def setup_args(parser=None):
if parser is None:
# parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser = ParlaiParser(add_model_args=True)
parser.set_params(
model='legacy:seq2seq:0',
model_file='models:convai2/seq2seq/convai2_self_seq2seq_model',
dict_file='models:convai2/seq2seq/convai2_self_seq2seq_model.dict',
dict_lower=True,
)
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.add_argument(
'-sc',
'--script-chateval',
type='bool',
default=False,
dest='chat_script',
help='Chateval script read file'
'True: chateval evaluation, False: single-turn conversation with agent(original model)',
)
parser.add_argument(
'-scip',
'--chateval-input-path',
type=str,
default=None,
dest='script_input_path',
help='Chateval script input path',
)
parser.add_argument(
'-scop',
'--chateval-output-path',
type=str,
default=None,
dest='script_output_path',
help='Chateval result output path',
)
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.add_argument(
'--save-world-logs',
type='bool',
default=False,
help='Saves a jsonl file containing all of the task examples and '
'model replies. Must also specify --report-filename.',
)
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-sc',
'--script-chateval',
type='bool',
default=False,
dest='chat_script',
help='Chateval script read file'
'True: chateval evaluation, False: single-turn conversation with agent(original model)',
)
parser.add_argument(
'-scip',
'--chateval-input-path',
type=str,
default=None,
dest='script_input_path',
help='Chateval script input path',
)
parser.add_argument(
'-scop',
'--chateval-output-path',
type=str,
default=None,
dest='script_output_path',
help='Chateval result output path',
)
parser.add_argument(
'--chateval-multi-num',
type=int,
default=0,
dest='chateval_multi_num',
help='True is chateval multiturn setting, turn coverage count.',
)
parser.add_argument(
'--chateval-multi',
type='bool',
default=False,
hidden=True,
dest='chateval_multi',
help='True is chateval multiturn setting, False just single turn.',
)
parser.set_defaults(model_file='models:convai2/kvmemnn/model')
LocalHumanAgent.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser, partial_opt=None)
SelfFeedingAgent.add_cmdline_args(parser, partial_opt=None)
parser.set_defaults(history_size=2)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(
True, True, 'Interactive chat with a model on the command line'
)
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser)
#WorldLogger.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True)
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument('--display-prettify', type='bool', default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates')
parser.add_argument('--display-ignore-fields', type=str,
default='label_candidates,text_candidates',
help='Do not display these fields')
LocalHumanAgent.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.add_argument(
'-rf',
'--report-filename',
type=str,
default='',
help='Saves a json file of the evaluation report either as an '
'extension to the model-file (if begins with a ".") or a whole '
'file path. Set to the empty string to not save at all.',
)
parser.add_argument(
'--save-world-logs',
type='bool',
default=False,
help='Saves a jsonl file containing all of the task examples and '
'model replies. Must also specify --report-filename.',
)
parser.add_argument('--world-logs-format',
type=str,
default='parlai',
choices=['jsonl', 'parlai', 'forever'],
help='File format to save chat logs. (default parlai)')
parser.add_argument('-ltim', '--log-every-n-secs', type=float, default=2)
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser)
WorldLogger.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
'''
parser.add_argument(
'-hi',
'--history',
type=str,
default='',
help='context history beyond the initial query',
)
parser.add_argument(
'-hist',
'--human_input',
type=str,
default='Hello.',
help='Human input message to the agent.',
)
parser.add_argument(
'-sampcans',
'--sampled_candidates',
type=str,
default='',
help='Sampled candidates',
)
'''
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(
True, True, 'Interactive chat with a model on the command line')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-add-fields',
type=str,
default='',
help=
'Display these fields when verbose is off (e.g., "--display-add-fields label_candidates,beam_texts")',
)
parser.add_argument(
'-it',
'--interactive-task',
type='bool',
default=True,
help='Create interactive version of task',
)
parser.add_argument(
'--outfile',
type=str,
default='',
help='Saves a jsonl file containing all of the task examples and '
'model replies. Set to the empty string to not save at all',
)
parser.add_argument(
'--save-format',
type=str,
default='conversations',
choices=['conversations', 'parlai'],
help=
'Format to save logs in. conversations is a jsonl format, parlai is a text format.',
)
parser.set_defaults(interactive_mode=True, task='interactive')
LocalHumanAgent.add_cmdline_args(parser, partial_opt=None)
WorldLogger.add_cmdline_args(parser, partial_opt=None)
return parser
def setup_args(parser=None):
if parser is None:
parser = ParlaiParser(True, True, 'Interactive chat with a model')
parser.add_argument('-d', '--display-examples', type='bool', default=False)
parser.add_argument(
'--display-prettify',
type='bool',
default=False,
help='Set to use a prettytable when displaying '
'examples with text candidates',
)
parser.add_argument(
'--display-ignore-fields',
type=str,
default='label_candidates,text_candidates',
help='Do not display these fields',
)
parser.set_defaults(model_file='models:convai2/kvmemnn/model')
LocalHumanAgent.add_cmdline_args(parser)
return parser