old_contents: # python3
  # Copyright 2018 DeepMind Technologies Limited. All rights reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """Environment wrapper which converts double-to-single precision."""
  
  from acme import specs
  from acme import types
  from acme.wrappers import base
  
  import dm_env
  import numpy as np
  import tree
  
  
  class SinglePrecisionWrapper(base.EnvironmentWrapper):
    """Wrapper which converts environments from double- to single-precision."""
  
    def _convert_timestep(self, timestep: dm_env.TimeStep) -> dm_env.TimeStep:
      return timestep._replace(
          reward=_convert_value(timestep.reward),
          discount=_convert_value(timestep.discount),
          observation=_convert_value(timestep.observation))
  
    def step(self, action) -> dm_env.TimeStep:
      return self._convert_timestep(self._environment.step(action))
  
    def reset(self) -> dm_env.TimeStep:
      return self._convert_timestep(self._environment.reset())
  
    def action_spec(self):
      return _convert_spec(self._environment.action_spec())
  
    def discount_spec(self):
      return _convert_spec(self._environment.discount_spec())
  
    def observation_spec(self):
      return _convert_spec(self._environment.observation_spec())
  
    def reward_spec(self):
      return _convert_spec(self._environment.reward_spec())
  
  
  def _convert_spec(nested_spec: types.NestedSpec) -> types.NestedSpec:
    """Convert a nested spec."""
  
    def _convert_single_spec(spec: specs.Array):
      """Convert a single spec."""
      if np.issubdtype(spec.dtype, np.float64):
        dtype = np.float32
      elif np.issubdtype(spec.dtype, np.int64):
        dtype = np.int32
      else:
        dtype = spec.dtype
      return spec.replace(dtype=dtype)
  
    return tree.map_structure(_convert_single_spec, nested_spec)
  
  
  def _convert_value(nested_value: types.Nest) -> types.Nest:
    """Convert a nested value given a desired nested spec."""
  
    def _convert_single_value(value):
      if value is not None:
        value = np.array(value, copy=False)
        if np.issubdtype(value.dtype, np.float64):
          value = np.array(value, copy=False, dtype=np.float32)
        elif np.issubdtype(value.dtype, np.int64):
          value = np.array(value, copy=False, dtype=np.int32)
      return value
  
    return tree.map_structure(_convert_single_value, nested_value)
  
new_contents: # python3
  # Copyright 2018 DeepMind Technologies Limited. All rights reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """Environment wrapper which converts double-to-single precision."""
  
  from acme import specs
  from acme import types
  from acme.wrappers import base
  
  import dm_env
  import numpy as np
  import tree
  
  
  class SinglePrecisionWrapper(base.EnvironmentWrapper):
    """Wrapper which converts environments from double- to single-precision."""
  
    def _convert_timestep(self, timestep: dm_env.TimeStep) -> dm_env.TimeStep:
      return timestep._replace(
          reward=_convert_value(timestep.reward),
          discount=_convert_value(timestep.discount),
          observation=_convert_value(timestep.observation))
  
    def step(self, action) -> dm_env.TimeStep:
      return self._convert_timestep(self._environment.step(action))
  
    def reset(self) -> dm_env.TimeStep:
      return self._convert_timestep(self._environment.reset())
  
    def action_spec(self):
      return _convert_spec(self._environment.action_spec())
  
    def discount_spec(self):
      return _convert_spec(self._environment.discount_spec())
  
    def observation_spec(self):
      return _convert_spec(self._environment.observation_spec())
  
    def reward_spec(self):
      return _convert_spec(self._environment.reward_spec())
  
  
  def _convert_spec(nested_spec: types.NestedSpec) -> types.NestedSpec:
    """Convert a nested spec."""
  
    def _convert_single_spec(spec: specs.Array):
      """Convert a single spec."""
      if spec.dtype == 'O':
        # Pass StringArray objects through unmodified.
        return spec
      if np.issubdtype(spec.dtype, np.float64):
        dtype = np.float32
      elif np.issubdtype(spec.dtype, np.int64):
        dtype = np.int32
      else:
        dtype = spec.dtype
      return spec.replace(dtype=dtype)
  
    return tree.map_structure(_convert_single_spec, nested_spec)
  
  
  def _convert_value(nested_value: types.Nest) -> types.Nest:
    """Convert a nested value given a desired nested spec."""
  
    def _convert_single_value(value):
      if value is not None:
        value = np.array(value, copy=False)
        if np.issubdtype(value.dtype, np.float64):
          value = np.array(value, copy=False, dtype=np.float32)
        elif np.issubdtype(value.dtype, np.int64):
          value = np.array(value, copy=False, dtype=np.int32)
      return value
  
    return tree.map_structure(_convert_single_value, nested_value)
  
subject: Handle StringArray observations in single_precision wrapper without crashing.