RAMjET
Understanding RAMjET
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Understanding RAMjET
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ramjet.models.gml_model

Code for a general convolutional model for light curve data.

Module Contents

Classes

GmlModel A general convolutional model for light curve data.
GmlModel1 A general convolutional model for light curve data.
GmlModel2 A general convolutional model for light curve data.
GmlModel2Wider A general convolutional model for light curve data.
GmlModel2LessBatchNorm A general convolutional model for light curve data.
GmlModel2NoL2 A general convolutional model for light curve data.
GmlModel2WiderNoL2 A general convolutional model for light curve data.
GmlModel2Wider4NoL2 A general convolutional model for light curve data.
GmlModel2Wider4NoL2NoDo A general convolutional model for light curve data.
GmlModel2Wider4 A general convolutional model for light curve data.
GmlModel3 A general convolutional model for light curve data.
GmlModel3Narrower A general convolutional model for light curve data.
GmlModel3NarrowerNoL2 A general convolutional model for light curve data.
class GmlModel(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel1(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2Wider(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2LessBatchNorm(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2NoL2(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2WiderNoL2(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2Wider4NoL2(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2Wider4NoL2NoDo(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel2Wider4(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel3(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel3Narrower(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
class GmlModel3NarrowerNoL2(number_of_label_types=1)[source]

Bases: tensorflow.keras.Model

A general convolutional model for light curve data.

__init__(self, number_of_label_types=1)[source]

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]

The forward pass of the layer.

Parameters:
  • inputs – The input tensor.
  • training – A boolean specifying if the layer should be in training mode.
  • mask – A mask for the input tensor.
Returns:

The output tensor of the layer.
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