se_densenet.py File Reference

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Namespaces
	se_densenet

Functions
def	se_densenet.preprocess_input (x, data_format=None)
def	se_densenet.SEDenseNet (input_shape=None, depth=40, nb_dense_block=3, growth_rate=12, nb_filter=-1, nb_layers_per_block=-1, bottleneck=False, reduction=0.0, dropout_rate=0.0, weight_decay=1e-4, subsample_initial_block=False, include_top=True, weights=None, input_tensor=None, classes=10, activation='softmax')
def	se_densenet.SEDenseNetImageNet121 (input_shape=None, bottleneck=True, reduction=0.5, dropout_rate=0.0, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, classes=1000, activation='N')
def	se_densenet.SEDenseNetImageNet169 (input_shape=None, bottleneck=True, reduction=0.5, dropout_rate=0.0, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, classes=1000, activation='softmax')
def	se_densenet.SEDenseNetImageNet201 (input_shape=None, bottleneck=True, reduction=0.5, dropout_rate=0.0, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, classes=1000, activation='softmax')
def	se_densenet.SEDenseNetImageNet264 (input_shape=None, bottleneck=True, reduction=0.5, dropout_rate=0.0, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, classes=1000, activation='softmax')
def	se_densenet.SEDenseNetImageNet161 (input_shape=None, bottleneck=True, reduction=0.5, dropout_rate=0.0, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, classes=1000, activation='softmax')
def	se_densenet.__conv_block (ip, nb_filter, bottleneck=False, dropout_rate=None, weight_decay=1e-4)
def	se_densenet.__dense_block (x, nb_layers, nb_filter, growth_rate, bottleneck=False, dropout_rate=None, weight_decay=1e-4, grow_nb_filters=True, return_concat_list=False)
def	se_densenet.__transition_block (ip, nb_filter, compression=1.0, weight_decay=1e-4)
def	se_densenet.__create_dense_net (nb_classes, img_input, include_top, depth=40, nb_dense_block=3, growth_rate=12, nb_filter=-1, nb_layers_per_block=-1, bottleneck=False, reduction=0.0, dropout_rate=None, weight_decay=1e-4, subsample_initial_block=False, activation='softmax')