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Merge branch 'master-github' into master-merge-internal20230916

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This commit is contained in:
mulin.lyh
2023-09-18 19:01:50 +08:00
parent a21e197151 ae039bbe02
commit 2fa2f9ef62
12 changed files with 84 additions and 15 deletions
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8
modelscope/hub/api.py
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@@ -243,7 +243,8 @@ class HubApi:
tag: Optional[str] = None,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION,
original_model_id: Optional[str] = None,
ignore_file_pattern: Optional[Union[List[str], str]] = None):
ignore_file_pattern: Optional[Union[List[str], str]] = None,
lfs_suffix: Optional[Union[str, List[str]]] = None):
"""Upload model from a given directory to given repository. A valid model directory
must contain a configuration.json file.
@@ -281,6 +282,7 @@ class HubApi:
branch and push to it.
original_model_id (str, optional): The base model id which this model is trained from
ignore_file_pattern (`Union[List[str], str]`, optional): The file pattern to ignore uploading
lfs_suffix (`List[str]`, optional): File types to use LFS to manage. examples: '*.safetensors'.
Raises:
InvalidParameter: Parameter invalid.
@@ -349,6 +351,10 @@ class HubApi:
date = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
commit_message = '[automsg] push model %s to hub at %s' % (
model_id, date)
if lfs_suffix is not None:
lfs_suffix_list = [lfs_suffix] if isinstance(lfs_suffix, str) else lfs_suffix
for suffix in lfs_suffix_list:
repo.add_lfs_type(suffix)
repo.push(
commit_message=commit_message,
local_branch=revision,

2
modelscope/hub/repository.py
View File

@@ -105,7 +105,7 @@ class Repository:
examples '*.safetensors'
"""
os.system(
"printf '%s filter=lfs diff=lfs merge=lfs -text\n'>>%s" %
"printf '\n%s filter=lfs diff=lfs merge=lfs -text\n'>>%s" %
(file_name_suffix, os.path.join(self.model_dir, '.gitattributes')))
def push(self,

17
modelscope/models/multi_modal/efficient_diffusion_tuning/efficient_stable_diffusion.py
View File

@@ -13,7 +13,6 @@ from diffusers import (AutoencoderKL, DDPMScheduler, DiffusionPipeline,
utils)
from diffusers.models import attention
from diffusers.utils import deprecation_utils
from swift import AdapterConfig, LoRAConfig, PromptConfig, Swift
from transformers import CLIPTextModel, CLIPTokenizer
from modelscope import snapshot_download
@@ -26,6 +25,7 @@ from modelscope.outputs import OutputKeys
from modelscope.utils.checkpoint import save_checkpoint, save_configuration
from modelscope.utils.config import Config
from modelscope.utils.constant import ModelFile, Tasks
from modelscope.utils.import_utils import is_swift_available
from .control_sd_lora import ControlLoRATuner
utils.deprecate = lambda *arg, **kwargs: None
@@ -34,6 +34,9 @@ attention.deprecate = lambda *arg, **kwargs: None
__tuner_MAP__ = {'lora': LoRATuner, 'control_lora': ControlLoRATuner}
if is_swift_available():
from swift import AdapterConfig, LoRAConfig, PromptConfig, Swift
@MODELS.register_module(
Tasks.efficient_diffusion_tuning,
@@ -110,6 +113,10 @@ class EfficientStableDiffusion(TorchModel):
self.tuner_name = tuner_name
if tuner_name == 'swift-lora':
if not is_swift_available():
raise ValueError(
'Please install swift by `pip install ms-swift` to use swift tuners.'
)
rank = tuner_config[
'rank'] if tuner_config and 'rank' in tuner_config else 4
lora_config = LoRAConfig(
@@ -119,6 +126,10 @@ class EfficientStableDiffusion(TorchModel):
use_merged_linear=False)
self.unet = Swift.prepare_model(self.unet, lora_config)
elif tuner_name == 'swift-adapter':
if not is_swift_available():
raise ValueError(
'Please install swift by `pip install ms-swift` to use swift tuners.'
)
adapter_length = tuner_config[
'adapter_length'] if tuner_config and 'adapter_length' in tuner_config else 10
adapter_config = AdapterConfig(
@@ -128,6 +139,10 @@ class EfficientStableDiffusion(TorchModel):
adapter_length=adapter_length)
self.unet = Swift.prepare_model(self.unet, adapter_config)
elif tuner_name == 'swift-prompt':
if not is_swift_available():
raise ValueError(
'Please install swift by `pip install ms-swift` to use swift tuners.'
)
prompt_length = tuner_config[
'prompt_length'] if tuner_config and 'prompt_length' in tuner_config else 10
prompt_config = PromptConfig(

7
modelscope/pipelines/audio/asr_inference_pipeline.py
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@@ -160,6 +160,7 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
token_num_relax=self.cmd['token_num_relax'],
decoding_ind=self.cmd['decoding_ind'],
decoding_mode=self.cmd['decoding_mode'],
fake_streaming=self.cmd['fake_streaming'],
**kwargs,
)
@@ -310,13 +311,15 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
'fs': {
'model_fs': None,
'audio_fs': None
}
},
'fake_streaming': False,
}
frontend_conf = None
token_num_relax = None
decoding_ind = None
decoding_mode = None
fake_streaming = False
if os.path.exists(outputs['am_model_config']):
config_file = open(outputs['am_model_config'], encoding='utf-8')
root = yaml.full_load(config_file)
@@ -350,6 +353,7 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
cmd['token_num_relax'] = token_num_relax
cmd['decoding_ind'] = decoding_ind
cmd['decoding_mode'] = decoding_mode
cmd['fake_streaming'] = fake_streaming
if outputs.__contains__('mvn_file'):
cmd['cmvn_file'] = outputs['mvn_file']
model_config = self.model_cfg['model_config']
@@ -389,6 +393,7 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
'punc_model_file',
'punc_infer_config',
'param_dict',
'fake_streaming',
]
for user_args in user_args_dict:

17
modelscope/utils/ast_utils.py
View File

@@ -435,24 +435,27 @@ class FilesAstScanning(object):
ignored.add(item)
return list(set(output) - set(ignored))
def traversal_files(self, path, check_sub_dir=None):
def traversal_files(self, path, check_sub_dir=None, include_init=False):
self.file_dirs = []
if check_sub_dir is None or len(check_sub_dir) == 0:
self._traversal_files(path)
self._traversal_files(path, include_init=include_init)
else:
for item in check_sub_dir:
sub_dir = os.path.join(path, item)
if os.path.isdir(sub_dir):
self._traversal_files(sub_dir)
self._traversal_files(sub_dir, include_init=include_init)
def _traversal_files(self, path):
def _traversal_files(self, path, include_init=False):
dir_list = os.scandir(path)
for item in dir_list:
if item.name.startswith('__') or item.name.endswith(
'.json') or item.name.endswith('.md'):
if item.name == '__init__.py' and not include_init:
continue
elif (item.name.startswith('__')
and item.name != '__init__.py') or item.name.endswith(
'.json') or item.name.endswith('.md'):
continue
if item.is_dir():
self._traversal_files(item.path)
self._traversal_files(item.path, include_init=include_init)
elif item.is_file() and item.name.endswith('.py'):
self.file_dirs.append(item.path)
elif item.is_file() and 'requirement' in item.name:

6
modelscope/utils/error.py
View File

@@ -174,3 +174,9 @@ XFORMERS_IMPORT_ERROR = """
{0} requires the timm library but it was not found in your environment. You can install it with pip:
`pip install xformers>=0.0.17`
"""
# docstyle-ignore
SWIFT_IMPORT_ERROR = """
{0} requires the ms-swift library but it was not found in your environment. You can install it with pip:
`pip install ms-swift -U`
"""

1
modelscope/utils/import_utils.py
View File

@@ -310,6 +310,7 @@ REQUIREMENTS_MAAPING = OrderedDict([
('open_clip', (is_package_available('open_clip'), OPENCLIP_IMPORT_ERROR)),
('taming', (is_package_available('taming'), TAMING_IMPORT_ERROR)),
('xformers', (is_package_available('xformers'), XFORMERS_IMPORT_ERROR)),
('swift', (is_package_available('swift'), SWIFT_IMPORT_ERROR)),
])
SYSTEM_PACKAGE = set(['os', 'sys', 'typing'])

2
modelscope/utils/plugins.py
View File

@@ -372,7 +372,7 @@ def import_module_from_model_dir(model_dir):
"""
from pathlib import Path
file_scanner = FilesAstScanning()
file_scanner.traversal_files(model_dir)
file_scanner.traversal_files(model_dir, include_init=True)
file_dirs = file_scanner.file_dirs
requirements = file_scanner.requirement_dirs

1
requirements/framework.txt
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@@ -4,7 +4,6 @@ datasets>=2.8.0,<=2.13.0
einops
filelock>=3.3.0
gast>=0.2.2
ms-swift
numpy
oss2
pandas

5
tests/pipelines/test_efficient_diffusion_tuning.py
View File

@@ -1,8 +1,8 @@
# Copyright 2022-2023 The Alibaba Fundamental Vision Team Authors. All rights reserved.
import os
import unittest
from modelscope.models import Model
from modelscope.models.multi_modal import EfficientStableDiffusion
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.utils.test_utils import test_level
@@ -11,6 +11,7 @@ from modelscope.utils.test_utils import test_level
class EfficientDiffusionTuningTest(unittest.TestCase):
def setUp(self) -> None:
os.system('pip install ms-swift -U')
self.task = Tasks.efficient_diffusion_tuning
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@@ -28,6 +29,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-lora'
model_revision = 'v1.0.2'
model = Model.from_pretrained(model_id, model_revision=model_revision)
from modelscope.models.multi_modal import EfficientStableDiffusion
self.assertTrue(model.__class__ == EfficientStableDiffusion)
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@@ -52,6 +54,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-control-lora'
model_revision = 'v1.0.2'
model = Model.from_pretrained(model_id, model_revision=model_revision)
from modelscope.models.multi_modal import EfficientStableDiffusion
self.assertTrue(model.__class__ == EfficientStableDiffusion)

6
tests/pipelines/test_efficient_diffusion_tuning_swift.py
View File

@@ -1,11 +1,11 @@
# Copyright 2022-2023 The Alibaba Fundamental Vision Team Authors. All rights reserved.
import os
import tempfile
import unittest
import cv2
from modelscope.models import Model
from modelscope.models.multi_modal import EfficientStableDiffusion
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.utils.test_utils import test_level
@@ -14,6 +14,7 @@ from modelscope.utils.test_utils import test_level
class EfficientDiffusionTuningTestSwift(unittest.TestCase):
def setUp(self) -> None:
os.system('pip install ms-swift -U')
self.task = Tasks.efficient_diffusion_tuning
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
@@ -39,6 +40,7 @@ class EfficientDiffusionTuningTestSwift(unittest.TestCase):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-swift-lora'
model_revision = 'v1.0.2'
model = Model.from_pretrained(model_id, model_revision=model_revision)
from modelscope.models.multi_modal import EfficientStableDiffusion
self.assertTrue(model.__class__ == EfficientStableDiffusion)
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
@@ -64,6 +66,7 @@ class EfficientDiffusionTuningTestSwift(unittest.TestCase):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-swift-adapter'
model_revision = 'v1.0.2'
model = Model.from_pretrained(model_id, model_revision=model_revision)
from modelscope.models.multi_modal import EfficientStableDiffusion
self.assertTrue(model.__class__ == EfficientStableDiffusion)
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
@@ -89,6 +92,7 @@ class EfficientDiffusionTuningTestSwift(unittest.TestCase):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-swift-prompt'
model_revision = 'v1.0.2'
model = Model.from_pretrained(model_id, model_revision=model_revision)
from modelscope.models.multi_modal import EfficientStableDiffusion
self.assertTrue(model.__class__ == EfficientStableDiffusion)

27
tests/utils/test_ast.py
View File

@@ -24,13 +24,31 @@ class AstScaningTest(unittest.TestCase):
def setUp(self):
print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
self.tmp_dir = tempfile.TemporaryDirectory().name
self.tmp_dir2 = tempfile.TemporaryDirectory().name
self.test_file = os.path.join(self.tmp_dir, 'test.py')
if not os.path.exists(self.tmp_dir):
os.makedirs(self.tmp_dir)
fnames = ['1.py', '2.py', '3.py', '__init__.py']
self.folders = ['.', 'a', 'b', 'c']
dir_path = self.tmp_dir2
folder_dirs = [
os.path.join(dir_path, folder) for folder in self.folders
]
for folder in folder_dirs:
os.makedirs(folder, exist_ok=True)
for fname in fnames:
fpath = os.path.join(folder, fname)
with open(fpath, 'w') as f:
f.write('hello world')
for folder in folder_dirs:
print(f'folder: {os.listdir(folder)}')
def tearDown(self):
super().tearDown()
shutil.rmtree(self.tmp_dir)
shutil.rmtree(self.tmp_dir2)
def test_ast_scaning_class(self):
astScaner = AstScanning()
@@ -75,6 +93,15 @@ class AstScaningTest(unittest.TestCase):
index_0 = list(requirements.keys())[0]
self.assertIsInstance(requirements[index_0], list)
fileScaner.traversal_files(self.tmp_dir2, include_init=False)
self.assertTrue(
os.path.join(self.tmp_dir2, '__init__.py') not in
fileScaner.file_dirs)
fileScaner.traversal_files(self.tmp_dir2, include_init=True)
self.assertTrue(
os.path.join(self.tmp_dir2, '__init__.py') in fileScaner.file_dirs)
def test_file_mtime_md5_method(self):
fileScaner = FilesAstScanning()
# create first file