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update
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@@ -49,7 +49,6 @@ word2idx = {u:i for i, u in enumerate(vocab)}
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idx2word = np.array(vocab)
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# sequence length to use for the transformer
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# must match the model being fine-tuned
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seq_length = args.sequence_len
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@@ -155,8 +154,7 @@ run_config = tf.contrib.tpu.RunConfig(
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run_config = tf.contrib.tpu.RunConfig(
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model_dir=args.model_dir,
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session_config=tf.ConfigProto(allow_soft_placement=True, log_device_placement=True),
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tpu_config=tf.contrib.tpu.TPUConfig(iterations_per_loop=100, num_cores_per_replica=1, input_partition_dims=[[1, 1], [1, 1]], per_host_input_for_training=3))
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session_config=tf.ConfigProto(allow_soft_placement=True, log_device_placement=True))
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tf.logging.set_verbosity(tf.logging.INFO)
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estimator_model = tf.keras.estimator.model_to_estimator(keras_model=model, config=run_config)
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