package models.cnn

optional int32 input_height = 1
Input image height.
optional int32 input_width = 2
Input image width.
optional int32 num_channels = 3
Input image number of channels.
optional ResnetModuleConfig resnet_module_config = 1000
Configuration object for the core resnet module.
optional optim.OptimizerConfig optimizer_config = 2000
Configuration object for training optimization.
optional int32 seed = 3000
Seed for initialization.

optional int32 num_channels = 1
Input image number of channels.
optional int32 num_classes = 2
Output prediction number of classes.
repeated int32 num_residual_units = 3
Number of residual units for each resolution stage.
repeated int32 num_filters = 4
Number of filters for each resolution stage.
repeated int32 strides = 5
Stride for the initial convolution of each resolution stage.
repeated int32 dilations = 6
Dilation rate for each resolution stage.
optional int32 init_stride = 7
Stride for the convolution layer in the very beginning.
optional bool init_max_pool = 8
Max pooling ratio for the very beginning.
optional int32 init_filter_size = 9
Initial size of a filter. (All filters afterwards are 3x3).
optional bool use_bottleneck = 10
Whether to use bottleneck layer.
optional bool build_classifier = 11
Whether to build the final classification layer.
optional float weight_decay = 12
Weight decay.
optional string data_format = 13
"NCHW" or "NHWC"
optional float dropout = 14
Dropout for wide residual networks.

message ResnetModelConfig