Sequential Class

The Sequential model is a linear stack of layers, useful for straightforward neural network architectures. Layers are added via the constructor or through the .add() method.

Attributes:

Name	Type	Description
layers	list	List of Layer instances in the model.

Example

model = Sequential([
    Dense(64, activation='relu', input_shape=(784,)),
    Dense(10, activation='softmax')
])

Source code in microkeras/models/sequential/sequential.py

class Sequential:
    """
    The Sequential model is a linear stack of layers, useful for
    straightforward neural network architectures. Layers are added via the constructor
    or through the `.add()` method.

    Attributes:
        layers (list): List of Layer instances in the model.

    Example:
        ```python
        model = Sequential([
            Dense(64, activation='relu', input_shape=(784,)),
            Dense(10, activation='softmax')
        ])
        ```
    """

    def __init__(self, layers):
        """
        Initialize the Sequential model.

        Args:
            layers (list): Initial list of Layer instances to add to the model.
        """
        initialize(self, layers)
        initialize(self, layers)

    add = add
    build = build
    copy = copy
    compile = compile
    fit = fit
    evaluate = evaluate
    predict = predict
    save = save

    @classmethod
    def load(cls, filename):
        """
        Load a model from a file.

        Args:
            filename (str): Path to the file containing the saved model.

        Returns:
            Sequential: Loaded model instance.

        Example:
            ```python
            loaded_model = Sequential.load('my_model.json')
            ```
        """
        return load(cls, filename)

Functions

__init__(layers)

Initialize the Sequential model.

Parameters:

Name	Type	Description	Default
layers	list	Initial list of Layer instances to add to the model.	required

Source code in microkeras/models/sequential/sequential.py

def __init__(self, layers):
    """
    Initialize the Sequential model.

    Args:
        layers (list): Initial list of Layer instances to add to the model.
    """
    initialize(self, layers)
    initialize(self, layers)

load(filename) classmethod

Load a model from a file.

Parameters:

Name	Type	Description	Default
filename	str	Path to the file containing the saved model.	required

Returns:

Name	Type	Description
Sequential		Loaded model instance.

Example

loaded_model = Sequential.load('my_model.json')

Source code in microkeras/models/sequential/sequential.py

@classmethod
def load(cls, filename):
    """
    Load a model from a file.

    Args:
        filename (str): Path to the file containing the saved model.

    Returns:
        Sequential: Loaded model instance.

    Example:
        ```python
        loaded_model = Sequential.load('my_model.json')
        ```
    """
    return load(cls, filename)