Mirrors/modelscope
1
0
Fork 0
mirror of https://github.com/modelscope/modelscope.git synced 2026-09-01 19:49:03 +02:00
Code Issues Packages Projects Releases Wiki Activity

test with model hub

Browse Source
This commit is contained in:
ly119399
2022-06-12 23:27:26 +08:00
parent e683a2d4cd
commit 46c2dcc27d
10 changed files with 141 additions and 115 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
modelscope/models/nlp/space/dialog_intent_model.py
View File

@@ -1,6 +1,10 @@
from typing import Any, Dict, Optional
import os
from typing import Any, Dict
from modelscope.preprocessors.space.fields.intent_field import \
IntentBPETextField
from modelscope.trainers.nlp.space.trainers.intent_trainer import IntentTrainer
from modelscope.utils.config import Config
from modelscope.utils.constant import Tasks
from ...base import Model, Tensor
from ...builder import MODELS
@@ -10,7 +14,7 @@ from .model.model_base import ModelBase
__all__ = ['DialogIntentModel']
@MODELS.register_module(Tasks.dialog_intent, module_name=r'space-intent')
@MODELS.register_module(Tasks.dialog_intent, module_name=r'space')
class DialogIntentModel(Model):
def __init__(self, model_dir: str, *args, **kwargs):
@@ -24,8 +28,14 @@ class DialogIntentModel(Model):
super().__init__(model_dir, *args, **kwargs)
self.model_dir = model_dir
self.text_field = kwargs.pop('text_field')
self.config = kwargs.pop('config')
self.config = kwargs.pop(
'config',
Config.from_file(
os.path.join(self.model_dir, 'configuration.json')))
self.text_field = kwargs.pop(
'text_field',
IntentBPETextField(self.model_dir, config=self.config))
self.generator = Generator.create(self.config, reader=self.text_field)
self.model = ModelBase.create(
model_dir=model_dir,
@@ -63,9 +73,8 @@ class DialogIntentModel(Model):
'logits': array([[-0.53860897, 1.5029076 ]], dtype=float32) # true value
}
"""
from numpy import array, float32
import torch
print('--forward--')
result = self.trainer.forward(input)
import numpy as np
pred = self.trainer.forward(input)
pred = np.squeeze(pred[0], 0)
return result
return {'pred': pred}

9
modelscope/pipelines/nlp/space/dialog_intent_pipeline.py
View File

@@ -9,7 +9,7 @@ from ...builder import PIPELINES
__all__ = ['DialogIntentPipeline']
@PIPELINES.register_module(Tasks.dialog_intent, module_name=r'space-intent')
@PIPELINES.register_module(Tasks.dialog_intent, module_name=r'space')
class DialogIntentPipeline(Pipeline):
def __init__(self, model: DialogIntentModel,
@@ -34,5 +34,10 @@ class DialogIntentPipeline(Pipeline):
Returns:
Dict[str, str]: the prediction results
"""
import numpy as np
pred = inputs['pred']
pos = np.where(pred == np.max(pred))
return inputs
result = {'pred': pred, 'label': pos[0]}
return result

7
modelscope/preprocessors/space/dialog_intent_preprocessor.py
View File

@@ -1,13 +1,12 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import uuid
from typing import Any, Dict, Union
from typing import Any, Dict
from modelscope.preprocessors.space.fields.intent_field import \
IntentBPETextField
from modelscope.utils.config import Config
from modelscope.utils.constant import Fields, InputFields
from modelscope.utils.constant import Fields
from modelscope.utils.type_assert import type_assert
from ..base import Preprocessor
from ..builder import PREPROCESSORS
@@ -15,7 +14,7 @@ from ..builder import PREPROCESSORS
__all__ = ['DialogIntentPreprocessor']
@PREPROCESSORS.register_module(Fields.nlp, module_name=r'space-intent')
@PREPROCESSORS.register_module(Fields.nlp, module_name=r'space')
class DialogIntentPreprocessor(Preprocessor):
def __init__(self, model_dir: str, *args, **kwargs):

5
modelscope/trainers/nlp/space/trainers/intent_trainer.py
View File

@@ -508,7 +508,6 @@ class IntentTrainer(Trainer):
report_for_unlabeled_data, cur_valid_metric=-accuracy)
def forward(self, batch):
outputs, labels = [], []
pred, true = [], []
with torch.no_grad():
@@ -522,12 +521,10 @@ class IntentTrainer(Trainer):
intent_probs = result['intent_probs']
if self.can_norm:
pred += [intent_probs]
true += batch['intent_label'].cpu().detach().tolist()
else:
pred += np.argmax(intent_probs, axis=1).tolist()
true += batch['intent_label'].cpu().detach().tolist()
return {'pred': pred}
return pred
def infer(self, data_iter, num_batches=None, ex_data_iter=None):
"""

0
tests/case/__init__.py
View File

0
tests/case/nlp/__init__.py
View File

76
tests/case/nlp/dialog_generation_case.py
View File

@@ -1,76 +0,0 @@
test_case = {
'sng0073': {
'goal': {
'taxi': {
'info': {
'leaveat': '17:15',
'destination': 'pizza hut fen ditton',
'departure': "saint john's college"
},
'reqt': ['car', 'phone'],
'fail_info': {}
}
},
'log': [{
'user':
"i would like a taxi from saint john 's college to pizza hut fen ditton .",
'user_delex':
'i would like a taxi from [value_departure] to [value_destination] .',
'resp':
'what time do you want to leave and what time do you want to arrive by ?',
'sys':
'what time do you want to leave and what time do you want to arrive by ?',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college",
'cons_delex': '[taxi] destination departure',
'sys_act': '[taxi] [request] leave arrive',
'turn_num': 0,
'turn_domain': '[taxi]'
}, {
'user': 'i want to leave after 17:15 .',
'user_delex': 'i want to leave after [value_leave] .',
'resp':
'booking completed ! your taxi will be [value_car] contact number is [value_phone]',
'sys':
'booking completed ! your taxi will be blue honda contact number is 07218068540',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college leave 17:15",
'cons_delex': '[taxi] destination departure leave',
'sys_act': '[taxi] [inform] car phone',
'turn_num': 1,
'turn_domain': '[taxi]'
}, {
'user': 'thank you for all the help ! i appreciate it .',
'user_delex': 'thank you for all the help ! i appreciate it .',
'resp':
'you are welcome . is there anything else i can help you with today ?',
'sys':
'you are welcome . is there anything else i can help you with today ?',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college leave 17:15",
'cons_delex': '[taxi] destination departure leave',
'sys_act': '[general] [reqmore]',
'turn_num': 2,
'turn_domain': '[general]'
}, {
'user': 'no , i am all set . have a nice day . bye .',
'user_delex': 'no , i am all set . have a nice day . bye .',
'resp': 'you too ! thank you',
'sys': 'you too ! thank you',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college leave 17:15",
'cons_delex': '[taxi] destination departure leave',
'sys_act': '[general] [bye]',
'turn_num': 3,
'turn_domain': '[general]'
}]
}
}

4
tests/case/nlp/dialog_intent_case.py
View File

@@ -1,4 +0,0 @@
test_case = [
'How do I locate my card?',
'I still have not received my new card, I ordered over a week ago.'
]

78
tests/pipelines/nlp/test_dialog_generation.py
View File

@@ -4,8 +4,6 @@ import os.path as osp
import tempfile
import unittest
from tests.case.nlp.dialog_generation_case import test_case
from modelscope.models.nlp import DialogGenerationModel
from modelscope.pipelines import DialogGenerationPipeline, pipeline
from modelscope.preprocessors import DialogGenerationPreprocessor
@@ -16,6 +14,82 @@ def merge(info, result):
class DialogGenerationTest(unittest.TestCase):
test_case = {
'sng0073': {
'goal': {
'taxi': {
'info': {
'leaveat': '17:15',
'destination': 'pizza hut fen ditton',
'departure': "saint john's college"
},
'reqt': ['car', 'phone'],
'fail_info': {}
}
},
'log': [{
'user':
"i would like a taxi from saint john 's college to pizza hut fen ditton .",
'user_delex':
'i would like a taxi from [value_departure] to [value_destination] .',
'resp':
'what time do you want to leave and what time do you want to arrive by ?',
'sys':
'what time do you want to leave and what time do you want to arrive by ?',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college",
'cons_delex': '[taxi] destination departure',
'sys_act': '[taxi] [request] leave arrive',
'turn_num': 0,
'turn_domain': '[taxi]'
}, {
'user': 'i want to leave after 17:15 .',
'user_delex': 'i want to leave after [value_leave] .',
'resp':
'booking completed ! your taxi will be [value_car] contact number is [value_phone]',
'sys':
'booking completed ! your taxi will be blue honda contact number is 07218068540',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college leave 17:15",
'cons_delex': '[taxi] destination departure leave',
'sys_act': '[taxi] [inform] car phone',
'turn_num': 1,
'turn_domain': '[taxi]'
}, {
'user': 'thank you for all the help ! i appreciate it .',
'user_delex': 'thank you for all the help ! i appreciate it .',
'resp':
'you are welcome . is there anything else i can help you with today ?',
'sys':
'you are welcome . is there anything else i can help you with today ?',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college leave 17:15",
'cons_delex': '[taxi] destination departure leave',
'sys_act': '[general] [reqmore]',
'turn_num': 2,
'turn_domain': '[general]'
}, {
'user': 'no , i am all set . have a nice day . bye .',
'user_delex': 'no , i am all set . have a nice day . bye .',
'resp': 'you too ! thank you',
'sys': 'you too ! thank you',
'pointer': '0,0,0,0,0,0',
'match': '',
'constraint':
"[taxi] destination pizza hut fen ditton departure saint john 's college leave 17:15",
'cons_delex': '[taxi] destination departure leave',
'sys_act': '[general] [bye]',
'turn_num': 3,
'turn_domain': '[general]'
}]
}
}
def test_run(self):

50
tests/pipelines/nlp/test_dialog_intent.py
View File

@@ -1,11 +1,9 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import os
import os.path as osp
import tempfile
import unittest
from tests.case.nlp.dialog_intent_case import test_case
from maas_hub.snapshot_download import snapshot_download
from modelscope.models import Model
from modelscope.models.nlp import DialogIntentModel
from modelscope.pipelines import DialogIntentPipeline, pipeline
from modelscope.preprocessors import DialogIntentPreprocessor
@@ -13,22 +11,46 @@ from modelscope.utils.constant import Tasks
class DialogGenerationTest(unittest.TestCase):
model_id = 'damo/nlp_space_dialog-intent'
test_case = [
'How do I locate my card?',
'I still have not received my new card, I ordered over a week ago.'
]
@unittest.skip('test with snapshot_download')
def test_run(self):
modeldir = '/Users/yangliu/Desktop/space-dialog-intent'
preprocessor = DialogIntentPreprocessor(model_dir=modeldir)
cache_path = snapshot_download(self.model_id)
preprocessor = DialogIntentPreprocessor(model_dir=cache_path)
model = DialogIntentModel(
model_dir=modeldir,
model_dir=cache_path,
text_field=preprocessor.text_field,
config=preprocessor.config)
pipeline1 = DialogIntentPipeline(
model=model, preprocessor=preprocessor)
# pipeline1 = pipeline(task=Tasks.dialog_intent, model=model, preprocessor=preprocessor)
for item in test_case:
print(pipeline1(item))
pipelines = [
DialogIntentPipeline(model=model, preprocessor=preprocessor),
pipeline(
task=Tasks.dialog_intent,
model=model,
preprocessor=preprocessor)
]
for my_pipeline, item in list(zip(pipelines, self.test_case)):
print(my_pipeline(item))
def test_run_with_model_from_modelhub(self):
model = Model.from_pretrained(self.model_id)
preprocessor = DialogIntentPreprocessor(model_dir=model.model_dir)
pipelines = [
DialogIntentPipeline(model=model, preprocessor=preprocessor),
pipeline(
task=Tasks.dialog_intent,
model=model,
preprocessor=preprocessor)
]
for my_pipeline, item in list(zip(pipelines, self.test_case)):
print(my_pipeline(item))
if __name__ == '__main__':