def set_dependencies(self, env: BentoServiceEnv):
# Note that keras module is not required, user can use tf.keras as an
# replacement for the keras module. Although tensorflow module is required to
# be used as the default Keras backend
pip_deps = ['tensorflow']
if self._keras_module_name == 'keras':
pip_deps.append('keras')
env.add_pip_packages(pip_deps)
def set_dependencies(self, env: BentoServiceEnv):
logger.warning(
"BentoML by default does not include spacy and torchvision package when "
"using FastaiModelArtifact. To make sure BentoML bundle those packages if "
"they are required for your model, either import those packages in "
"BentoService definition file or manually add them via "
"`@env(pip_packages=['torchvision'])` when defining a BentoService"
)
env.add_pip_packages(['torch', "fastai<2.0.0"])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(['coremltools>=4.0b2'])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(["fasttext"])
def set_dependencies(self, env: BentoServiceEnv):
if self.backend == "onnxruntime":
env.add_pip_packages(["onnxruntime"])
elif self.backend == "onnxruntime-gpu":
env.add_pip_packages(["onnxruntime-gpu"])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(['tensorflow'])
def set_dependencies(self, env: BentoServiceEnv):
if env._infer_pip_packages:
env.add_pip_packages(['xgboost'])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(['spacy'])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(['torch', "detectron2"])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(["easyocr>=1.3.0"])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(['h2o'])
env.add_conda_dependencies(['openjdk'])
def set_dependencies(self, env: BentoServiceEnv):
if env._infer_pip_packages:
env.add_pip_packages(["mxnet"])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(["numpy"])
def set_dependencies(self, env: BentoServiceEnv):
env.add_pip_packages(['pytorch-lightning'])
def set_dependencies(self, env: BentoServiceEnv):
if self.backend == 'onnxruntime':
env.add_pip_packages(['onnxruntime'])
def set_dependencies(self, env: BentoServiceEnv):
if env._infer_pip_packages:
env.add_pip_packages(['scikit-learn'])