baseline_imagenet_wide_resnet.gin

include 'meta_dataset/learn/gin/setups/imagenet.gin'
include 'meta_dataset/learn/gin/models/baseline_config.gin'

# Backbone hypers.
LearnerConfig.embedding_network = 'wide_resnet'
LearnerConfig.pretrained_checkpoint = ''
LearnerConfig.pretrained_source = 'scratch'

# Model hypers.
BaselineLearner.knn_distance = 'cosine'
BaselineLearner.cosine_classifier = True
BaselineLearner.cosine_logits_multiplier = 1
BaselineLearner.use_weight_norm = True

# Data hypers.
DataConfig.image_height = 126

# Training hypers (not needed for eval).
LearnerConfig.decay_every = 100
LearnerConfig.decay_rate = 0.5082121576573064
LearnerConfig.learning_rate = 0.007084776688116927
weight_decay = 0.000005078192976503067