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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def transformer_mlperf_tpu():
 """HParams for Transformer model on TPU for MLPerf on TPU 2x2."""

  hparams = transformer_base_v3()
  hparams.mlperf_mode = True
  hparams.symbol_modality_num_shards = 1
  hparams.max_length = 256  # ignored when using "_packed" problems
  hparams.batch_size = 2048  # per-chip batch size matches the reference model
  hparams.hidden_size = 1024
  hparams.filter_size = 4096
  hparams.num_heads = 16
  hparams.attention_dropout_broadcast_dims = "0,1"  # batch, heads
  hparams.relu_dropout_broadcast_dims = "1"  # length
  hparams.layer_prepostprocess_dropout_broadcast_dims = "1"  # length
  return hparams