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'chain_initializer': initializers.serialize(self.chain_initializer),
                  'boundary_initializer': initializers.serialize(self.boundary_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'activation': activations.serialize(self.activation),
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'chain_regularizer': regularizers.serialize(self.chain_regularizer),
                  'boundary_regularizer': regularizers.serialize(self.boundary_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'chain_constraint': constraints.serialize(self.chain_constraint),
                  'boundary_constraint': constraints.serialize(self.boundary_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'input_dim': self.input_dim,
                  'unroll': self.unroll}
        base_config = super(CRF, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {
            'units': self.units,
            'n_experts':self.n_experts,
            'expert_activation': activations.serialize(self.expert_activation),
            'gating_activation': activations.serialize(self.gating_activation),
            'use_expert_bias': self.use_expert_bias,
            'use_gating_bias': self.use_gating_bias,
            'expert_kernel_initializer_scale': self.expert_kernel_initializer_scale,
            'gating_kernel_initializer_scale': self.gating_kernel_initializer_scale,
            'expert_bias_initializer': initializers.serialize(self.expert_bias_initializer),
            'gating_bias_initializer': initializers.serialize(self.gating_bias_initializer),
            'expert_kernel_regularizer': regularizers.serialize(self.expert_kernel_regularizer),
            'gating_kernel_regularizer': regularizers.serialize(self.gating_kernel_regularizer),
            'expert_bias_regularizer': regularizers.serialize(self.expert_bias_regularizer),
            'gating_bias_regularizer': regularizers.serialize(self.gating_bias_regularizer),
            'expert_kernel_constraint': constraints.serialize(self.expert_kernel_constraint),
            'gating_kernel_constraint': constraints.serialize(self.gating_kernel_constraint),
            'expert_bias_constraint': constraints.serialize(self.expert_bias_constraint),
            'gating_bias_constraint': constraints.serialize(self.gating_bias_constraint),
            'activity_regularizer': regularizers.serialize(self.activity_regularizer)
        }
        base_config = super(DenseMoE, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'activation': activations.serialize(self.activation),
                  'use_bias': self.use_bias,
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'recurrent_initializer': initializers.serialize(self.recurrent_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'activity_regularizer': regularizers.serialize(self.activity_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'recurrent_constraint': constraints.serialize(self.recurrent_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'dropout': self.dropout,
                  'recurrent_dropout': self.recurrent_dropout}
        base_config = super(TT_RNN, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {'units': self.units,
                  'activation': activations.serialize(self.activation),
                  'recurrent_activation': activations.serialize(self.recurrent_activation),
                  'use_bias': self.use_bias,
                  'kernel_initializer': initializers.serialize(self.kernel_initializer),
                  'recurrent_initializer': initializers.serialize(self.recurrent_initializer),
                  'bias_initializer': initializers.serialize(self.bias_initializer),
                  'unit_forget_bias': self.unit_forget_bias,
                  'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
                  'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer),
                  'bias_regularizer': regularizers.serialize(self.bias_regularizer),
                  'activity_regularizer': regularizers.serialize(self.activity_regularizer),
                  'kernel_constraint': constraints.serialize(self.kernel_constraint),
                  'recurrent_constraint': constraints.serialize(self.recurrent_constraint),
                  'bias_constraint': constraints.serialize(self.bias_constraint),
                  'dropout': self.dropout,
                  'recurrent_dropout': self.recurrent_dropout}
        base_config = super(PhasedLSTM, self).get_config()
        return dict(list(base_config.items()) + list(config.items())) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def sanitizedInitSer(init):
	if init in [sqrt_init]:
		return "sqrt_init"
	elif init == "complex" or isinstance(init, ComplexInit):
		return "complex"
	elif init == "complex_independent" or isinstance(init, ComplexIndependentFilters):
		return "complex_independent"
	else:
		return initializers.serialize(init) 

# 需要导入模块: from keras import activations [as 别名]
# 或者: from keras.activations import serialize [as 别名]
def get_config(self):
        config = {
            'rank': self.rank,
            'filters': self.filters,
            'kernel_size': self.kernel_size,
            'strides': self.strides,
            'padding': self.padding,
            'data_format': self.data_format,
            'dilation_rate': self.dilation_rate,
            'activation': activations.serialize(self.activation),
            'use_bias': self.use_bias,
            'normalize_weight': self.normalize_weight,
            'kernel_initializer': sanitizedInitSer(self.kernel_initializer),
            'bias_initializer': sanitizedInitSer(self.bias_initializer),
            'gamma_diag_initializer': sanitizedInitSer(self.gamma_diag_initializer),
            'gamma_off_initializer': sanitizedInitSer(self.gamma_off_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'bias_regularizer': regularizers.serialize(self.bias_regularizer),
            'gamma_diag_regularizer': regularizers.serialize(self.gamma_diag_regularizer),
            'gamma_off_regularizer': regularizers.serialize(self.gamma_off_regularizer),
            'activity_regularizer': regularizers.serialize(self.activity_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint),
            'gamma_diag_constraint': constraints.serialize(self.gamma_diag_constraint),
            'gamma_off_constraint': constraints.serialize(self.gamma_off_constraint),
            'init_criterion': self.init_criterion,
            'spectral_parametrization': self.spectral_parametrization,
        }
        base_config = super(ComplexConv, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))