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'])