# Install the module
# pip install -e .

# Or copy the convmlp folder to your project

# Basic usage
from convmlp import ConvMLPClassifier

# Define convolutional layers
conv_layers = [
    {'type': 'conv2d', 'filters': 32, 'kernel_size': 3, 'padding': 'same'},
    {'type': 'maxpool2d', 'pool_size': 2},
    {'type': 'flatten'},  # Important: flatten before MLP
]

# Create model
model = ConvMLPClassifier(
    conv_layers=conv_layers,
    mlp_layers=[128, 64],  # MLP hidden layers after conv
    input_shape=(1, 28, 28),  # For MNIST
    max_iter=100
)

# Fit and predict
model.fit(X_train, y_train)
predictions = model.predict(X_test)