![]() Mode ( str) – the rendering type Return type Name of module whose attribute is being shadowed, if any. Name ( str) – name of attribute to check forĪlready_found ( bool) – whether this attribute has already been found in a wrapper Sequence getattr_depth_check ( name, already_found ) ¶Ĭheck if an attribute reference is being hidden in a recursive call to _getattr_ Parameters Return RGB images from each environment Return type List of values of ‘attr_name’ in all environments get_images ( ) ¶ Indices ( Union]) – Indices of envs to get attribute from ParametersĪttr_name ( str) – The name of the attribute whose value to return Return attribute from vectorized environment. List of items returned by the environment’s method call abstract get_attr ( attr_name, indices = None ) ¶ Method_name ( str) – The name of the environment method to invoke. abstract env_method ( method_name, * method_args, indices = None, ** method_kwargs ) ¶Ĭall instance methods of vectorized environments. True if the env is wrapped, False otherwise, for each env queried. Method_kwargs – Any keyword arguments to provide in the call Method_args – Any positional arguments to provide in the call Indices ( Union]) – Indices of envs whose method to call Method_name – The name of the environment method to invoke. ![]() None abstract env_is_wrapped ( wrapper_class, indices = None ) ¶Ĭheck if environments are wrapped with a given wrapper. Observation_space ( Space) – the observation spaceĬlean up the environment’s resources. Num_envs ( int) – the number of environments VecEnv ( num_envs, observation_space, action_space ) ¶Īn abstract asynchronous, vectorized environment. step_wait () return obs, reward, done, info env = DummyVecEnv () # Wrap the VecEnv env = VecExtractDictObs ( env, key = "observation" ) VecEnv ¶ class stable_env. step_async ( actions ) def step_wait ( self ) -> VecEnvStepReturn : obs, reward, done, info = self. reset () return obs def step_async ( self, actions : np. _init_ ( venv = venv, observation_space = venv. Similar to Gym's FilterObservation wrapper: :param venv: The vectorized environment :param key: The key of the dictionary observation """ def _init_ ( self, venv : VecEnv, key : str ): self. The supported operators are selection, filter and group by.Import numpy as np from stable_env.base_vec_env import VecEnv, VecEnvStepReturn, VecEnvWrapper class VecExtractDictObs ( VecEnvWrapper ): """ A vectorized wrapper for filtering a specific key from dictionary observations. DDL queries or DML queries are not supported. The current implementation supports only single table read-only queries. The client logs can also be configured to show up on the console. More detailed logs are printed at the debug The Hive client will log, at the info level, whether a query'sĮxecution is being vectorized. Log Information about Vectorized Execution of Queries If it cannot be supported, Hive will execute the query with vectorization turned off. When vectorization is enabled, Hive examines the query and the data to determine whether vectorization can be supported. To enable vectorization, set this configuration parameter: =true HIVE-4160 has the design document for vectorization and tracks the implementation of On the entire column vector, which improves the instruction pipelines and cache usage. Each batch is usually an array of primitive types. Vectorization allows Hive to process a batch of rows together instead of processing
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