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def | se_resnet_saul.SEResNet (input_shape=None, initial_conv_filters=64, depth=[3, filters=[64, width=1, bottleneck=False, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, pooling=None, classes=1000) |
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def | se_resnet_saul.SEResNet18 (input_shape=None, width=1, bottleneck=False, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, pooling=None, classes=1000) |
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def | se_resnet_saul.SEResNet34 (input_shape=None, width=1, bottleneck=False, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, pooling=None, classes=1000) |
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def | se_resnet_saul.SEResNet50 (input_shape=None, width=1, bottleneck=True, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, pooling=None, classes=1000) |
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def | se_resnet_saul.SEResNet101 (input_shape=None, width=1, bottleneck=True, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, pooling=None, classes=1000) |
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def | se_resnet_saul.SEResNet154 (input_shape=None, width=1, bottleneck=True, weight_decay=1e-4, include_top=True, weights=None, input_tensor=None, pooling=None, classes=1000) |
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def | se_resnet_saul._resnet_block (input, filters, k=1, strides=(1, 1)) |
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def | se_resnet_saul._resnet_bottleneck_block (input, filters, k=1, strides=(1, 1)) |
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def | se_resnet_saul._create_se_resnet (classes, img_input, include_top, initial_conv_filters, filters, depth, width, bottleneck, weight_decay, pooling) |
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