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Forward Layer Method

Functions

forward_layer(layer, A_prev)

Perform forward propagation for a single layer.

Parameters:

Name Type Description Default
layer Layer

The current layer object.

 required
A_prev ndarray

Activation output from the previous layer.

 required

Returns:

Name Type Description
tuple

(Z, A) Z (numpy.ndarray): The linear combination output. A (numpy.ndarray): The activation output.
Example 
layer = Dense(64, activation='relu')
A_prev = np.random.randn(128, 32)
Z, A = forward_layer(layer, A_prev)
print(Z.shape, A.shape)
Source code in microkeras/operations/forward/forward_layer.py 
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def forward_layer(layer, A_prev):
    """
    Perform forward propagation for a single layer.

    Args:
        layer (Layer): The current layer object.
        A_prev (numpy.ndarray): Activation output from the previous layer.

    Returns:
        tuple: (Z, A)
            Z (numpy.ndarray): The linear combination output.
            A (numpy.ndarray): The activation output.

    Example:
        ```python
        layer = Dense(64, activation='relu')
        A_prev = np.random.randn(128, 32)
        Z, A = forward_layer(layer, A_prev)
        print(Z.shape, A.shape)
        ```
    """
    Z = calculate_Z(layer.W, A_prev, layer.b)
    A = calculate_A(Z, layer.activation)
    return Z, A