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Commit efe2fe48 authored by Maja Jablonska's avatar Maja Jablonska
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Added config template file

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1 merge request!46Merge COMBO 3.0 into master
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combo/config.template.json 0 → 100644
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View file @ efe2fe48
{
"model": {
"type": "semantic_multitask",
"parameters": {
"dependency_relation": {
"type": "combo_dependency_parsing_from_vocab",
"parameters": {
"dependency_projection_layer": {
"type": "linear_layer",
"parameters": {
"activation": { "type": "tanh", "parameters": {} },
"dropout_rate": 0.25,
"in_features": 1024,
"out_features": 128
}
},
"head_predictor": {
"type": "head_prediction",
"parameters": {
"cycle_loss_n": 0,
"dependency_projection_layer": {
"type": "linear_layer",
"parameters": {
"activation": { "type": "tanh", "parameters": {} },
"in_features": 1024,
"out_features": 512
}
},
"head_projection_layer": {
"type": "linear_layer",
"parameters": {
"activation": { "type": "tanh", "parameters": {} },
"in_features": 1024,
"out_features": 512
}
}
}
},
"head_projection_layer": {
"type": "linear_layer",
"parameters": {
"activation": { "type": "tanh", "parameters": {} },
"dropout_rate": 0.25,
"in_features": 1024,
"out_features": 128
}
},
"vocab_namespace": "deprel_labels"
}
},
"lemmatizer": {
"type": "combo_lemma_predictor_from_vocab",
"parameters": {
"activations": [
{ "type": "gelu", "parameters": {} },
{ "type": "gelu", "parameters": {} },
{ "type": "gelu", "parameters": {} },
{ "type": "linear", "parameters": {} }
],
"char_vocab_namespace": "token_characters",
"dilation": [1, 2, 4, 1],
"embedding_dim": 300,
"filters": [256, 256, 256],
"input_projection_layer": {
"type": "linear_layer",
"parameters": {
"activation": { "type": "tanh", "parameters": {} },
"dropout_rate": 0.25,
"in_features": 1024,
"out_features": 32
}
},
"kernel_size": [3, 3, 3, 1],
"lemma_vocab_namespace": "lemma_characters",
"padding": [1, 2, 4, 0],
"stride": [1, 1, 1, 1]
}
},
"loss_weights": {
"deprel": 0.8,
"feats": 0.2,
"head": 0.2,
"lemma": 0.05,
"semrel": 0.05,
"upostag": 0.05,
"xpostag": 0.05
},
"morphological_feat": {
"type": "combo_morpho_from_vocab",
"parameters": {
"activations": [
{ "type": "tanh", "parameters": {} },
{ "type": "linear", "parameters": {} }
],
"dropout": [0.25, 0.0],
"hidden_dims": [128],
"input_dim": 1024,
"num_layers": 2,
"vocab_namespace": "feats_labels"
}
},
"regularizer": {
"type": "base_regularizer",
"parameters": {
"regexes": [
[
".*conv1d.*",
{ "type": "l2_regularizer", "parameters": { "alpha": 1e-6 } }
],
[
".*forward.*",
{ "type": "l2_regularizer", "parameters": { "alpha": 1e-6 } }
],
[
".*backward.*",
{ "type": "l2_regularizer", "parameters": { "alpha": 1e-6 } }
],
[
".*char_embed.*",
{ "type": "l2_regularizer", "parameters": { "alpha": 1e-5 } }
]
]
}
},
"seq_encoder": {
"type": "combo_encoder",
"parameters": {
"layer_dropout_probability": 0.33,
"stacked_bilstm": {
"type": "combo_stacked_bilstm",
"parameters": {
"hidden_size": 512,
"input_size": 164,
"layer_dropout_probability": 0.33,
"num_layers": 2,
"recurrent_dropout_probability": 0.33
}
}
}
},
"text_field_embedder": {
"type": "base_text_field_embedder",
"parameters": {
"token_embedders": {
"char": {
"type": "char_embeddings_token_embedder",
"parameters": {
"dilated_cnn_encoder": {
"type": "dilated_cnn",
"parameters": {
"activations": [
{ "type": "gelu", "parameters": {} },
{ "type": "gelu", "parameters": {} },
{ "type": "linear", "parameters": {} }
],
"dilation": [1, 2, 4],
"filters": [512, 256, 64],
"input_dim": 64,
"kernel_size": [3, 3, 3],
"padding": [1, 2, 4],
"stride": [1, 1, 1]
}
},
"embedding_dim": 64
}
},
"token": {
"type": "transformers_word_embedder",
"parameters": { "projection_dim": 100 }
}
}
}
},
"upos_tagger": {
"type": "feedforward_predictor_from_vocab",
"parameters": {
"vocab_namespace": "upostag_labels",
"input_dim": 1024,
"num_layers": 2,
"hidden_dims": [64],
"activations": [
{ "type": "tanh", "parameters": {} },
{ "type": "linear", "parameters": {} }
],
"dropout": [0.25, 0.0]
}
},
"xpos_tagger": {
"type": "feedforward_predictor_from_vocab",
"parameters": {
"vocab_namespace": "xpostag_labels",
"input_dim": 1024,
"num_layers": 2,
"hidden_dims": [64],
"activations": [
{ "type": "tanh", "parameters": {} },
{ "type": "linear", "parameters": {} }
],
"dropout": [0.25, 0.0]
}
}
}
},
"data_loader": {
"type": "simple_data_loader_from_dataset_reader",
"parameters": {
"reader": {
"type": "conllu_dataset_reader",
"parameters": {
"features": ["token", "char"],
"tokenizer": {
"type": "lambo_tokenizer"
},
"lemma_indexers": {
"char": {
"type": "characters_const_padding_token_indexer",
"parameters": {
"tokenizer": {
"type": "character_tokenizer",
"parameters": {
"end_tokens": ["__END__"],
"start_tokens": ["__START__"]
}
},
"min_padding_length": 32,
"namespace": "lemma_characters"
}
}
},
"targets": ["deprel", "feats", "head", "lemma", "upostag", "xpostag"],
"token_indexers": {
"char": {
"type": "characters_const_padding_token_indexer",
"parameters": {
"tokenizer": {
"type": "character_tokenizer",
"parameters": {
"end_tokens": ["__END__"],
"start_tokens": ["__START__"]
}
},
"min_padding_length": 32
}
},
"token": {
"type": "pretrained_transformer_mismatched_fixed_token_indexer",
"parameters": { "model_name": "allegro/herbert-base-cased" }
}
},
"use_sem": false
}
},
"batch_size": 1,
"shuffle": true,
"batches_per_epoch": 64,
"quiet": false
}
},
"dataset_reader": {
"type": "conllu_dataset_reader",
"parameters": {
"features": ["token", "char"],
"tokenizer": {
"type": "lambo_tokenizer"
},
"lemma_indexers": {
"char": {
"type": "characters_const_padding_token_indexer",
"parameters": {
"tokenizer": {
"type": "character_tokenizer",
"parameters": {
"end_tokens": ["__END__"],
"start_tokens": ["__START__"]
}
},
"min_padding_length": 32,
"namespace": "lemma_characters"
}
}
},
"targets": ["deprel", "feats", "head", "lemma", "upostag", "xpostag"],
"token_indexers": {
"char": {
"type": "characters_const_padding_token_indexer",
"parameters": {
"tokenizer": {
"type": "character_tokenizer",
"parameters": {
"end_tokens": ["__END__"],
"start_tokens": ["__START__"]
}
},
"min_padding_length": 32
}
},
"token": {
"type": "pretrained_transformer_mismatched_fixed_token_indexer",
"parameters": { "model_name": "allegro/herbert-base-cased" }
}
},
"use_sem": false
}
},
"training": {},
"model_name": "allegro/herbert-base-cased"
}
combo/modules/archival.py
+ 3
− 3
View file @ efe2fe48
......@@ -81,7 +81,7 @@ def archive(model: Model,
with (TemporaryDirectory(os.path.join('tmp')) as t,
BytesIO() as out_stream,
tarfile.open(os.path.join(serialization_dir, 'model.tar.gz'), 'w|gz') as tar_file):
add_to_tar(tar_file, out_stream, json.dumps(parameters).encode(), 'config.json')
add_to_tar(tar_file, out_stream, json.dumps(parameters).encode(), 'config.template.json')
weights_path = os.path.join(t, 'weights.th')
torch.save(model.state_dict(), weights_path)
tar_file.add(weights_path, 'weights.th')
......@@ -100,7 +100,7 @@ def extracted_archive(resolved_archive_file, cleanup=True):
with tarfile.open(resolved_archive_file) as archive:
subdir_and_files = [
tarinfo for tarinfo in archive.getmembers()
if (any([tarinfo.name.endswith(f) for f in ['config.json', 'weights.th']])
if (any([tarinfo.name.endswith(f) for f in ['config.template.json', 'weights.th']])
or 'vocabulary' in tarinfo.name)
]
for f in subdir_and_files:
......@@ -127,7 +127,7 @@ def load_archive(url_or_filename: Union[PathLike, str],
with extracted_archive(rarchive_file) as archive_file:
model = Model.load(archive_file, cuda_device=cuda_device)
config_path = os.path.join(archive_file, 'config.json')
config_path = os.path.join(archive_file, 'config.template.json')
with open(config_path, 'r') as f:
config = json.load(f)
......
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