示例#1
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 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_dependencies_if_missing(pip_deps)
示例#2
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 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_dependencies=['torchvision'])` when defining a BentoService"
     )
     env.add_pip_dependencies_if_missing(['torch', "fastai"])
示例#3
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 def set_dependencies(self, env: BentoServiceEnv):
     if self.backend == 'onnxruntime':
         env.add_pip_dependencies_if_missing(['onnxruntime'])
示例#4
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 def set_dependencies(self, env: BentoServiceEnv):
     env.add_pip_dependencies_if_missing(['h2o'])
     env.add_conda_dependencies(['openjdk'])
示例#5
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 def set_dependencies(self, env: BentoServiceEnv):
     env.add_pip_dependencies_if_missing(['tensorflow'])
示例#6
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 def set_dependencies(self, env: BentoServiceEnv):
     env.add_pip_dependencies_if_missing(['xgboost'])
示例#7
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 def set_dependencies(self, env: BentoServiceEnv):
     env.add_pip_dependencies_if_missing(['coremltools>=4.0b2'])
示例#8
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 def set_dependencies(self, env: BentoServiceEnv):
     env.add_pip_dependencies_if_missing(["fasttext"])
示例#9
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 def set_dependencies(self, env: BentoServiceEnv):
     env.add_pip_dependencies_if_missing(['lightgbm'])