本文整理匯總了Python中tensor2tensor.models.transformer.transformer_base方法的典型用法代碼示例。如果您正苦於以下問題：Python transformer.transformer_base方法的具體用法？Python transformer.transformer_base怎麽用？Python transformer.transformer_base使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類tensor2tensor.models.transformer的用法示例。
在下文中一共展示了transformer.transformer_base方法的15個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: iwslt_base
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def iwslt_base():
"""Set of hyperparameters."""
# Model architecture flags.
hparams = transformer.transformer_base()
hparams.num_hidden_layers = 5
hparams.hidden_size = 256
hparams.filter_size = 1024
hparams.num_heads = 4
# Other flags.
hparams.summarize_grads = False
hparams.summarize_vars = False
# Optimization-related flags.
hparams.clip_grad_norm = 1.0
hparams.learning_rate_decay_scheme = "noam"
hparams.learning_rate_warmup_steps = 8000
hparams.learning_rate = 0.2
hparams.learning_rate_schedule = (
"constant*linear_warmup*rsqrt_decay*rsqrt_hidden_size")
hparams.learning_rate_constant = 2.0
hparams.add_hparam("predict_target_length", True)
hparams.add_hparam("lendiff_bound", 30)
hparams = update_hparams_for_tpu(hparams)
hparams.add_hparam("pos_attn", False)
return hparams 示例2: _apply_encoder_layer
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def _apply_encoder_layer(translation_layer, output_depth, nonpadding_list):
"""Applies an encoder layer with basic arguments."""
input_tensor = tf.random_uniform(
[_BATCH_SIZE, _TOTAL_SEQUENCE_LENGTH, _INPUT_DEPTH]) / 4.0
nonpadding = tf.constant(nonpadding_list)
residual_tensor = tf.random_uniform(
[_BATCH_SIZE, _TOTAL_SEQUENCE_LENGTH, output_depth])
hparams = transformer.transformer_base()
return translation_layer.apply_layer(
input_tensor,
residual_tensor,
output_depth,
tf.nn.relu,
hparams,
"",
mask_future=False,
nonpadding=nonpadding,
layer_preprocess_fn=None,
postprocess_dropout=True) 示例3: universal_transformer_small
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def universal_transformer_small():
hparams = transformer.transformer_base()
hparams = update_hparams_for_universal_transformer(hparams)
return hparams 示例4: transformer_teeny
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_teeny():
hparams = transformer.transformer_base()
hparams.num_rec_steps = 2
hparams.hidden_size = 128
hparams.filter_size = 128
hparams.num_heads = 2
return hparams 示例5: transformer_aux_base
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_aux_base():
"""Set of hyperparameters."""
hparams = transformer.transformer_base()
hparams.shared_embedding_and_softmax_weights = False
hparams.add_hparam("shift_values", "1,2,3,4")
return hparams 示例6: wmt_enro_tpu
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def wmt_enro_tpu():
"""HParams for Transformer model on TPU."""
hparams = transformer.transformer_base()
hparams = transformer.update_hparams_for_tpu(hparams)
hparams.batch_size = 512
return hparams 示例7: iwslt_baseline_gpu
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def iwslt_baseline_gpu():
"""HParams for Transformer model on TPU."""
hparams = transformer.transformer_base()
hparams.hidden_size = 256
hparams.filter_size = 1024
hparams.num_hidden_layers = 5
hparams.num_heads = 2
hparams.layer_prepostprocess_dropout = 0.1
hparams.attention_dropout = 0.1
hparams.relu_dropout = 0.1
hparams.dropout = 0.1
return hparams 示例8: iwslt_baseline_tpu
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def iwslt_baseline_tpu():
"""HParams for Transformer model on TPU."""
hparams = transformer.transformer_base()
transformer.update_hparams_for_tpu(hparams)
hparams.hidden_size = 256
hparams.filter_size = 1024
hparams.num_hidden_layers = 5
hparams.num_heads = 2
hparams.layer_prepostprocess_dropout = 0.1
hparams.attention_dropout = 0.1
hparams.relu_dropout = 0.1
hparams.dropout = 0.1
hparams.add_hparam("pos_attn", False)
return hparams 示例9: universal_transformer_base_fp16
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def universal_transformer_base_fp16():
hparams = transformer.transformer_base()
hparams = update_hparams_for_universal_transformer(hparams)
hparams.activation_dtype = "float16"
return hparams 示例10: transformer_teeny
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_teeny():
hparams = transformer.transformer_base()
hparams.hidden_size = 128
hparams.filter_size = 128
hparams.num_heads = 2
return hparams 示例11: transformer_base_bs1
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_base_bs1():
hparams = transformer.transformer_base()
hparams.add_hparam("block_size", 1)
return hparams 示例12: transformer_base_bs2
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_base_bs2():
hparams = transformer.transformer_base()
hparams.add_hparam("block_size", 2)
return hparams 示例13: transformer_base_bs4
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_base_bs4():
hparams = transformer.transformer_base()
hparams.add_hparam("block_size", 4)
return hparams 示例14: transformer_base_bs5
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_base_bs5():
hparams = transformer.transformer_base()
hparams.add_hparam("block_size", 5)
return hparams 示例15: transformer_base_bs6
# 需要導入模塊: from tensor2tensor.models import transformer [as 別名]
# 或者: from tensor2tensor.models.transformer import transformer_base [as 別名]
def transformer_base_bs6():
hparams = transformer.transformer_base()
hparams.add_hparam("block_size", 6)
return hparams