[to #42966122] requirements enchanment and self-host repo support

* add self-hosted repo:
* add extra requirements for different field and reduce necessary requirements
* update docker file with so required by audio
* add requirements checker which will be used later when implement lazy import
* remove repeated requirements and replace opencv-python-headless with opencv-python

example usage:
```shell
pip install model_scope[all] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[cv] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[nlp] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[audio] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html
pip install model_scope[multi-modal] -f https://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/repo.html

```
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9211383

.dev_scripts/run_docker.sh

@@ -0,0 +1,7 @@
+#sudo docker run --name zwm_maas -v /home/wenmeng.zwm/workspace:/home/wenmeng.zwm/workspace   --net host -ti reg.docker.alibaba-inc.com/pai-dlc/tensorflow-training:2.3-gpu-py36-cu101-ubuntu18.04 bash
+#sudo docker run --name zwm_maas_pytorch -v /home/wenmeng.zwm/workspace:/home/wenmeng.zwm/workspace --net host  -ti reg.docker.alibaba-inc.com/pai-dlc/pytorch-training:1.10PAI-gpu-py36-cu113-ubuntu18.04 bash
+CONTAINER_NAME=modelscope-dev
+IMAGE_NAME=registry.cn-shanghai.aliyuncs.com/modelscope/modelscope
+IMAGE_VERSION=v0.1.1-16-g62856fa-devel
+MOUNT_DIR=/home/wenmeng.zwm/workspace
+sudo docker run --name  $CONTAINER_NAME -v $MOUNT_DIR:$MOUNT_DIR --net host  -ti ${IMAGE_NAME}:${IMAGE_VERSION} bash

docker/pytorch.dockerfile

@@ -30,7 +30,8 @@ RUN apt-get update &&\
     zip \
     zlib1g-dev \
     unzip \
-    pkg-config
+    pkg-config \
+    libsndfile1
 
 # install modelscope and its python env
 WORKDIR /opt/modelscope

docs/source/index.rst

@@ -13,6 +13,7 @@ ModelScope doc
 
    quick_start.md
    develop.md
+   faq.md
 
 .. toctree::
    :maxdepth: 2
@@ -20,6 +21,8 @@ ModelScope doc
 
    tutorials/index
 
+
+
 .. toctree::
    :maxdepth: 2
    :caption: Changelog

modelscope/models/__init__.py

@@ -1,11 +1,26 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
-
-from .audio.ans.frcrn import FRCRNModel
-from .audio.kws import GenericKeyWordSpotting
-from .audio.tts.am import SambertNetHifi16k
-from .audio.tts.vocoder import Hifigan16k
 from .base import Model
 from .builder import MODELS, build_model
-from .multi_modal import OfaForImageCaptioning
-from .nlp import (BertForSequenceClassification, SbertForSentenceSimilarity,
-                  SbertForZeroShotClassification)
+
+try:
+    from .audio.tts.am import SambertNetHifi16k
+    from .audio.tts.vocoder import Hifigan16k
+
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'tensorflow'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)
+
+try:
+    from .audio.kws import GenericKeyWordSpotting
+    from .multi_modal import OfaForImageCaptioning
+    from .nlp import (BertForSequenceClassification,
+                      SbertForSentenceSimilarity,
+                      SbertForZeroShotClassification)
+    from .audio.ans.frcrn import FRCRNModel
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'pytorch'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)

modelscope/pipelines/audio/__init__.py

@@ -1,3 +1,16 @@
-from .kws_kwsbp_pipeline import *  # noqa F403
-from .linear_aec_pipeline import LinearAECPipeline
-from .text_to_speech_pipeline import *  # noqa F403
+try:
+    from .kws_kwsbp_pipeline import *  # noqa F403
+    from .linear_aec_pipeline import LinearAECPipeline
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'torch'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)
+
+try:
+    from .text_to_speech_pipeline import *  # noqa F403
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'tensorflow'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)

modelscope/pipelines/cv/__init__.py

@@ -1,5 +1,18 @@
-from .action_recognition_pipeline import ActionRecognitionPipeline
-from .animal_recog_pipeline import AnimalRecogPipeline
-from .image_cartoon_pipeline import ImageCartoonPipeline
-from .image_matting_pipeline import ImageMattingPipeline
-from .ocr_detection_pipeline import OCRDetectionPipeline
+try:
+    from .action_recognition_pipeline import ActionRecognitionPipeline
+    from .animal_recog_pipeline import AnimalRecogPipeline
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'torch'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)
+
+try:
+    from .image_cartoon_pipeline import ImageCartoonPipeline
+    from .image_matting_pipeline import ImageMattingPipeline
+    from .ocr_detection_pipeline import OCRDetectionPipeline
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'tensorflow'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)

modelscope/pipelines/multi_modal/__init__.py

@@ -1,3 +1,9 @@
-from .image_captioning_pipeline import ImageCaptionPipeline
-from .multi_modal_embedding_pipeline import MultiModalEmbeddingPipeline
-from .visual_question_answering_pipeline import VisualQuestionAnsweringPipeline
+try:
+    from .image_captioning_pipeline import ImageCaptionPipeline
+    from .multi_modal_embedding_pipeline import MultiModalEmbeddingPipeline
+    from .visual_question_answering_pipeline import VisualQuestionAnsweringPipeline
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'torch'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)

modelscope/pipelines/nlp/__init__.py

@@ -1,6 +1,12 @@
-from .fill_mask_pipeline import *  # noqa F403
-from .sentence_similarity_pipeline import *  # noqa F403
-from .sequence_classification_pipeline import *  # noqa F403
-from .text_generation_pipeline import *  # noqa F403
-from .word_segmentation_pipeline import *  # noqa F403
-from .zero_shot_classification_pipeline import *  # noqa F403
+try:
+    from .fill_mask_pipeline import *  # noqa F403
+    from .sentence_similarity_pipeline import *  # noqa F403
+    from .sequence_classification_pipeline import *  # noqa F403
+    from .text_generation_pipeline import *  # noqa F403
+    from .word_segmentation_pipeline import *  # noqa F403
+    from .zero_shot_classification_pipeline import *  # noqa F403
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'torch'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)

modelscope/preprocessors/__init__.py

@@ -1,11 +1,18 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 
-from .audio import LinearAECAndFbank
 from .base import Preprocessor
 from .builder import PREPROCESSORS, build_preprocessor
 from .common import Compose
 from .image import LoadImage, load_image
 from .kws import WavToLists
-from .multi_modal import *  # noqa F403
-from .nlp import *  # noqa F403
 from .text_to_speech import *  # noqa F403
+
+try:
+    from .audio import LinearAECAndFbank
+    from .multi_modal import *  # noqa F403
+    from .nlp import *  # noqa F403
+except ModuleNotFoundError as e:
+    if str(e) == "No module named 'tensorflow'":
+        pass
+    else:
+        raise ModuleNotFoundError(e)

modelscope/utils/check_requirements.py

@@ -0,0 +1,79 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
+
+from modelscope.utils.constant import Fields, Requirements
+from modelscope.utils.import_utils import requires
+
+
+def get_msg(field):
+    msg = f'\n{field} requirements not installed, please execute ' \
+          f'`pip install requirements/{field}.txt` or ' \
+          f'`pip install modelscope[{field}]`'
+    return msg
+
+
+class NLPModuleNotFoundError(ModuleNotFoundError):
+
+    def __init__(self, e: ModuleNotFoundError) -> None:
+        e.msg += get_msg(Fields.nlp)
+        super().__init__(e)
+
+
+class CVModuleNotFoundError(ModuleNotFoundError):
+
+    def __init__(self, e: ModuleNotFoundError) -> None:
+        e.msg += get_msg(Fields.cv)
+        super().__init__(e)
+
+
+class AudioModuleNotFoundError(ModuleNotFoundError):
+
+    def __init__(self, e: ModuleNotFoundError) -> None:
+        e.msg += get_msg(Fields.audio)
+        super().__init__(e)
+
+
+class MultiModalModuleNotFoundError(ModuleNotFoundError):
+
+    def __init__(self, e: ModuleNotFoundError) -> None:
+        e.msg += get_msg(Fields.multi_modal)
+        super().__init__(e)
+
+
+def check_nlp():
+    try:
+        requires('nlp models', (
+            Requirements.torch,
+            Requirements.tokenizers,
+        ))
+    except ImportError as e:
+        raise NLPModuleNotFoundError(e)
+
+
+def check_cv():
+    try:
+        requires('cv models', (
+            Requirements.torch,
+            Requirements.tokenizers,
+        ))
+    except ImportError as e:
+        raise CVModuleNotFoundError(e)
+
+
+def check_audio():
+    try:
+        requires('audio models', (
+            Requirements.torch,
+            Requirements.tf,
+        ))
+    except ImportError as e:
+        raise AudioModuleNotFoundError(e)
+
+
+def check_multi_modal():
+    try:
+        requires('multi-modal models', (
+            Requirements.torch,
+            Requirements.tokenizers,
+        ))
+    except ImportError as e:
+        raise MultiModalModuleNotFoundError(e)

modelscope/utils/config.py

@@ -17,9 +17,10 @@ from typing import Dict
 import addict
 from yapf.yapflib.yapf_api import FormatCode
 
+from modelscope.utils.import_utils import (import_modules,
+                                           import_modules_from_file,
+                                           validate_py_syntax)
 from modelscope.utils.logger import get_logger
-from modelscope.utils.pymod import (import_modules, import_modules_from_file,
-                                    validate_py_syntax)
 
 if platform.system() == 'Windows':
     import regex as re  # type: ignore

modelscope/utils/constant.py

@@ -97,5 +97,18 @@ class ModelFile(object):
     TORCH_MODEL_BIN_FILE = 'pytorch_model.bin'
 
 
+class Requirements(object):
+    """Requirement names for each module
+    """
+    protobuf = 'protobuf'
+    sentencepiece = 'sentencepiece'
+    sklearn = 'sklearn'
+    scipy = 'scipy'
+    timm = 'timm'
+    tokenizers = 'tokenizers'
+    tf = 'tf'
+    torch = 'torch'
+
+
 TENSORFLOW = 'tensorflow'
 PYTORCH = 'pytorch'

modelscope/utils/import_utils.py

@@ -0,0 +1,324 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
+# Part of the implementation is borrowed from huggingface/transformers.
+import ast
+import functools
+import importlib.util
+import os
+import os.path as osp
+import sys
+import types
+from collections import OrderedDict
+from functools import wraps
+from importlib import import_module
+from itertools import chain
+from types import ModuleType
+from typing import Any
+
+import json
+from packaging import version
+
+from modelscope.utils.constant import Fields
+from modelscope.utils.logger import get_logger
+
+if sys.version_info < (3, 8):
+    import importlib_metadata
+else:
+    import importlib.metadata as importlib_metadata
+
+logger = get_logger()
+
+
+def import_modules_from_file(py_file: str):
+    """ Import module from a certrain file
+
+    Args:
+        py_file: path to a python file to be imported
+
+    Return:
+
+    """
+    dirname, basefile = os.path.split(py_file)
+    if dirname == '':
+        dirname == './'
+    module_name = osp.splitext(basefile)[0]
+    sys.path.insert(0, dirname)
+    validate_py_syntax(py_file)
+    mod = import_module(module_name)
+    sys.path.pop(0)
+    return module_name, mod
+
+
+def import_modules(imports, allow_failed_imports=False):
+    """Import modules from the given list of strings.
+
+    Args:
+        imports (list | str | None): The given module names to be imported.
+        allow_failed_imports (bool): If True, the failed imports will return
+            None. Otherwise, an ImportError is raise. Default: False.
+
+    Returns:
+        list[module] | module | None: The imported modules.
+
+    Examples:
+        >>> osp, sys = import_modules(
+        ...     ['os.path', 'sys'])
+        >>> import os.path as osp_
+        >>> import sys as sys_
+        >>> assert osp == osp_
+        >>> assert sys == sys_
+    """
+    if not imports:
+        return
+    single_import = False
+    if isinstance(imports, str):
+        single_import = True
+        imports = [imports]
+    if not isinstance(imports, list):
+        raise TypeError(
+            f'custom_imports must be a list but got type {type(imports)}')
+    imported = []
+    for imp in imports:
+        if not isinstance(imp, str):
+            raise TypeError(
+                f'{imp} is of type {type(imp)} and cannot be imported.')
+        try:
+            imported_tmp = import_module(imp)
+        except ImportError:
+            if allow_failed_imports:
+                logger.warning(f'{imp} failed to import and is ignored.')
+                imported_tmp = None
+            else:
+                raise ImportError
+        imported.append(imported_tmp)
+    if single_import:
+        imported = imported[0]
+    return imported
+
+
+def validate_py_syntax(filename):
+    with open(filename, 'r', encoding='utf-8') as f:
+        # Setting encoding explicitly to resolve coding issue on windows
+        content = f.read()
+    try:
+        ast.parse(content)
+    except SyntaxError as e:
+        raise SyntaxError('There are syntax errors in config '
+                          f'file {filename}: {e}')
+
+
+# following code borrows implementation from huggingface/transformers
+ENV_VARS_TRUE_VALUES = {'1', 'ON', 'YES', 'TRUE'}
+ENV_VARS_TRUE_AND_AUTO_VALUES = ENV_VARS_TRUE_VALUES.union({'AUTO'})
+USE_TF = os.environ.get('USE_TF', 'AUTO').upper()
+USE_TORCH = os.environ.get('USE_TORCH', 'AUTO').upper()
+_torch_version = 'N/A'
+if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
+    _torch_available = importlib.util.find_spec('torch') is not None
+    if _torch_available:
+        try:
+            _torch_version = importlib_metadata.version('torch')
+            logger.info(f'PyTorch version {_torch_version} available.')
+        except importlib_metadata.PackageNotFoundError:
+            _torch_available = False
+else:
+    logger.info('Disabling PyTorch because USE_TF is set')
+    _torch_available = False
+
+_tf_version = 'N/A'
+if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
+    _tf_available = importlib.util.find_spec('tensorflow') is not None
+    if _tf_available:
+        candidates = (
+            'tensorflow',
+            'tensorflow-cpu',
+            'tensorflow-gpu',
+            'tf-nightly',
+            'tf-nightly-cpu',
+            'tf-nightly-gpu',
+            'intel-tensorflow',
+            'intel-tensorflow-avx512',
+            'tensorflow-rocm',
+            'tensorflow-macos',
+        )
+        _tf_version = None
+        # For the metadata, we have to look for both tensorflow and tensorflow-cpu
+        for pkg in candidates:
+            try:
+                _tf_version = importlib_metadata.version(pkg)
+                break
+            except importlib_metadata.PackageNotFoundError:
+                pass
+        _tf_available = _tf_version is not None
+    if _tf_available:
+        if version.parse(_tf_version) < version.parse('2'):
+            pass
+        else:
+            logger.info(f'TensorFlow version {_tf_version} available.')
+else:
+    logger.info('Disabling Tensorflow because USE_TORCH is set')
+    _tf_available = False
+
+_timm_available = importlib.util.find_spec('timm') is not None
+try:
+    _timm_version = importlib_metadata.version('timm')
+    logger.debug(f'Successfully imported timm version {_timm_version}')
+except importlib_metadata.PackageNotFoundError:
+    _timm_available = False
+
+
+def is_scipy_available():
+    return importlib.util.find_spec('scipy') is not None
+
+
+def is_sklearn_available():
+    if importlib.util.find_spec('sklearn') is None:
+        return False
+    return is_scipy_available() and importlib.util.find_spec('sklearn.metrics')
+
+
+def is_sentencepiece_available():
+    return importlib.util.find_spec('sentencepiece') is not None
+
+
+def is_protobuf_available():
+    if importlib.util.find_spec('google') is None:
+        return False
+    return importlib.util.find_spec('google.protobuf') is not None
+
+
+def is_tokenizers_available():
+    return importlib.util.find_spec('tokenizers') is not None
+
+
+def is_timm_available():
+    return _timm_available
+
+
+def is_torch_available():
+    return _torch_available
+
+
+def is_torch_cuda_available():
+    if is_torch_available():
+        import torch
+
+        return torch.cuda.is_available()
+    else:
+        return False
+
+
+def is_tf_available():
+    return _tf_available
+
+
+# docstyle-ignore
+PROTOBUF_IMPORT_ERROR = """
+{0} requires the protobuf library but it was not found in your environment. Checkout the instructions on the
+installation page of its repo: https://github.com/protocolbuffers/protobuf/tree/master/python#installation and
+follow the ones that match your environment.
+"""
+
+# docstyle-ignore
+SENTENCEPIECE_IMPORT_ERROR = """
+{0} requires the SentencePiece library but it was not found in your environment. Checkout the instructions on the
+installation page of its repo: https://github.com/google/sentencepiece#installation and follow the ones
+that match your environment.
+"""
+
+# docstyle-ignore
+SKLEARN_IMPORT_ERROR = """
+{0} requires the scikit-learn library but it was not found in your environment. You can install it with:
+```
+pip install -U scikit-learn
+```
+In a notebook or a colab, you can install it by executing a cell with
+```
+!pip install -U scikit-learn
+```
+"""
+
+# docstyle-ignore
+TENSORFLOW_IMPORT_ERROR = """
+{0} requires the TensorFlow library but it was not found in your environment. Checkout the instructions on the
+installation page: https://www.tensorflow.org/install and follow the ones that match your environment.
+"""
+
+# docstyle-ignore
+TIMM_IMPORT_ERROR = """
+{0} requires the timm library but it was not found in your environment. You can install it with pip:
+`pip install timm`
+"""
+
+# docstyle-ignore
+TOKENIZERS_IMPORT_ERROR = """
+{0} requires the 🤗 Tokenizers library but it was not found in your environment. You can install it with:
+```
+pip install tokenizers
+```
+In a notebook or a colab, you can install it by executing a cell with
+```
+!pip install tokenizers
+```
+"""
+
+# docstyle-ignore
+PYTORCH_IMPORT_ERROR = """
+{0} requires the PyTorch library but it was not found in your environment. Checkout the instructions on the
+installation page: https://pytorch.org/get-started/locally/ and follow the ones that match your environment.
+"""
+
+# docstyle-ignore
+SCIPY_IMPORT_ERROR = """
+{0} requires the scipy library but it was not found in your environment. You can install it with pip:
+`pip install scipy`
+"""
+
+REQUIREMENTS_MAAPING = OrderedDict([
+    ('protobuf', (is_protobuf_available, PROTOBUF_IMPORT_ERROR)),
+    ('sentencepiece', (is_sentencepiece_available,
+                       SENTENCEPIECE_IMPORT_ERROR)),
+    ('sklearn', (is_sklearn_available, SKLEARN_IMPORT_ERROR)),
+    ('tf', (is_tf_available, TENSORFLOW_IMPORT_ERROR)),
+    ('timm', (is_timm_available, TIMM_IMPORT_ERROR)),
+    ('tokenizers', (is_tokenizers_available, TOKENIZERS_IMPORT_ERROR)),
+    ('torch', (is_torch_available, PYTORCH_IMPORT_ERROR)),
+    ('scipy', (is_scipy_available, SCIPY_IMPORT_ERROR)),
+])
+
+
+def requires(obj, requirements):
+    if not isinstance(requirements, (list, tuple)):
+        requirements = [requirements]
+    if isinstance(obj, str):
+        name = obj
+    else:
+        name = obj.__name__ if hasattr(obj,
+                                       '__name__') else obj.__class__.__name__
+    checks = (REQUIREMENTS_MAAPING[req] for req in requirements)
+    failed = [msg.format(name) for available, msg in checks if not available()]
+    if failed:
+        raise ImportError(''.join(failed))
+
+
+def torch_required(func):
+    # Chose a different decorator name than in tests so it's clear they are not the same.
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        if is_torch_available():
+            return func(*args, **kwargs)
+        else:
+            raise ImportError(f'Method `{func.__name__}` requires PyTorch.')
+
+    return wrapper
+
+
+def tf_required(func):
+    # Chose a different decorator name than in tests so it's clear they are not the same.
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        if is_tf_available():
+            return func(*args, **kwargs)
+        else:
+            raise ImportError(f'Method `{func.__name__}` requires TF.')
+
+    return wrapper

modelscope/utils/pymod.py

@@ -1,90 +0,0 @@
-# Copyright (c) Alibaba, Inc. and its affiliates.
-
-import ast
-import os
-import os.path as osp
-import sys
-import types
-from importlib import import_module
-
-from modelscope.utils.logger import get_logger
-
-logger = get_logger()
-
-
-def import_modules_from_file(py_file: str):
-    """ Import module from a certrain file
-
-    Args:
-        py_file: path to a python file to be imported
-
-    Return:
-
-    """
-    dirname, basefile = os.path.split(py_file)
-    if dirname == '':
-        dirname == './'
-    module_name = osp.splitext(basefile)[0]
-    sys.path.insert(0, dirname)
-    validate_py_syntax(py_file)
-    mod = import_module(module_name)
-    sys.path.pop(0)
-    return module_name, mod
-
-
-def import_modules(imports, allow_failed_imports=False):
-    """Import modules from the given list of strings.
-
-    Args:
-        imports (list | str | None): The given module names to be imported.
-        allow_failed_imports (bool): If True, the failed imports will return
-            None. Otherwise, an ImportError is raise. Default: False.
-
-    Returns:
-        list[module] | module | None: The imported modules.
-
-    Examples:
-        >>> osp, sys = import_modules(
-        ...     ['os.path', 'sys'])
-        >>> import os.path as osp_
-        >>> import sys as sys_
-        >>> assert osp == osp_
-        >>> assert sys == sys_
-    """
-    if not imports:
-        return
-    single_import = False
-    if isinstance(imports, str):
-        single_import = True
-        imports = [imports]
-    if not isinstance(imports, list):
-        raise TypeError(
-            f'custom_imports must be a list but got type {type(imports)}')
-    imported = []
-    for imp in imports:
-        if not isinstance(imp, str):
-            raise TypeError(
-                f'{imp} is of type {type(imp)} and cannot be imported.')
-        try:
-            imported_tmp = import_module(imp)
-        except ImportError:
-            if allow_failed_imports:
-                logger.warning(f'{imp} failed to import and is ignored.')
-                imported_tmp = None
-            else:
-                raise ImportError
-        imported.append(imported_tmp)
-    if single_import:
-        imported = imported[0]
-    return imported
-
-
-def validate_py_syntax(filename):
-    with open(filename, 'r', encoding='utf-8') as f:
-        # Setting encoding explicitly to resolve coding issue on windows
-        content = f.read()
-    try:
-        ast.parse(content)
-    except SyntaxError as e:
-        raise SyntaxError('There are syntax errors in config '
-                          f'file {filename}: {e}')

modelscope/utils/registry.py

@@ -1,7 +1,9 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 
 import inspect
+from typing import List, Tuple, Union
 
+from modelscope.utils.import_utils import requires
 from modelscope.utils.logger import get_logger
 
 default_group = 'default'
@@ -52,9 +54,14 @@ class Registry(object):
     def _register_module(self,
                          group_key=default_group,
                          module_name=None,
-                         module_cls=None):
+                         module_cls=None,
+                         requirements=None):
         assert isinstance(group_key,
                           str), 'group_key is required and must be str'
+
+        if requirements is not None:
+            requires(module_cls, requirements)
+
         if group_key not in self._modules:
             self._modules[group_key] = dict()
 
@@ -86,7 +93,8 @@ class Registry(object):
     def register_module(self,
                         group_key: str = default_group,
                         module_name: str = None,
-                        module_cls: type = None):
+                        module_cls: type = None,
+                        requirements: Union[List, Tuple] = None):
         """ Register module
 
         Example:
@@ -110,17 +118,18 @@ class Registry(object):
                 default group name is 'default'
             module_name: Module name
             module_cls: Module class object
+            requirements: Module necessary requirements
 
         """
         if not (module_name is None or isinstance(module_name, str)):
             raise TypeError(f'module_name must be either of None, str,'
                             f'got {type(module_name)}')
-
         if module_cls is not None:
             self._register_module(
                 group_key=group_key,
                 module_name=module_name,
-                module_cls=module_cls)
+                module_cls=module_cls,
+                requirements=requirements)
             return module_cls
 
         # if module_cls is None, should return a decorator function
@@ -128,7 +137,8 @@ class Registry(object):
             self._register_module(
                 group_key=group_key,
                 module_name=module_name,
-                module_cls=module_cls)
+                module_cls=module_cls,
+                requirements=requirements)
             return module_cls
 
         return _register

requirements.txt

@@ -1,6 +1 @@
 -r requirements/runtime.txt
--r requirements/pipeline.txt
--r requirements/multi-modal.txt
--r requirements/nlp.txt
--r requirements/audio.txt
--r requirements/cv.txt

requirements/audio.txt

@@ -1,10 +1,5 @@
 #tts
 h5py
-https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/TTS/requirements/pytorch_wavelets-1.3.0-py3-none-any.whl
-https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/TTS/requirements/ttsfrd-0.0.2-cp36-cp36m-linux_x86_64.whl; python_version=='3.6'
-https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/TTS/requirements/ttsfrd-0.0.2-cp37-cp37m-linux_x86_64.whl; python_version=='3.7'
-https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/TTS/requirements/ttsfrd-0.0.2-cp38-cp38-linux_x86_64.whl; python_version=='3.8'
-https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/TTS/requirements/ttsfrd-0.0.2-cp39-cp39-linux_x86_64.whl; python_version=='3.9'
 inflect
 keras
 librosa
@@ -14,6 +9,7 @@ nara_wpe
 numpy
 protobuf>3,<=3.20
 ptflops
+pytorch_wavelets==1.3.0
 PyWavelets>=1.0.0
 scikit-learn
 SoundFile>0.10
@@ -24,4 +20,5 @@ torch
 torchaudio
 torchvision
 tqdm
+ttsfrd==0.0.2
 unidecode

requirements/multi-modal.txt

@@ -1,8 +1,6 @@
-datasets
-einops
+fairseq==maas
 ftfy>=6.0.3
-https://jirenmr.oss-cn-zhangjiakou.aliyuncs.com/ofa/fairseq-maas-py3-none-any.whl
-https://jirenmr.oss-cn-zhangjiakou.aliyuncs.com/ofa/ofa-0.0.2-py3-none-any.whl
+ofa==0.0.2
 pycocoevalcap>=1.2
 pycocotools>=2.0.4
 rouge_score

requirements/nlp.txt

@@ -1 +1 @@
-https://alinlp.alibaba-inc.com/pypi/sofa-1.0.4.2-py3-none-any.whl
+sofa==1.0.4.2

requirements/pipeline.txt

@@ -1,6 +0,0 @@
-#https://atp-modelzoo-sh.oss-cn-shanghai.aliyuncs.com/release/package/whl/easynlp-0.0.4-py2.py3-none-any.whl
-# tensorflow
-#--find-links https://download.pytorch.org/whl/torch_stable.html
-# torch<1.10,>=1.8.0
-# torchaudio
-# torchvision

requirements/runtime.txt

@@ -1,16 +1,18 @@
 addict
 datasets
 easydict
+einops
 filelock>=3.3.0
 numpy
-opencv-python-headless
+opencv-python
 Pillow>=6.2.0
+protobuf>3,<=3.20
 pyyaml
 requests
-requests==2.27.1
 scipy
-setuptools==58.0.4
+setuptools
 tokenizers<=0.10.3
+torch
 tqdm>=4.64.0
-transformers<=4.16.2
+transformers<=4.16.2,>=4.10.3
 yapf

setup.py

@@ -5,6 +5,8 @@ import shutil
 import subprocess
 from setuptools import find_packages, setup
 
+from modelscope.utils.constant import Fields
+
 
 def readme():
     with open('README.md', encoding='utf-8') as f:
@@ -169,6 +171,16 @@ if __name__ == '__main__':
     pack_resource()
     os.chdir('package')
     install_requires, deps_link = parse_requirements('requirements.txt')
+    extra_requires = {}
+    all_requires = []
+    for field in dir(Fields):
+        if field.startswith('_'):
+            continue
+        extra_requires[field], _ = parse_requirements(
+            f'requirements/{field}.txt')
+        all_requires.append(extra_requires[field])
+    extra_requires['all'] = all_requires
+
     setup(
         name='model-scope',
         version=get_version(),
@@ -193,5 +205,6 @@ if __name__ == '__main__':
         license='Apache License 2.0',
         tests_require=parse_requirements('requirements/tests.txt'),
         install_requires=install_requires,
+        extras_require=extra_requires,
         dependency_links=deps_link,
         zip_safe=False)

tests/utils/test_check_requirements.py

@@ -0,0 +1,22 @@
+# Copyright (c) Alibaba, Inc. and its affiliates.
+
+import unittest
+from typing import List, Union
+
+from modelscope.utils.check_requirements import NLPModuleNotFoundError, get_msg
+from modelscope.utils.constant import Fields
+
+
+class ImportUtilsTest(unittest.TestCase):
+
+    def test_type_module_not_found(self):
+        with self.assertRaises(NLPModuleNotFoundError) as ctx:
+            try:
+                import not_found
+            except ModuleNotFoundError as e:
+                raise NLPModuleNotFoundError(e)
+        self.assertTrue(get_msg(Fields.nlp) in ctx.exception.msg.msg)
+
+
+if __name__ == '__main__':
+    unittest.main()