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PiperOrigin-RevId: 424505240
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# MobileNetV3Small ImageNet classification. 67.5% top-1 and 87.6% top-5 accuracy.
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runtime:
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distribution_strategy: 'tpu'
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mixed_precision_dtype: 'bfloat16'
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task:
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model:
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num_classes: 1001
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input_size: [224, 224, 3]
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backbone:
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type: 'mobilenet'
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mobilenet:
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model_id: 'MobileNetV3Small'
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filter_size_scale: 1.0
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norm_activation:
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activation: 'relu'
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norm_momentum: 0.997
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norm_epsilon: 0.001
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use_sync_bn: false
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dropout_rate: 0.2
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losses:
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l2_weight_decay: 0.00001
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one_hot: true
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label_smoothing: 0.1
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train_data:
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input_path: 'imagenet-2012-tfrecord/train*'
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is_training: true
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global_batch_size: 4096
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dtype: 'bfloat16'
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validation_data:
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input_path: 'imagenet-2012-tfrecord/valid*'
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is_training: false
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global_batch_size: 4096
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dtype: 'bfloat16'
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drop_remainder: false
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trainer:
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train_steps: 312000 # 1000 epochs
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validation_steps: 12
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validation_interval: 312
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steps_per_loop: 312 # NUM_EXAMPLES (1281167) // global_batch_size
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summary_interval: 312
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checkpoint_interval: 312
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optimizer_config:
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optimizer:
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type: 'rmsprop'
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rmsprop:
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rho: 0.9
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momentum: 0.9
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epsilon: 0.002
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learning_rate:
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type: 'exponential'
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exponential:
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initial_learning_rate: 0.01
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decay_steps: 936 # 3 * steps_per_epoch
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decay_rate: 0.99
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staircase: true
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ema:
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average_decay: 0.9999
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trainable_weights_only: false
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warmup:
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type: 'linear'
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linear:
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warmup_steps: 1560
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warmup_learning_rate: 0.001

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