We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
fix(scheduling): expose Strategy class


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `src/bentoml/__init__.py`
Content:
```
1 """
2 BentoML
3 =======
4 
5 BentoML is the unified ML Model Serving framework. Data Scientists and ML Engineers use
6 BentoML to:
7 
8 * Accelerate and standardize the process of taking ML models to production across teams
9 * Build reliable, scalable, and high performance model serving systems
10 * Provide a flexible MLOps platform that grows with your Data Science needs
11 
12 To learn more, visit BentoML documentation at: http://docs.bentoml.com
13 To get involved with the development, find us on GitHub: https://github.com/bentoml
14 And join us in the BentoML slack community: https://l.bentoml.com/join-slack
15 """
16 
17 from typing import TYPE_CHECKING
18 
19 from ._internal.configuration import BENTOML_VERSION as __version__
20 from ._internal.configuration import load_config
21 from ._internal.configuration import save_config
22 from ._internal.configuration import set_serialization_strategy
23 
24 # Inject dependencies and configurations
25 load_config()
26 
27 # BentoML built-in types
28 from ._internal.bento import Bento
29 from ._internal.cloud import YataiClient
30 from ._internal.context import ServiceContext as Context
31 from ._internal.models import Model
32 from ._internal.monitoring import monitor
33 from ._internal.runner import Runnable
34 from ._internal.runner import Runner
35 from ._internal.service import Service
36 from ._internal.service.loader import load
37 from ._internal.tag import Tag
38 from ._internal.utils.http import Cookie
39 
40 # Bento management APIs
41 from .bentos import delete
42 from .bentos import export_bento
43 from .bentos import get
44 from .bentos import import_bento
45 from .bentos import list  # pylint: disable=W0622
46 from .bentos import pull
47 from .bentos import push
48 from .bentos import serve
49 
50 # server API
51 from .server import GrpcServer
52 from .server import HTTPServer
53 
54 # Framework specific modules, model management and IO APIs are lazily loaded upon import.
55 if TYPE_CHECKING:
56     from . import catboost
57     from . import detectron
58     from . import diffusers
59     from . import easyocr
60     from . import fastai
61     from . import flax
62     from . import gluon
63     from . import h2o
64     from . import keras
65     from . import lightgbm
66     from . import mlflow
67     from . import onnx
68     from . import onnxmlir
69     from . import paddle
70     from . import picklable_model
71     from . import pycaret
72     from . import pytorch
73     from . import pytorch_lightning
74     from . import ray
75     from . import sklearn
76     from . import spacy
77     from . import statsmodels
78     from . import tensorflow
79     from . import tensorflow_v1
80     from . import torchscript
81     from . import transformers
82     from . import triton
83     from . import xgboost
84 
85     # isort: off
86     from . import io
87     from . import models
88     from . import metrics  # Prometheus metrics client
89     from . import container  # Container API
90     from . import client  # Client API
91     from . import batch  # Batch API
92     from . import exceptions  # BentoML exceptions
93     from . import server  # Server API
94     from . import monitoring  # Monitoring API
95     from . import cloud  # Cloud API
96 
97     # isort: on
98 else:
99     from ._internal.utils import LazyLoader as _LazyLoader
100 
101     # ML Frameworks
102     catboost = _LazyLoader("bentoml.catboost", globals(), "bentoml.catboost")
103     detectron = _LazyLoader("bentoml.detectron", globals(), "bentoml.detectron")
104     diffusers = _LazyLoader("bentoml.diffusers", globals(), "bentoml.diffusers")
105     easyocr = _LazyLoader("bentoml.easyocr", globals(), "bentoml.easyocr")
106     flax = _LazyLoader("bentoml.flax", globals(), "bentoml.flax")
107     fastai = _LazyLoader("bentoml.fastai", globals(), "bentoml.fastai")
108     gluon = _LazyLoader("bentoml.gluon", globals(), "bentoml.gluon")
109     h2o = _LazyLoader("bentoml.h2o", globals(), "bentoml.h2o")
110     lightgbm = _LazyLoader("bentoml.lightgbm", globals(), "bentoml.lightgbm")
111     mlflow = _LazyLoader("bentoml.mlflow", globals(), "bentoml.mlflow")
112     onnx = _LazyLoader("bentoml.onnx", globals(), "bentoml.onnx")
113     onnxmlir = _LazyLoader("bentoml.onnxmlir", globals(), "bentoml.onnxmlir")
114     keras = _LazyLoader("bentoml.keras", globals(), "bentoml.keras")
115     paddle = _LazyLoader("bentoml.paddle", globals(), "bentoml.paddle")
116     pycaret = _LazyLoader("bentoml.pycaret", globals(), "bentoml.pycaret")
117     pytorch = _LazyLoader("bentoml.pytorch", globals(), "bentoml.pytorch")
118     pytorch_lightning = _LazyLoader(
119         "bentoml.pytorch_lightning", globals(), "bentoml.pytorch_lightning"
120     )
121     sklearn = _LazyLoader("bentoml.sklearn", globals(), "bentoml.sklearn")
122     picklable_model = _LazyLoader(
123         "bentoml.picklable_model", globals(), "bentoml.picklable_model"
124     )
125     spacy = _LazyLoader("bentoml.spacy", globals(), "bentoml.spacy")
126     statsmodels = _LazyLoader("bentoml.statsmodels", globals(), "bentoml.statsmodels")
127     tensorflow = _LazyLoader("bentoml.tensorflow", globals(), "bentoml.tensorflow")
128     tensorflow_v1 = _LazyLoader(
129         "bentoml.tensorflow_v1", globals(), "bentoml.tensorflow_v1"
130     )
131     torchscript = _LazyLoader("bentoml.torchscript", globals(), "bentoml.torchscript")
132     transformers = _LazyLoader(
133         "bentoml.transformers", globals(), "bentoml.transformers"
134     )
135     xgboost = _LazyLoader("bentoml.xgboost", globals(), "bentoml.xgboost")
136 
137     # Integrations
138     triton = _LazyLoader("bentoml.triton", globals(), "bentoml.triton")
139     ray = _LazyLoader("bentoml.ray", globals(), "bentoml.ray")
140 
141     io = _LazyLoader("bentoml.io", globals(), "bentoml.io")
142     batch = _LazyLoader("bentoml.batch", globals(), "bentoml.batch")
143     models = _LazyLoader("bentoml.models", globals(), "bentoml.models")
144     metrics = _LazyLoader("bentoml.metrics", globals(), "bentoml.metrics")
145     container = _LazyLoader("bentoml.container", globals(), "bentoml.container")
146     client = _LazyLoader("bentoml.client", globals(), "bentoml.client")
147     server = _LazyLoader("bentoml.server", globals(), "bentoml.server")
148     exceptions = _LazyLoader("bentoml.exceptions", globals(), "bentoml.exceptions")
149     monitoring = _LazyLoader("bentoml.monitoring", globals(), "bentoml.monitoring")
150     cloud = _LazyLoader("bentoml.cloud", globals(), "bentoml.cloud")
151 
152     del _LazyLoader
153 
154 __all__ = [
155     "__version__",
156     "Context",
157     "Cookie",
158     "Service",
159     "models",
160     "batch",
161     "metrics",
162     "container",
163     "client",
164     "server",
165     "io",
166     "Tag",
167     "Model",
168     "Runner",
169     "Runnable",
170     "monitoring",
171     "YataiClient",  # Yatai REST API Client
172     # bento APIs
173     "list",
174     "get",
175     "delete",
176     "import_bento",
177     "export_bento",
178     "load",
179     "push",
180     "pull",
181     "serve",
182     "Bento",
183     "exceptions",
184     # server APIs
185     "HTTPServer",
186     "GrpcServer",
187     # Framework specific modules
188     "catboost",
189     "detectron",
190     "diffusers",
191     "easyocr",
192     "flax",
193     "fastai",
194     "gluon",
195     "h2o",
196     "lightgbm",
197     "mlflow",
198     "onnx",
199     "onnxmlir",
200     "paddle",
201     "picklable_model",
202     "pycaret",
203     "pytorch",
204     "pytorch_lightning",
205     "keras",
206     "sklearn",
207     "spacy",
208     "statsmodels",
209     "tensorflow",
210     "tensorflow_v1",
211     "torchscript",
212     "transformers",
213     "xgboost",
214     # integrations
215     "ray",
216     "cloud",
217     "triton",
218     "monitor",
219     "load_config",
220     "save_config",
221     "set_serialization_strategy",
222 ]
223
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/src/bentoml/__init__.py b/src/bentoml/__init__.py
--- a/src/bentoml/__init__.py
+++ b/src/bentoml/__init__.py
@@ -30,8 +30,10 @@
 from ._internal.context import ServiceContext as Context
 from ._internal.models import Model
 from ._internal.monitoring import monitor
+from ._internal.resource import Resource
 from ._internal.runner import Runnable
 from ._internal.runner import Runner
+from ._internal.runner.strategy import Strategy
 from ._internal.service import Service
 from ._internal.service.loader import load
 from ._internal.tag import Tag
@@ -219,4 +221,6 @@
     "load_config",
     "save_config",
     "set_serialization_strategy",
+    "Strategy",
+    "Resource",
 ]

{"golden_diff": "diff --git a/src/bentoml/__init__.py b/src/bentoml/__init__.py\n--- a/src/bentoml/__init__.py\n+++ b/src/bentoml/__init__.py\n@@ -30,8 +30,10 @@\n from ._internal.context import ServiceContext as Context\n from ._internal.models import Model\n from ._internal.monitoring import monitor\n+from ._internal.resource import Resource\n from ._internal.runner import Runnable\n from ._internal.runner import Runner\n+from ._internal.runner.strategy import Strategy\n from ._internal.service import Service\n from ._internal.service.loader import load\n from ._internal.tag import Tag\n@@ -219,4 +221,6 @@\n     \"load_config\",\n     \"save_config\",\n     \"set_serialization_strategy\",\n+    \"Strategy\",\n+    \"Resource\",\n ]\n", "issue": "fix(scheduling): expose Strategy class\n\n", "before_files": [{"content": "\"\"\"\nBentoML\n=======\n\nBentoML is the unified ML Model Serving framework. Data Scientists and ML Engineers use\nBentoML to:\n\n* Accelerate and standardize the process of taking ML models to production across teams\n* Build reliable, scalable, and high performance model serving systems\n* Provide a flexible MLOps platform that grows with your Data Science needs\n\nTo learn more, visit BentoML documentation at: http://docs.bentoml.com\nTo get involved with the development, find us on GitHub: https://github.com/bentoml\nAnd join us in the BentoML slack community: https://l.bentoml.com/join-slack\n\"\"\"\n\nfrom typing import TYPE_CHECKING\n\nfrom ._internal.configuration import BENTOML_VERSION as __version__\nfrom ._internal.configuration import load_config\nfrom ._internal.configuration import save_config\nfrom ._internal.configuration import set_serialization_strategy\n\n# Inject dependencies and configurations\nload_config()\n\n# BentoML built-in types\nfrom ._internal.bento import Bento\nfrom ._internal.cloud import YataiClient\nfrom ._internal.context import ServiceContext as Context\nfrom ._internal.models import Model\nfrom ._internal.monitoring import monitor\nfrom ._internal.runner import Runnable\nfrom ._internal.runner import Runner\nfrom ._internal.service import Service\nfrom ._internal.service.loader import load\nfrom ._internal.tag import Tag\nfrom ._internal.utils.http import Cookie\n\n# Bento management APIs\nfrom .bentos import delete\nfrom .bentos import export_bento\nfrom .bentos import get\nfrom .bentos import import_bento\nfrom .bentos import list  # pylint: disable=W0622\nfrom .bentos import pull\nfrom .bentos import push\nfrom .bentos import serve\n\n# server API\nfrom .server import GrpcServer\nfrom .server import HTTPServer\n\n# Framework specific modules, model management and IO APIs are lazily loaded upon import.\nif TYPE_CHECKING:\n    from . import catboost\n    from . import detectron\n    from . import diffusers\n    from . import easyocr\n    from . import fastai\n    from . import flax\n    from . import gluon\n    from . import h2o\n    from . import keras\n    from . import lightgbm\n    from . import mlflow\n    from . import onnx\n    from . import onnxmlir\n    from . import paddle\n    from . import picklable_model\n    from . import pycaret\n    from . import pytorch\n    from . import pytorch_lightning\n    from . import ray\n    from . import sklearn\n    from . import spacy\n    from . import statsmodels\n    from . import tensorflow\n    from . import tensorflow_v1\n    from . import torchscript\n    from . import transformers\n    from . import triton\n    from . import xgboost\n\n    # isort: off\n    from . import io\n    from . import models\n    from . import metrics  # Prometheus metrics client\n    from . import container  # Container API\n    from . import client  # Client API\n    from . import batch  # Batch API\n    from . import exceptions  # BentoML exceptions\n    from . import server  # Server API\n    from . import monitoring  # Monitoring API\n    from . import cloud  # Cloud API\n\n    # isort: on\nelse:\n    from ._internal.utils import LazyLoader as _LazyLoader\n\n    # ML Frameworks\n    catboost = _LazyLoader(\"bentoml.catboost\", globals(), \"bentoml.catboost\")\n    detectron = _LazyLoader(\"bentoml.detectron\", globals(), \"bentoml.detectron\")\n    diffusers = _LazyLoader(\"bentoml.diffusers\", globals(), \"bentoml.diffusers\")\n    easyocr = _LazyLoader(\"bentoml.easyocr\", globals(), \"bentoml.easyocr\")\n    flax = _LazyLoader(\"bentoml.flax\", globals(), \"bentoml.flax\")\n    fastai = _LazyLoader(\"bentoml.fastai\", globals(), \"bentoml.fastai\")\n    gluon = _LazyLoader(\"bentoml.gluon\", globals(), \"bentoml.gluon\")\n    h2o = _LazyLoader(\"bentoml.h2o\", globals(), \"bentoml.h2o\")\n    lightgbm = _LazyLoader(\"bentoml.lightgbm\", globals(), \"bentoml.lightgbm\")\n    mlflow = _LazyLoader(\"bentoml.mlflow\", globals(), \"bentoml.mlflow\")\n    onnx = _LazyLoader(\"bentoml.onnx\", globals(), \"bentoml.onnx\")\n    onnxmlir = _LazyLoader(\"bentoml.onnxmlir\", globals(), \"bentoml.onnxmlir\")\n    keras = _LazyLoader(\"bentoml.keras\", globals(), \"bentoml.keras\")\n    paddle = _LazyLoader(\"bentoml.paddle\", globals(), \"bentoml.paddle\")\n    pycaret = _LazyLoader(\"bentoml.pycaret\", globals(), \"bentoml.pycaret\")\n    pytorch = _LazyLoader(\"bentoml.pytorch\", globals(), \"bentoml.pytorch\")\n    pytorch_lightning = _LazyLoader(\n        \"bentoml.pytorch_lightning\", globals(), \"bentoml.pytorch_lightning\"\n    )\n    sklearn = _LazyLoader(\"bentoml.sklearn\", globals(), \"bentoml.sklearn\")\n    picklable_model = _LazyLoader(\n        \"bentoml.picklable_model\", globals(), \"bentoml.picklable_model\"\n    )\n    spacy = _LazyLoader(\"bentoml.spacy\", globals(), \"bentoml.spacy\")\n    statsmodels = _LazyLoader(\"bentoml.statsmodels\", globals(), \"bentoml.statsmodels\")\n    tensorflow = _LazyLoader(\"bentoml.tensorflow\", globals(), \"bentoml.tensorflow\")\n    tensorflow_v1 = _LazyLoader(\n        \"bentoml.tensorflow_v1\", globals(), \"bentoml.tensorflow_v1\"\n    )\n    torchscript = _LazyLoader(\"bentoml.torchscript\", globals(), \"bentoml.torchscript\")\n    transformers = _LazyLoader(\n        \"bentoml.transformers\", globals(), \"bentoml.transformers\"\n    )\n    xgboost = _LazyLoader(\"bentoml.xgboost\", globals(), \"bentoml.xgboost\")\n\n    # Integrations\n    triton = _LazyLoader(\"bentoml.triton\", globals(), \"bentoml.triton\")\n    ray = _LazyLoader(\"bentoml.ray\", globals(), \"bentoml.ray\")\n\n    io = _LazyLoader(\"bentoml.io\", globals(), \"bentoml.io\")\n    batch = _LazyLoader(\"bentoml.batch\", globals(), \"bentoml.batch\")\n    models = _LazyLoader(\"bentoml.models\", globals(), \"bentoml.models\")\n    metrics = _LazyLoader(\"bentoml.metrics\", globals(), \"bentoml.metrics\")\n    container = _LazyLoader(\"bentoml.container\", globals(), \"bentoml.container\")\n    client = _LazyLoader(\"bentoml.client\", globals(), \"bentoml.client\")\n    server = _LazyLoader(\"bentoml.server\", globals(), \"bentoml.server\")\n    exceptions = _LazyLoader(\"bentoml.exceptions\", globals(), \"bentoml.exceptions\")\n    monitoring = _LazyLoader(\"bentoml.monitoring\", globals(), \"bentoml.monitoring\")\n    cloud = _LazyLoader(\"bentoml.cloud\", globals(), \"bentoml.cloud\")\n\n    del _LazyLoader\n\n__all__ = [\n    \"__version__\",\n    \"Context\",\n    \"Cookie\",\n    \"Service\",\n    \"models\",\n    \"batch\",\n    \"metrics\",\n    \"container\",\n    \"client\",\n    \"server\",\n    \"io\",\n    \"Tag\",\n    \"Model\",\n    \"Runner\",\n    \"Runnable\",\n    \"monitoring\",\n    \"YataiClient\",  # Yatai REST API Client\n    # bento APIs\n    \"list\",\n    \"get\",\n    \"delete\",\n    \"import_bento\",\n    \"export_bento\",\n    \"load\",\n    \"push\",\n    \"pull\",\n    \"serve\",\n    \"Bento\",\n    \"exceptions\",\n    # server APIs\n    \"HTTPServer\",\n    \"GrpcServer\",\n    # Framework specific modules\n    \"catboost\",\n    \"detectron\",\n    \"diffusers\",\n    \"easyocr\",\n    \"flax\",\n    \"fastai\",\n    \"gluon\",\n    \"h2o\",\n    \"lightgbm\",\n    \"mlflow\",\n    \"onnx\",\n    \"onnxmlir\",\n    \"paddle\",\n    \"picklable_model\",\n    \"pycaret\",\n    \"pytorch\",\n    \"pytorch_lightning\",\n    \"keras\",\n    \"sklearn\",\n    \"spacy\",\n    \"statsmodels\",\n    \"tensorflow\",\n    \"tensorflow_v1\",\n    \"torchscript\",\n    \"transformers\",\n    \"xgboost\",\n    # integrations\n    \"ray\",\n    \"cloud\",\n    \"triton\",\n    \"monitor\",\n    \"load_config\",\n    \"save_config\",\n    \"set_serialization_strategy\",\n]\n", "path": "src/bentoml/__init__.py"}], "after_files": [{"content": "\"\"\"\nBentoML\n=======\n\nBentoML is the unified ML Model Serving framework. Data Scientists and ML Engineers use\nBentoML to:\n\n* Accelerate and standardize the process of taking ML models to production across teams\n* Build reliable, scalable, and high performance model serving systems\n* Provide a flexible MLOps platform that grows with your Data Science needs\n\nTo learn more, visit BentoML documentation at: http://docs.bentoml.com\nTo get involved with the development, find us on GitHub: https://github.com/bentoml\nAnd join us in the BentoML slack community: https://l.bentoml.com/join-slack\n\"\"\"\n\nfrom typing import TYPE_CHECKING\n\nfrom ._internal.configuration import BENTOML_VERSION as __version__\nfrom ._internal.configuration import load_config\nfrom ._internal.configuration import save_config\nfrom ._internal.configuration import set_serialization_strategy\n\n# Inject dependencies and configurations\nload_config()\n\n# BentoML built-in types\nfrom ._internal.bento import Bento\nfrom ._internal.cloud import YataiClient\nfrom ._internal.context import ServiceContext as Context\nfrom ._internal.models import Model\nfrom ._internal.monitoring import monitor\nfrom ._internal.resource import Resource\nfrom ._internal.runner import Runnable\nfrom ._internal.runner import Runner\nfrom ._internal.runner.strategy import Strategy\nfrom ._internal.service import Service\nfrom ._internal.service.loader import load\nfrom ._internal.tag import Tag\nfrom ._internal.utils.http import Cookie\n\n# Bento management APIs\nfrom .bentos import delete\nfrom .bentos import export_bento\nfrom .bentos import get\nfrom .bentos import import_bento\nfrom .bentos import list  # pylint: disable=W0622\nfrom .bentos import pull\nfrom .bentos import push\nfrom .bentos import serve\n\n# server API\nfrom .server import GrpcServer\nfrom .server import HTTPServer\n\n# Framework specific modules, model management and IO APIs are lazily loaded upon import.\nif TYPE_CHECKING:\n    from . import catboost\n    from . import detectron\n    from . import diffusers\n    from . import easyocr\n    from . import fastai\n    from . import flax\n    from . import gluon\n    from . import h2o\n    from . import keras\n    from . import lightgbm\n    from . import mlflow\n    from . import onnx\n    from . import onnxmlir\n    from . import paddle\n    from . import picklable_model\n    from . import pycaret\n    from . import pytorch\n    from . import pytorch_lightning\n    from . import ray\n    from . import sklearn\n    from . import spacy\n    from . import statsmodels\n    from . import tensorflow\n    from . import tensorflow_v1\n    from . import torchscript\n    from . import transformers\n    from . import triton\n    from . import xgboost\n\n    # isort: off\n    from . import io\n    from . import models\n    from . import metrics  # Prometheus metrics client\n    from . import container  # Container API\n    from . import client  # Client API\n    from . import batch  # Batch API\n    from . import exceptions  # BentoML exceptions\n    from . import server  # Server API\n    from . import monitoring  # Monitoring API\n    from . import cloud  # Cloud API\n\n    # isort: on\nelse:\n    from ._internal.utils import LazyLoader as _LazyLoader\n\n    # ML Frameworks\n    catboost = _LazyLoader(\"bentoml.catboost\", globals(), \"bentoml.catboost\")\n    detectron = _LazyLoader(\"bentoml.detectron\", globals(), \"bentoml.detectron\")\n    diffusers = _LazyLoader(\"bentoml.diffusers\", globals(), \"bentoml.diffusers\")\n    easyocr = _LazyLoader(\"bentoml.easyocr\", globals(), \"bentoml.easyocr\")\n    flax = _LazyLoader(\"bentoml.flax\", globals(), \"bentoml.flax\")\n    fastai = _LazyLoader(\"bentoml.fastai\", globals(), \"bentoml.fastai\")\n    gluon = _LazyLoader(\"bentoml.gluon\", globals(), \"bentoml.gluon\")\n    h2o = _LazyLoader(\"bentoml.h2o\", globals(), \"bentoml.h2o\")\n    lightgbm = _LazyLoader(\"bentoml.lightgbm\", globals(), \"bentoml.lightgbm\")\n    mlflow = _LazyLoader(\"bentoml.mlflow\", globals(), \"bentoml.mlflow\")\n    onnx = _LazyLoader(\"bentoml.onnx\", globals(), \"bentoml.onnx\")\n    onnxmlir = _LazyLoader(\"bentoml.onnxmlir\", globals(), \"bentoml.onnxmlir\")\n    keras = _LazyLoader(\"bentoml.keras\", globals(), \"bentoml.keras\")\n    paddle = _LazyLoader(\"bentoml.paddle\", globals(), \"bentoml.paddle\")\n    pycaret = _LazyLoader(\"bentoml.pycaret\", globals(), \"bentoml.pycaret\")\n    pytorch = _LazyLoader(\"bentoml.pytorch\", globals(), \"bentoml.pytorch\")\n    pytorch_lightning = _LazyLoader(\n        \"bentoml.pytorch_lightning\", globals(), \"bentoml.pytorch_lightning\"\n    )\n    sklearn = _LazyLoader(\"bentoml.sklearn\", globals(), \"bentoml.sklearn\")\n    picklable_model = _LazyLoader(\n        \"bentoml.picklable_model\", globals(), \"bentoml.picklable_model\"\n    )\n    spacy = _LazyLoader(\"bentoml.spacy\", globals(), \"bentoml.spacy\")\n    statsmodels = _LazyLoader(\"bentoml.statsmodels\", globals(), \"bentoml.statsmodels\")\n    tensorflow = _LazyLoader(\"bentoml.tensorflow\", globals(), \"bentoml.tensorflow\")\n    tensorflow_v1 = _LazyLoader(\n        \"bentoml.tensorflow_v1\", globals(), \"bentoml.tensorflow_v1\"\n    )\n    torchscript = _LazyLoader(\"bentoml.torchscript\", globals(), \"bentoml.torchscript\")\n    transformers = _LazyLoader(\n        \"bentoml.transformers\", globals(), \"bentoml.transformers\"\n    )\n    xgboost = _LazyLoader(\"bentoml.xgboost\", globals(), \"bentoml.xgboost\")\n\n    # Integrations\n    triton = _LazyLoader(\"bentoml.triton\", globals(), \"bentoml.triton\")\n    ray = _LazyLoader(\"bentoml.ray\", globals(), \"bentoml.ray\")\n\n    io = _LazyLoader(\"bentoml.io\", globals(), \"bentoml.io\")\n    batch = _LazyLoader(\"bentoml.batch\", globals(), \"bentoml.batch\")\n    models = _LazyLoader(\"bentoml.models\", globals(), \"bentoml.models\")\n    metrics = _LazyLoader(\"bentoml.metrics\", globals(), \"bentoml.metrics\")\n    container = _LazyLoader(\"bentoml.container\", globals(), \"bentoml.container\")\n    client = _LazyLoader(\"bentoml.client\", globals(), \"bentoml.client\")\n    server = _LazyLoader(\"bentoml.server\", globals(), \"bentoml.server\")\n    exceptions = _LazyLoader(\"bentoml.exceptions\", globals(), \"bentoml.exceptions\")\n    monitoring = _LazyLoader(\"bentoml.monitoring\", globals(), \"bentoml.monitoring\")\n    cloud = _LazyLoader(\"bentoml.cloud\", globals(), \"bentoml.cloud\")\n\n    del _LazyLoader\n\n__all__ = [\n    \"__version__\",\n    \"Context\",\n    \"Cookie\",\n    \"Service\",\n    \"models\",\n    \"batch\",\n    \"metrics\",\n    \"container\",\n    \"client\",\n    \"server\",\n    \"io\",\n    \"Tag\",\n    \"Model\",\n    \"Runner\",\n    \"Runnable\",\n    \"monitoring\",\n    \"YataiClient\",  # Yatai REST API Client\n    # bento APIs\n    \"list\",\n    \"get\",\n    \"delete\",\n    \"import_bento\",\n    \"export_bento\",\n    \"load\",\n    \"push\",\n    \"pull\",\n    \"serve\",\n    \"Bento\",\n    \"exceptions\",\n    # server APIs\n    \"HTTPServer\",\n    \"GrpcServer\",\n    # Framework specific modules\n    \"catboost\",\n    \"detectron\",\n    \"diffusers\",\n    \"easyocr\",\n    \"flax\",\n    \"fastai\",\n    \"gluon\",\n    \"h2o\",\n    \"lightgbm\",\n    \"mlflow\",\n    \"onnx\",\n    \"onnxmlir\",\n    \"paddle\",\n    \"picklable_model\",\n    \"pycaret\",\n    \"pytorch\",\n    \"pytorch_lightning\",\n    \"keras\",\n    \"sklearn\",\n    \"spacy\",\n    \"statsmodels\",\n    \"tensorflow\",\n    \"tensorflow_v1\",\n    \"torchscript\",\n    \"transformers\",\n    \"xgboost\",\n    # integrations\n    \"ray\",\n    \"cloud\",\n    \"triton\",\n    \"monitor\",\n    \"load_config\",\n    \"save_config\",\n    \"set_serialization_strategy\",\n    \"Strategy\",\n    \"Resource\",\n]\n", "path": "src/bentoml/__init__.py"}]}