Class: Transformers::XlmRoberta::XLMRobertaConfig
- Inherits:
-
PretrainedConfig
- Object
- PretrainedConfig
- Transformers::XlmRoberta::XLMRobertaConfig
- Defined in:
- lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb
Instance Attribute Summary collapse
-
#attention_probs_dropout_prob ⇒ Object
readonly
Returns the value of attribute attention_probs_dropout_prob.
-
#bos_token_id ⇒ Object
readonly
Returns the value of attribute bos_token_id.
-
#classifier_dropout ⇒ Object
readonly
Returns the value of attribute classifier_dropout.
-
#eos_token_id ⇒ Object
readonly
Returns the value of attribute eos_token_id.
-
#hidden_act ⇒ Object
readonly
Returns the value of attribute hidden_act.
-
#hidden_dropout_prob ⇒ Object
readonly
Returns the value of attribute hidden_dropout_prob.
-
#hidden_size ⇒ Object
readonly
Returns the value of attribute hidden_size.
-
#initializer_range ⇒ Object
readonly
Returns the value of attribute initializer_range.
-
#intermediate_size ⇒ Object
readonly
Returns the value of attribute intermediate_size.
-
#layer_norm_eps ⇒ Object
readonly
Returns the value of attribute layer_norm_eps.
-
#max_position_embeddings ⇒ Object
readonly
Returns the value of attribute max_position_embeddings.
-
#num_attention_heads ⇒ Object
readonly
Returns the value of attribute num_attention_heads.
-
#num_hidden_layers ⇒ Object
readonly
Returns the value of attribute num_hidden_layers.
-
#pad_token_id ⇒ Object
readonly
Returns the value of attribute pad_token_id.
-
#position_embedding_type ⇒ Object
readonly
Returns the value of attribute position_embedding_type.
-
#type_vocab_size ⇒ Object
readonly
Returns the value of attribute type_vocab_size.
-
#use_cache ⇒ Object
readonly
Returns the value of attribute use_cache.
-
#vocab_size ⇒ Object
readonly
Returns the value of attribute vocab_size.
Attributes inherited from PretrainedConfig
#_commit_hash, #add_cross_attention, #architectures, #chunk_size_feed_forward, #id2label, #is_decoder, #is_encoder_decoder, #output_attentions, #output_hidden_states, #problem_type, #pruned_heads, #tie_encoder_decoder, #tie_word_embeddings, #tokenizer_class
Instance Method Summary collapse
Methods inherited from PretrainedConfig
#_attn_implementation, #_dict, from_dict, from_pretrained, get_config_dict, #getattr, #hasattr, #method_missing, #name_or_path, #name_or_path=, #num_labels, #num_labels=, #respond_to_missing?, #to_dict, #to_diff_dict, #to_json_string, #to_s, #use_return_dict
Methods included from ClassAttribute
Constructor Details
#initialize(vocab_size: 30522, hidden_size: 768, num_hidden_layers: 12, num_attention_heads: 12, intermediate_size: 3072, hidden_act: "gelu", hidden_dropout_prob: 0.1, attention_probs_dropout_prob: 0.1, max_position_embeddings: 512, type_vocab_size: 2, initializer_range: 0.02, layer_norm_eps: 1e-12, pad_token_id: 1, bos_token_id: 0, eos_token_id: 2, position_embedding_type: "absolute", use_cache: true, classifier_dropout: nil, **kwargs) ⇒ XLMRobertaConfig
Returns a new instance of XLMRobertaConfig.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 27 def initialize( vocab_size: 30522, hidden_size: 768, num_hidden_layers: 12, num_attention_heads: 12, intermediate_size: 3072, hidden_act: "gelu", hidden_dropout_prob: 0.1, attention_probs_dropout_prob: 0.1, max_position_embeddings: 512, type_vocab_size: 2, initializer_range: 0.02, layer_norm_eps: 1e-12, pad_token_id: 1, bos_token_id: 0, eos_token_id: 2, position_embedding_type: "absolute", use_cache: true, classifier_dropout: nil, **kwargs ) super(pad_token_id: pad_token_id, bos_token_id: bos_token_id, eos_token_id: eos_token_id, **kwargs) @vocab_size = vocab_size @hidden_size = hidden_size @num_hidden_layers = num_hidden_layers @num_attention_heads = num_attention_heads @hidden_act = hidden_act @intermediate_size = intermediate_size @hidden_dropout_prob = hidden_dropout_prob @attention_probs_dropout_prob = attention_probs_dropout_prob @max_position_embeddings = @type_vocab_size = type_vocab_size @initializer_range = initializer_range @layer_norm_eps = layer_norm_eps @position_embedding_type = @use_cache = use_cache @classifier_dropout = classifier_dropout end |
Dynamic Method Handling
This class handles dynamic methods through the method_missing method in the class Transformers::PretrainedConfig
Instance Attribute Details
#attention_probs_dropout_prob ⇒ Object (readonly)
Returns the value of attribute attention_probs_dropout_prob.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def attention_probs_dropout_prob @attention_probs_dropout_prob end |
#bos_token_id ⇒ Object (readonly)
Returns the value of attribute bos_token_id.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def bos_token_id @bos_token_id end |
#classifier_dropout ⇒ Object (readonly)
Returns the value of attribute classifier_dropout.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def classifier_dropout @classifier_dropout end |
#eos_token_id ⇒ Object (readonly)
Returns the value of attribute eos_token_id.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def eos_token_id @eos_token_id end |
#hidden_act ⇒ Object (readonly)
Returns the value of attribute hidden_act.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def hidden_act @hidden_act end |
#hidden_dropout_prob ⇒ Object (readonly)
Returns the value of attribute hidden_dropout_prob.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def hidden_dropout_prob @hidden_dropout_prob end |
#hidden_size ⇒ Object (readonly)
Returns the value of attribute hidden_size.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def hidden_size @hidden_size end |
#initializer_range ⇒ Object (readonly)
Returns the value of attribute initializer_range.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def initializer_range @initializer_range end |
#intermediate_size ⇒ Object (readonly)
Returns the value of attribute intermediate_size.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def intermediate_size @intermediate_size end |
#layer_norm_eps ⇒ Object (readonly)
Returns the value of attribute layer_norm_eps.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def layer_norm_eps @layer_norm_eps end |
#max_position_embeddings ⇒ Object (readonly)
Returns the value of attribute max_position_embeddings.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def @max_position_embeddings end |
#num_attention_heads ⇒ Object (readonly)
Returns the value of attribute num_attention_heads.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def num_attention_heads @num_attention_heads end |
#num_hidden_layers ⇒ Object (readonly)
Returns the value of attribute num_hidden_layers.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def num_hidden_layers @num_hidden_layers end |
#pad_token_id ⇒ Object (readonly)
Returns the value of attribute pad_token_id.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def pad_token_id @pad_token_id end |
#position_embedding_type ⇒ Object (readonly)
Returns the value of attribute position_embedding_type.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def @position_embedding_type end |
#type_vocab_size ⇒ Object (readonly)
Returns the value of attribute type_vocab_size.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def type_vocab_size @type_vocab_size end |
#use_cache ⇒ Object (readonly)
Returns the value of attribute use_cache.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def use_cache @use_cache end |
#vocab_size ⇒ Object (readonly)
Returns the value of attribute vocab_size.
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# File 'lib/transformers/models/xlm_roberta/configuration_xlm_roberta.rb', line 21 def vocab_size @vocab_size end |