old_contents: # 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.
  
  """Common JAX type definitions."""
  
  import dataclasses
  from typing import Any, Callable, Dict, Generic, Mapping, TypeVar
  
  from acme import types
  import chex
  import dm_env
  import jax.numpy as jnp
  
  PRNGKey = jnp.ndarray
  Networks = TypeVar('Networks')
  PolicyNetwork = TypeVar('PolicyNetwork')
  Sample = TypeVar('Sample')
  TrainingState = TypeVar('TrainingState')
  
  TrainingMetrics = Mapping[str, jnp.ndarray]
  """Metrics returned by the training step.
  
  Typically these are logged, so the values are expected to be scalars.
  """
  
  Variables = Mapping[str, types.NestedArray]
  """Mapping of variable collections.
  
  A mapping of variable collections, as defined by Learner.get_variables.
  The keys are the collection names, the values are nested arrays representing
  the values of the corresponding collection variables.
  """
  
  
  @chex.dataclass(frozen=True, mappable_dataclass=False)
  class TrainingStepOutput(Generic[TrainingState]):
    state: TrainingState
    metrics: TrainingMetrics
  
  
  Seed = int
  EnvironmentFactory = Callable[[Seed], dm_env.Environment]
  
  
  @dataclasses.dataclass
  class ModelToSnapshot:
    """Stores all necessary info to be able to save a model.
  
    Attributes:
      model: a jax function to be saved.
      params: fixed params to be passed to the function.
      dummy_kwargs: arguments to be passed to the function.
    """
    model: Any  # Callable[params, **dummy_kwargs]
    params: Any
    dummy_kwargs: Dict[str, Any]
  
new_contents: # 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.
  
  """Common JAX type definitions."""
  
  import dataclasses
  from typing import Any, Callable, Dict, Generic, Mapping, TypeVar
  
  from acme import types
  import chex
  import dm_env
  import jax
  import jax.numpy as jnp
  
  PRNGKey = jax.random.KeyArray
  Networks = TypeVar('Networks')
  PolicyNetwork = TypeVar('PolicyNetwork')
  Sample = TypeVar('Sample')
  TrainingState = TypeVar('TrainingState')
  
  TrainingMetrics = Mapping[str, jnp.ndarray]
  """Metrics returned by the training step.
  
  Typically these are logged, so the values are expected to be scalars.
  """
  
  Variables = Mapping[str, types.NestedArray]
  """Mapping of variable collections.
  
  A mapping of variable collections, as defined by Learner.get_variables.
  The keys are the collection names, the values are nested arrays representing
  the values of the corresponding collection variables.
  """
  
  
  @chex.dataclass(frozen=True, mappable_dataclass=False)
  class TrainingStepOutput(Generic[TrainingState]):
    state: TrainingState
    metrics: TrainingMetrics
  
  
  Seed = int
  EnvironmentFactory = Callable[[Seed], dm_env.Environment]
  
  
  @dataclasses.dataclass
  class ModelToSnapshot:
    """Stores all necessary info to be able to save a model.
  
    Attributes:
      model: a jax function to be saved.
      params: fixed params to be passed to the function.
      dummy_kwargs: arguments to be passed to the function.
    """
    model: Any  # Callable[params, **dummy_kwargs]
    params: Any
    dummy_kwargs: Dict[str, Any]
  
subject: Change jax.types.PRNGKey to be jax.random.KeyArray.