Python tensorflow.keras.regularizers.serialize() Examples

The following are 21 code examples of tensorflow.keras.regularizers.serialize(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow.keras.regularizers , or try the search function .
Example #1
Source Project: StyleGAN2-Tensorflow-2.0   Author: manicman1999   File: conv_mod.py    License: MIT License 6 votes vote down vote up 
def get_config(self):
        config = {
            'filters': self.filters,
            'kernel_size': self.kernel_size,
            'strides': self.strides,
            'padding': self.padding,
            'dilation_rate': self.dilation_rate,
            'kernel_initializer': initializers.serialize(self.kernel_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'activity_regularizer':
                regularizers.serialize(self.activity_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'demod': self.demod
        }
        base_config = super(Conv2DMod, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #2
Source Project: bcnn   Author: sandialabs   File: groupnorm.py    License: MIT License 6 votes vote down vote up 
def get_config(self):
        config = {
            "groups": self.groups,
            "axis": self.axis,
            "epsilon": self.epsilon,
            "center": self.center,
            "scale": self.scale,
            "beta_initializer": initializers.serialize(self.beta_initializer),
            "gamma_initializer": initializers.serialize(self.gamma_initializer),
            "beta_regularizer": regularizers.serialize(self.beta_regularizer),
            "gamma_regularizer": regularizers.serialize(self.gamma_regularizer),
            "beta_constraint": constraints.serialize(self.beta_constraint),
            "gamma_constraint": constraints.serialize(self.gamma_constraint)
        }
        base_config = super(GroupNormalization, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #3
Source Project: qkeras   Author: google   File: qconvolutional.py    License: Apache License 2.0 6 votes vote down vote up 
def get_config(self):
    config = super(QDepthwiseConv2D, self).get_config()
    config.pop("filters", None)
    config.pop("kernel_initializer", None)
    config.pop("kernel_regularizer", None)
    config.pop("kernel_constraint", None)
    config["depth_multiplier"] = self.depth_multiplier
    config["depthwise_initializer"] = initializers.serialize(
        self.depthwise_initializer)
    config["depthwise_regularizer"] = regularizers.serialize(
        self.depthwise_regularizer)
    config["depthwise_constraint"] = constraints.serialize(
        self.depthwise_constraint)
    config["depthwise_quantizer"] = constraints.serialize(
        self.depthwise_quantizer_internal)
    config["bias_quantizer"] = constraints.serialize(
        self.bias_quantizer_internal)
    config["depthwise_range"] = self.depthwise_range
    config["bias_range"] = self.bias_range
    return config
Example #4
Source Project: TensorNetwork   Author: google   File: conv2d_mpo.py    License: Apache License 2.0 6 votes vote down vote up 
def get_config(self) -> dict:
    config = {
        'filters': self.filters,
        'kernel_size': self.kernel_size,
        'num_nodes': self.num_nodes,
        'bond_dim': self.bond_dim,
        '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),
    }
    base_config = super(Conv2DMPO, self).get_config()
    config.update(base_config)
    return config
Example #5
Source Project: 3d-brain-tumor-segmentation   Author: vliu15   File: group_norm.py    License: Apache License 2.0 6 votes vote down vote up 
def get_config(self):
        config = {
            'groups': self.groups,
            'axis': self.axis,
            'epsilon': self.epsilon,
            'center': self.center,
            'scale': self.scale,
            'beta_initializer': initializers.serialize(self.beta_initializer),
            'gamma_initializer': initializers.serialize(self.gamma_initializer),
            'beta_regularizer': regularizers.serialize(self.beta_regularizer),
            'gamma_regularizer': regularizers.serialize(self.gamma_regularizer),
            'beta_constraint': constraints.serialize(self.beta_constraint),
            'gamma_constraint': constraints.serialize(self.gamma_constraint)
        }
        base_config = super(GroupNormalization, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #6
Source Project: Basic_CNNs_TensorFlow2   Author: calmisential   File: group_convolution.py    License: MIT License 6 votes vote down vote up 
def get_config(self):
        config = {
            "input_channels": self.input_channels,
            "output_channels": self.output_channels,
            "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),
            "groups": self.groups,
            "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(GroupConv2D, self).get_config()
        return {**base_config, **config}
Example #7
Source Project: Basic_CNNs_TensorFlow2   Author: calmisential   File: group_convolution.py    License: MIT License 6 votes vote down vote up 
def get_config(self):
        config = {
            "input_channels": self.input_channels,
            "output_channels": self.output_channels,
            "kernel_size": self.kernel_size,
            "strides": self.strides,
            "padding": self.padding,
            "output_padding": self.output_padding,
            "data_format": self.data_format,
            "dilation_rate": self.dilation_rate,
            "activation": activations.serialize(self.activation),
            "groups": self.groups,
            "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(GroupConv2DTranspose, self).get_config()
        return {**base_config, **config}
Example #8
Source Project: TF.Keras-Commonly-used-models   Author: 1044197988   File: FRN.py    License: Apache License 2.0 6 votes vote down vote up 
def get_config(self):
        config = {
            'axis': self.axis,
            'epsilon': self.epsilon,
            'beta_initializer': initializers.serialize(self.beta_initializer),
            'tau_initializer': initializers.serialize(self.tau_initializer),
            'gamma_initializer': initializers.serialize(self.gamma_initializer),
            'beta_regularizer': regularizers.serialize(self.beta_regularizer),
            'tau_regularizer': regularizers.serialize(self.tau_regularizer),
            'gamma_regularizer': regularizers.serialize(self.gamma_regularizer),
            'beta_constraint': constraints.serialize(self.beta_constraint),
            'gamma_constraint': constraints.serialize(self.gamma_constraint),
            'tau_constraint': constraints.serialize(self.tau_constraint)
        }
        base_config = super(FRN, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #9
Source Project: spektral   Author: danielegrattarola   File: keras.py    License: MIT License 5 votes vote down vote up 
def serialize_kwarg(key, attr):
    if key.endswith('_initializer'):
        return initializers.serialize(attr)
    if key.endswith('_regularizer'):
        return regularizers.serialize(attr)
    if key.endswith('_constraint'):
        return constraints.serialize(attr)
    if key == 'activation':
        return activations.serialize(attr)
    if key == 'use_bias':
        return attr
Example #10
Source Project: spektral   Author: danielegrattarola   File: topk_pool.py    License: MIT License 5 votes vote down vote up 
def get_config(self):
        config = {
            'ratio': self.ratio,
            'return_mask': self.return_mask,
            'kernel_initializer': initializers.serialize(self.kernel_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
        }
        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #11
Source Project: spektral   Author: danielegrattarola   File: diff_pool.py    License: MIT License 5 votes vote down vote up 
def get_config(self):
        config = {
            'k': self.k,
            'channels': self.channels,
            'return_mask': self.return_mask,
            'kernel_initializer': initializers.serialize(self.kernel_initializer),
            'kernel_regularizer': regularizers.serialize(self.kernel_regularizer),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
        }
        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #12
Source Project: spektral   Author: danielegrattarola   File: mincut_pool.py    License: MIT License 5 votes vote down vote up 
def get_config(self):
        config = {
            'k': self.k,
            'mlp_hidden': self.mlp_hidden,
            'mlp_activation': self.mlp_activation,
            'return_mask': self.return_mask,
            '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),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint)
        }
        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #13
Source Project: spektral   Author: danielegrattarola   File: graph_conv.py    License: MIT License 5 votes vote down vote up 
def get_config(self):
        config = {
            'channels': self.channels,
            '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),
            'kernel_constraint': constraints.serialize(self.kernel_constraint),
            'bias_constraint': constraints.serialize(self.bias_constraint)
        }
        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #14
Source Project: keras-squeeze-excite-network   Author: titu1994   File: se_mobilenets.py    License: MIT License 5 votes vote down vote up 
def get_config(self):
        config = super(DepthwiseConv2D, self).get_config()
        config.pop('filters')
        config.pop('kernel_initializer')
        config.pop('kernel_regularizer')
        config.pop('kernel_constraint')
        config['depth_multiplier'] = self.depth_multiplier
        config['depthwise_initializer'] = initializers.serialize(self.depthwise_initializer)
        config['depthwise_regularizer'] = regularizers.serialize(self.depthwise_regularizer)
        config['depthwise_constraint'] = constraints.serialize(self.depthwise_constraint)
        return config
Example #15
Source Project: qkeras   Author: google   File: qlayers.py    License: Apache License 2.0 5 votes vote down vote up 
def get_config(self):
    config = {
        "units": self.units,
        "activation": activations.serialize(self.activation),
        "use_bias": self.use_bias,
        "kernel_quantizer":
            constraints.serialize(self.kernel_quantizer_internal),
        "bias_quantizer":
            constraints.serialize(self.bias_quantizer_internal),
        "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),
        "kernel_range": self.kernel_range,
        "bias_range": self.bias_range
    }
    base_config = super(QDense, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))
Example #16
Source Project: qkeras   Author: google   File: qconvolutional.py    License: Apache License 2.0 5 votes vote down vote up 
def get_config(self):
    config = {
        "kernel_quantizer":
            constraints.serialize(self.kernel_quantizer_internal),
        "bias_quantizer":
            constraints.serialize(self.bias_quantizer_internal),
        "kernel_range": self.kernel_range,
        "bias_range": self.bias_range
    }
    base_config = super(QConv1D, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))
Example #17
Source Project: qkeras   Author: google   File: qconvolutional.py    License: Apache License 2.0 5 votes vote down vote up 
def get_config(self):
    config = {
        "kernel_quantizer":
            constraints.serialize(self.kernel_quantizer_internal),
        "bias_quantizer":
            constraints.serialize(self.bias_quantizer_internal),
        "kernel_range": self.kernel_range,
        "bias_range": self.bias_range
    }
    base_config = super(QConv2D, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))
Example #18
Source Project: qkeras   Author: google   File: qnormalization.py    License: Apache License 2.0 5 votes vote down vote up 
def get_config(self):
    config = {
        'axis': self.axis,
        'momentum': self.momentum,
        'epsilon': self.epsilon,
        'center': self.center,
        'scale': self.scale,
        'beta_quantizer':
            constraints.serialize(self.beta_quantizer_internal),
        'gamma_quantizer':
            constraints.serialize(self.gamma_quantizer_internal),
        'mean_quantizer':
            constraints.serialize(self.mean_quantizer_internal),
        'variance_quantizer':
            constraints.serialize(self.variance_quantizer_internal),
        'beta_initializer': initializers.serialize(self.beta_initializer),
        'gamma_initializer': initializers.serialize(self.gamma_initializer),
        'moving_mean_initializer':
            initializers.serialize(self.moving_mean_initializer),
        'moving_variance_initializer':
            initializers.serialize(self.moving_variance_initializer),
        'beta_regularizer': regularizers.serialize(self.beta_regularizer),
        'gamma_regularizer': regularizers.serialize(self.gamma_regularizer),
        'beta_constraint': constraints.serialize(self.beta_constraint),
        'gamma_constraint': constraints.serialize(self.gamma_constraint),
        'beta_range': self.beta_range,
        'gamma_range': self.gamma_range,
    }
    base_config = super(BatchNormalization, self).get_config()
    return dict(list(base_config.items()) + list(config.items()))
Example #19
Source Project: megnet   Author: materialsvirtuallab   File: set2set.py    License: BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def get_config(self):
        config = {"T": self.T,
                  "n_hidden": self.n_hidden,
                  "activation": activations.serialize(self.activation),
                  "activation_lstm": activations.serialize(
                      self.activation_lstm),
                  "recurrent_activation": activations.serialize(
                      self.recurrent_activation),
                  "kernel_initializer": initializers.serialize(
                      self.kernel_initializer),
                  "recurrent_initializer": initializers.serialize(
                      self.recurrent_initializer),
                  "bias_initializer": initializers.serialize(
                      self.bias_initializer),
                  "use_bias": self.use_bias,
                  "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)

                  }
        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Example #20
Source Project: megnet   Author: materialsvirtuallab   File: base.py    License: BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def get_config(self) -> Dict:
        """
        Part of keras layer interface, where the signature is converted into a dict
        Returns:
            configurational dictionary
        """
        config = {
            '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().get_config()
        return dict(list(base_config.items()) + list(config.items()))  # noqa
Example #21
Source Project: Echo   Author: digantamisra98   File: custom_activation.py    License: MIT License 5 votes vote down vote up 
def get_config(self):
        config = {
            "alpha_initializer": initializers.serialize(self.b_initializer),
            "alpha_regularizer": regularizers.serialize(self.b_regularizer),
            "alpha_constraint": constraints.serialize(self.b_constraint),
            "b_initializer": initializers.serialize(self.b_initializer),
            "b_regularizer": regularizers.serialize(self.b_regularizer),
            "b_constraint": constraints.serialize(self.b_constraint),
            "shared_axes": self.shared_axes,
        }
        base_config = super(APL, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))