Module: am¶
Defined in animius/__init__.py.
Overview¶
Modules¶
Classes¶
class ChatbotData
class CombinedPredictionData
class IntentNERData
class SpeakerVerificationData
am.Commands¶
Defined in animius/Commands.py.
Class am.Commands contains the whole details of console commands, such as their arguments or their descriptions.
__init__¶
Args:
- console (am.Console) -- reference to an am.Console object.
Properties¶
None
Methods¶
__iter__¶
__iter__()
Returns an iterator for the command dict.
Args: None
Returns: A reference to the iterator for the command dict.
__getitem__¶
__getitem__(item)
Returns detail information of a command.
For example, __getitem__('exportWaifu') will return:
1 2 3 4 5 6 7 8 9 | [
console.export_waifu,
{
'-n': ['name', 'str', 'Name of waifu'],
'-p': ['path', 'str', 'Path to export file']
},
'Export a waifu',
"exportWaifu -n 'waifu name' -p 'path_name'"
]
|
Args:
- item (
str) -- command name.
Returns: A dict similar to the example above.
am.Console¶
Defined in animius/Console.py.
Class am.Console includes the method corresponding to each command, a queue which controls the workflow, and a command handler.
__init__¶
Args:
- init_directory (
str) -- the path to the directory in which animius saves resources. (Optional)
Properties¶
Methods¶
am.Console.server¶
am.Console.server(console, port, local=True, password='', max_clients=10)
Start socket server on specific port.
Args:
-
console (
am.Console) -- reference to an am.Console object. -
port (
int) -- specific port which the socket server listening on. -
local (
boolean) -- whether or not the server runs on local address. (as known as '127.0.0.1' or 'localhost') -
password (
str) -- password which requires when clients creating a connection with the socket server. (optional) -
max_clients (
int) -- specific number of clients the server can communicate with. (optional)
Returns:
The reference to a thread object which socket server is running on.
am.Model¶
am.Model is an abstract class which is the template of other models.
Defined in animius/Model.py.
__init__¶
Args: None
Properties¶
Methods¶
DEFAULT_CONFIG¶
am.Model.DEFAULT_CONFIG()
Get defaul model config.
Args: None
Returns: A dict of model config.
DEFAULT_MODEL_STRUCTURE¶
am.Model.DEFAULT_MODEL_STRUCTURE()
Get defaul model structure of specific model.
Args: None
Returns: A dict of model structure.
DEFAULT_HYPERPARAMETERS¶
am.Model.DEFAULT_HYPERPARAMETERS()
Get defaul hyperparameters.
Args: None
Returns: A dict of hyperparameters.
build_graph¶
'build_graph' is a abstract method.
init_tensorflow¶
init_tensorflow(graph=None, init_param=True, init_sess=True)
Initialize TensorFlow.
Args:
-
graph (
tf.Graph) -- reference to a tf.Graph object. (Optional) -
init_param* (
bool) -- whether or not to initialize parameters. (Optional) -
init_sess* (
bool) -- whether or not to initialize tf.Session. (Optional)
Returns: None.
init_hyperdash¶
init_hyperdash(name)
Initialize Hyperdash.
Args:
- name (
str) -- name of hyperdash.
Returns: None
init_embedding¶
init_embedding(word_embedding_placeholder)
Initialize embedding.
Args:
- word_embedding_placeholder (
str) -- name of hyperdash.
model_config¶
model_config()
Get Model Config of specific model.
Args: None
Returns: The reference to a am.ModelConfig object.
save¶
save(directory=None, name='model', meta=True, graph=False)
Save model to local file.
Args:
-
directory (
str) -- directory where you want to save file. (Optional) -
name* (
str) -- name of model file. (Optional) -
meta* (
boolean) -- whether or not to save meta file. (Optional) -
graph* (
boolean) -- whether or not to save graph. (Optional)
Returns: directory where model file saves.
load (Class method)¶
load(cls, directory, name='model', data=None)
Load model from local file.
Args:
-
cls (
str) -- type of model, must be included in ['SpeakerVerification', 'Chatbot', 'IntentNER', 'CombinedChatbot']. -
directory (
str) -- directory where you want to save model file. -
name* (
str) -- name of model file. (Optional) -
data* (
str) -- name of data to load. (Optional)
Returns: The reference to the am.Model object.
am.ModelConfig¶
Defined in animius/ModelConfig.py.
__init__¶
Args:
-
cls (
str) -- type of model config, must be included in ['SpeakerVerification', 'Chatbot', 'IntentNER', 'CombinedChatbot']. -
config (
dict) -- dict of config. (Optional) -
hyperparameters (
dict) -- dict of hyperparameters. (Optional) -
model_structure (
dict) -- dict of model structures. (Optional)
Properties¶
config
hyperparameters
model_structure
Methods¶
apply_defaults¶
apply_defaults()
Apply default model config.
For example:
1 2 | config = am.ModelConfig(cls="Chatbot") config.apply_defaults() |
Args: None
Returns: None
save¶
save(directory, name='model_config')
Save model config to local file.
Args:
-
directory (
str) -- directory where you want to save config file. -
name* (
str) -- name of model config file. (Optional)
Returns: directory where config file saves.
load (Class method)¶
load(cls, directory, name='model_config')
Load model config from local file.
Args:
-
cls (
str) -- type of model config, must be included in ['SpeakerVerification', 'Chatbot', 'IntentNER', 'CombinedChatbot']. -
directory (
str) -- directory where you want to save config file. -
name* (
str) -- name of model config file. (Optional)
Returns: The reference to the am.ModelConfig object.
am.SubtitleParser¶
Defined in animius/ParseSubtitle.py.
__init__¶
Args: None
Methods¶
load¶
load(subtitle_path)
Load subtitle (SSA file) from local file.
Args:
- subtitle_path* (
str) -- path to subtitle file.
Returns: None
parse_audio_sentences¶
parse_audio_sentences()
Add audio sentences from subtitle file.
Args: None
Returns: None
slice_audio¶
slice_audio(audio_path, save_path)
Slice audio and save results into specific path.
Args:
-
audio_path* (
str) -- path to audio file. -
save_path* (
str) -- path to save results.
detect_conversation¶
detect_conversation(speaking, time_gap=5000)
Args:
Returns:
am.Waifu¶
Defined in animius/Waifu.py.
__init__¶
am.Waifu(name, models=None, description='', image='')
Args:
-
name* (
str) -- name of waifu. -
models* (
dict) -- dict of models. (Optional) -
description* (
str) -- description of waifu. (Optional) -
image* (
str) -- image of waifu. (Optional)
Methods¶
add_combined_prediction_model¶
add_combined_prediction_model(directory, name)
Add combined prediction model to specific waifu.
Args:
-
directory* (
str) -- path to the combined prediction model. -
name* (
str) -- name of combined prediction model.
Returns: None
load_combined_prediction_model¶
load_combined_prediction_model()
Load combined prediction model to specific waifu.
Args: None
Returns: None
build_input¶
add_regex¶
add_regex(regex_rule, isIntentNER, result)
Add regex rule.
For example:
testWaifu.add_regex('how's the weather in (.+)', True, 'getWeather')
testWaifu.add_regex('good morning', False, 'Good morning!')
Args:
-
regex_rule* (
str) -- regex rule. -
isIntentNER* (
boolean) -- whether or not the regex rule will return Intent and NER. -
result* (
str) -- string which the regex rule will return.
Returns: None
predict¶
predict(sentence)
Predict results using regex rules and model.
Args:
- sentence* (
str) -- sentence which will be predicted by waifu.
Returns:
For general messages, the format of returned value will be: {'message': string}.
For commands, the format of returned value will be: {'intent': intent, 'ner': [ner, ner_sentence]}.
save¶
save(directory, name='waifu')
Save waifu to local files.
Args:
-
directory* (
str) -- path to save files. -
name* (
str) -- name of waifu to save.
Returns: Directory to saved file.
load (Class method)¶
am.Waifu.load(directory, name='waifu')
Load Waifu from local files.
Args:
-
directory* (
str) -- path to save files. -
name* (
str) -- name of waifu to load.
Returns: a reference to am.Waifu object.
am.WordEmbedding¶
Defined in animius/WordEmbedding.py.
__init__¶
Args: None
Methods¶
create_embedding¶
create_embedding(glove_path, vocab_size=100000)
Create word embeddings from pre-trained word embeddings file.
Since Animius natively does not support word embedding training, you have to download pre-trained word embeddings such as GloVe.
Args:
-
glove_path* (
str) -- path to pre-trained word embeddings. -
vocab_size* (
int) -- amount of vocabularies which will be contained in the word embedding. (Optional)
Returns: None
save¶
save(directory, name='embedding')
Save word embeddings to local file.
Args:
-
directory (
str) -- directory where you want to save word embeddings file. -
name* (
str) -- name of word embeddings file. (Optional)
Returns: directory where word embedding file saves.
load (Class method)¶
am.WordEmbedding.load(directory, name='embedding')
Load embedding from local file.
Args:
-
directory (
str) -- directory where you want to save word embeddings file. -
name* (
str) -- name of word embeddings file. (Optional)
Returns: The reference to the am.WordEmbeddings object.