resnet

ResNet

resnet(v1/v1.5/v2).py - academic (idiomatic)
resnet_cifar10(v1/v2).py - academic (idiomatic)
resnet(v1/v1.5/v2)_c.py - production (composable)

Paper

Macro-Architecture

Micro-Architecture

Stem Group

ResNet Block with Identity Shortcut

v2.0

In v2.0, the BatchNormalization and ReLU activation function is moved from after the convolution to before.

ResNet Block with Projection Shortcut

v1.0

v1.5

In v1.5, the strided convolution is moved from the 1x1 convolution to the 3x3 bottleneck convolution.

v2.0

In v2.0, the BatchNormalization and ReLU activation function is moved from after the convolution to before.

Classifier

Composable

Example: Instantiate a stock ResNet model

from resnet_v1_c import ResNetV1

# ResNet50 v1.0 from research paper
resnet = ResNetV1(50)

# ResNet50 v1.0 custom input shape/classes
resnet = ResNetV1(50, input_shape=(128, 128, 3), n_classes=50)

# getter for the tf.keras model
model = resnet.model

Example: Compose and Train a ResNet model

    ''' Example for constructing/training a ResNet V1 model on CIFAR-10
    '''
    # Example of constructing a mini-ResNet
    groups = [ { 'n_filters' : 64, 'n_blocks': 1 },
               { 'n_filters': 128, 'n_blocks': 2 },
               { 'n_filters': 256, 'n_blocks': 2 }]
    resnet = ResNetV1(groups, input_shape=(32, 32, 3), n_classes=10)
    resnet.model.summary()
    resnet.cifar10()
    ```