modeling¶
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class
ProphetNetModel
(vocab_size, bos_token_id=102, pad_token_id=0, eos_token_id=102, hidden_size=1024, decoder_start_token_id=102, max_position_embeddings=512, activation_function='gelu', activation_dropout=0.1, dropout=0.1, relative_max_distance=128, ngram=2, num_buckets=32, encoder_ffn_dim=4096, num_encoder_attention_heads=16, num_encoder_layers=12, decoder_ffn_dim=4096, num_decoder_attention_heads=16, num_decoder_layers=12, attention_dropout=0.1, init_std=0.02, eps=0.1, add_cross_attention=True, disable_ngram_loss=False, **kwargs)[source]¶ Bases:
paddlenlp.transformers.prophetnet.modeling.ProphetNetPretrainedModel
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forward
(input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, encoder_output: Optional[Tuple] = None, use_cache=True, past_key_values=None)[source]¶ Defines the computation performed at every call. Should be overridden by all subclasses.
- Parameters
*inputs (tuple) – unpacked tuple arguments
**kwargs (dict) – unpacked dict arguments
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class
ProphetNetPretrainedModel
(*args, **kwargs)[source]¶ Bases:
paddlenlp.transformers.model_utils.PretrainedModel
An abstract class for pretrained Prophetnet models. It provides Prophetnet related
model_config_file
,pretrained_init_configuration
,resource_files_names
,pretrained_resource_files_map
,base_model_prefix
for downloading and loading pretrained models.-
base_model_class
¶ alias of
paddlenlp.transformers.prophetnet.modeling.ProphetNetModel
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class
ProphetNetEncoder
(word_embeddings, vocab_size, hidden_size, pad_token_id, max_position_embeddings, encoder_ffn_dim, activation_function, activation_dropout, attention_dropout, dropout, num_encoder_attention_heads, num_encoder_layers, init_std)[source]¶ Bases:
paddlenlp.transformers.prophetnet.modeling.ProphetNetPretrainedModel
- word_embeddings (
paddle.nn.Embeddings
of shape(config.vocab_size, config.hidden_size)
,optional
): The word embedding parameters. This can be used to initialize
ProphetNetEncoder
with pre-defined word embeddings instead of randomly initialized word embeddings.
- word_embeddings (
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class
ProphetNetDecoder
(word_embeddings, vocab_size, hidden_size, pad_token_id, max_position_embeddings, relative_max_distance, ngram, num_buckets, num_decoder_attention_heads, decoder_ffn_dim, activation_function, activation_dropout, dropout, attention_dropout, add_cross_attention, num_decoder_layers, init_std)[source]¶ Bases:
paddlenlp.transformers.prophetnet.modeling.ProphetNetPretrainedModel
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forward
(input_ids=None, attention_mask=None, encoder_hidden_states=None, encoder_attention_mask=None, past_key_values=None, use_cache=True)[source]¶ Defines the computation performed at every call. Should be overridden by all subclasses.
- Parameters
*inputs (tuple) – unpacked tuple arguments
**kwargs (dict) – unpacked dict arguments
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class
ProphetNetForConditionalGeneration
(prophetnet)[source]¶ Bases:
paddlenlp.transformers.prophetnet.modeling.ProphetNetPretrainedModel
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forward
(input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, encoder_output=None, labels=None, use_cache=True, past_key_values=None)[source]¶ Defines the computation performed at every call. Should be overridden by all subclasses.
- Parameters
*inputs (tuple) – unpacked tuple arguments
**kwargs (dict) – unpacked dict arguments
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