chore: remove old train logic

deeppavlov · Feb 8, 2018 · 40d4c9e · 40d4c9e
1 parent ae3dfca
commit 40d4c9e
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Showing 3 changed files with 7 additions and 78 deletions.
diff --git a/deeppavlov/core/commands/train.py b/deeppavlov/core/commands/train.py
@@ -26,78 +26,20 @@
 from deeppavlov.core.common.file import read_json
 from deeppavlov.core.common.registry import model as get_model
 from deeppavlov.core.common.metrics_registry import get_metrics_by_names
-from deeppavlov.core.commands.infer import build_agent_from_config
 from deeppavlov.core.common.params import from_params
 from deeppavlov.core.data.dataset import Dataset
 from deeppavlov.core.models.inferable import Inferable
 from deeppavlov.core.models.trainable import Trainable
 from deeppavlov.core.common import paths
 
 
-# TODO pass paths to local model configs to agent config.
-
-
-def train_agent_models(config_path: str):
-    usr_dir = paths.USR_PATH
-    a = build_agent_from_config(config_path)
-
-    for skill_config in a.skill_configs:
-        model_config = skill_config['model']
-        model_name = model_config['name']
-
-        if issubclass(get_model(model_name), Trainable):
-            reader_config = skill_config['dataset_reader']
-            reader = from_params(get_model(reader_config['name']), {})
-            data = reader.read(reader_config.get('data_path', usr_dir))
-
-            dataset_config = skill_config['dataset']
-            dataset_name = dataset_config['name']
-            dataset = from_params(get_model(dataset_name), dataset_config, data=data)
-
-            model = from_params(get_model(model_name), model_config)
-            model.train(dataset)
-        else:
-            print('Model {} is not an instance of Trainable, skip training.'.format(model_name),
-                  file=sys.stderr)
-
-
-def train_model_from_config(config_path: str, mode='train'):
-    usr_dir = paths.USR_PATH
-    config = read_json(config_path)
-
-    reader_config = config['dataset_reader']
-    # NOTE: Why there are no params for dataset reader? Because doesn't have __init__()
-    reader = from_params(get_model(reader_config['name']), {})
-    data = reader.read(reader_config.get('data_path', usr_dir))
-
-    dataset_config = config['dataset']
-    dataset_name = dataset_config['name']
-    dataset = from_params(get_model(dataset_name), dataset_config, data=data)
-
-    vocabs = {}
-    if 'vocabs' in config:
-        for vocab_param_name, vocab_config in config['vocabs'].items():
-            vocab_name = vocab_config['name']
-            v = from_params(get_model(vocab_name), vocab_config, mode=mode)
-            v.train(dataset.iter_all('train'))
-            vocabs[vocab_param_name] = v
-
-    model_config = config['model']
-    model_name = model_config['name']
-    model = from_params(get_model(model_name), model_config, vocabs=vocabs, mode=mode)
-
-    model.train(dataset)
-
-    # The result is a saved to user_dir trained model.
-
-
 def _fit(model: Trainable, dataset: Dataset, train_config={}):
     model.fit(dataset.iter_all('train'))
     model.save()
     return model
 
 
-def train_experimental(config_path: str):
+def train_model_from_config(config_path: str):
     usr_dir = paths.USR_PATH
     config = read_json(config_path)
 

diff --git a/deeppavlov/deep.py b/deeppavlov/deep.py
@@ -23,7 +23,7 @@
 sys.path.append(str(p))
 
 from deeppavlov.core.commands.utils import set_usr_dir, get_usr_dir
-from deeppavlov.core.commands.train import train_experimental
+from deeppavlov.core.commands.train import train_model_from_config
 from deeppavlov.core.commands.infer import interact_model
 from telegram_utils.telegram_ui import interact_model_by_telegram
 
@@ -44,7 +44,7 @@ def main():
 
     try:
         if args.mode == 'train':
-            train_experimental(pipeline_config_path)
+            train_model_from_config(pipeline_config_path)
         elif args.mode == 'interact':
             interact_model(pipeline_config_path)
         elif args.mode == 'interactbot':

diff --git a/deeppavlov/run_model.py b/deeppavlov/run_model.py
@@ -14,35 +14,22 @@
 limitations under the License.
 """
 
-from deeppavlov.core.commands.train import train_experimental
+from deeppavlov.core.commands.train import train_model_from_config
 from deeppavlov.core.commands.infer import interact_model
 from deeppavlov.core.commands.utils import set_usr_dir, get_usr_dir
 
-# HCN_new
-# configs/go_bot/config.json
 
-# Speller
-# configs/error_model/config_en.json
-# configs/error_model/config_ru.json
-# configs/error_model/config_ru_custom_vocab.json
-
-# Intents classifier
-# configs/intents/config_dstc2.json
-
-# NER
-# configs/ner/slot_config.json
-
-PIPELINE_CONFIG_PATH = 'configs/intents/config_train.json'
+# PIPELINE_CONFIG_PATH = 'configs/intents/config_train.json'
 # PIPELINE_CONFIG_PATH = 'configs/ner/ner_dstc2_train.json'
 # PIPELINE_CONFIG_PATH = 'configs/ner/ner_conll2003_train.json'
 # PIPELINE_CONFIG_PATH = 'configs/ner/slot_config_train.json'
 # PIPELINE_CONFIG_PATH = 'configs/error_model/config_en.json'
 # PIPELINE_CONFIG_PATH = 'configs/error_model/config_ru.json'
-# PIPELINE_CONFIG_PATH = 'configs/go_bot/config_train.json'
+PIPELINE_CONFIG_PATH = 'configs/go_bot/config_train.json'
 set_usr_dir(PIPELINE_CONFIG_PATH)
 try:
     # train_model_from_config(PIPELINE_CONFIG_PATH)
-    train_experimental(PIPELINE_CONFIG_PATH)
+    train_model_from_config(PIPELINE_CONFIG_PATH)
     interact_model(PIPELINE_CONFIG_PATH)
 # remove if usr_dir is empty:
 finally: