From 45061f4bbbcfa87d11bbba3cfc2305a650a41c26 Mon Sep 17 00:00:00 2001
From: johnquan <johnquan@google.com>
Date: Fri, 8 Dec 2023 12:16:59 +0000
Subject: [PATCH] Fix lint errors in `parts.py` and `processors.py`.

PiperOrigin-RevId: 589085615
---
 dqn_zoo/parts.py      |  9 ++++-----
 dqn_zoo/processors.py | 23 +++++++++++++++--------
 2 files changed, 19 insertions(+), 13 deletions(-)

diff --git a/dqn_zoo/parts.py b/dqn_zoo/parts.py
index 14276bc..ea28898 100644
--- a/dqn_zoo/parts.py
+++ b/dqn_zoo/parts.py
@@ -22,7 +22,7 @@
 import csv
 import os
 import timeit
-from typing import Any, Iterable, Mapping, Optional, Tuple, Union
+from typing import Any, Iterable, Mapping, Optional, Sequence, Tuple, Union
 
 import distrax
 import dm_env
@@ -123,7 +123,7 @@ def run_loop(
 
 
 def generate_statistics(
-    trackers: Iterable[Any],
+    trackers: Sequence[Any],
     timestep_action_sequence: Iterable[
         Tuple[
             dm_env.Environment,
@@ -329,7 +329,7 @@ def get(self) -> Mapping[str, float]:
     return self._statistics
 
 
-def make_default_trackers(initial_agent: Agent):
+def make_default_trackers(initial_agent: Agent) -> Sequence[Any]:
   return [
       EpisodeTracker(),
       StepRateTracker(),
@@ -461,7 +461,7 @@ def __init__(self, fname: str):
     self._header_written = False
     self._fieldnames = None
 
-  def write(self, values: collections.OrderedDict) -> None:
+  def write(self, values: collections.OrderedDict[str, float]) -> None:
     """Appends given values as new row to CSV file."""
     if self._fieldnames is None:
       self._fieldnames = values.keys()
@@ -479,7 +479,6 @@ def write(self, values: collections.OrderedDict) -> None:
 
   def close(self) -> None:
     """Closes the `CsvWriter`."""
-    pass
 
   def get_state(self) -> Mapping[str, Any]:
     """Retrieves `CsvWriter` state as a `dict` (e.g. for serialization)."""
diff --git a/dqn_zoo/processors.py b/dqn_zoo/processors.py
index 83a0f2d..7774de3 100644
--- a/dqn_zoo/processors.py
+++ b/dqn_zoo/processors.py
@@ -94,7 +94,9 @@ def named_tuple_sequence_stack(values: Sequence[NamedTuple]) -> NamedTuple:
 class Deque:
   """Double ended queue with a maximum length and initial values."""
 
-  def __init__(self, max_length: int, initial_values=None):
+  def __init__(
+      self, max_length: int, initial_values: Optional[Iterable[Any]] = None
+  ):
     self._deque = collections.deque(maxlen=max_length)
     self._initial_values = initial_values or []
 
@@ -102,7 +104,7 @@ def reset(self) -> None:
     self._deque.clear()
     self._deque.extend(self._initial_values)
 
-  def __call__(self, value: Any) -> collections.deque:
+  def __call__(self, value: Any) -> collections.deque[Any]:
     self._deque.append(value)
     return self._deque
 
@@ -297,19 +299,20 @@ def reduce_step_type(
   """Outputs a representative step type from an array of step types."""
   # Zero padding will appear to be FIRST. Padding should only be seen before the
   # FIRST (e.g. 000F) or after LAST (e.g. ML00).
-  if debug:
-    np_step_types = np.array(step_types)
+
   output_step_type = StepType.MID
   for i, step_type in enumerate(step_types):
     if step_type == 0:  # step_type not actually FIRST, but we do expect 000F.
-      if debug and not (np_step_types == 0).all():
-        raise ValueError('Expected zero padding followed by FIRST.')
+      if debug:
+        if not (np.array(step_types) == 0).all():
+          raise ValueError('Expected zero padding followed by FIRST.')
       output_step_type = StepType.FIRST
       break
     elif step_type == StepType.LAST:
       output_step_type = StepType.LAST
-      if debug and not (np_step_types[i + 1 :] == 0).all():
-        raise ValueError('Expected LAST to be followed by zero padding.')
+      if debug:
+        if not (np.array(step_types)[i + 1 :] == 0).all():
+          raise ValueError('Expected LAST to be followed by zero padding.')
       break
     else:
       if step_type != StepType.MID:
@@ -343,8 +346,12 @@ def aggregate_discounts(
       raise ValueError(
           'All discounts should be 0 or 1, got: %s.' % np_discounts
       )
+  else:
+    np_discounts = None
+
   if None in discounts:
     if debug:
+      assert isinstance(np_discounts, np.ndarray)
       if not (np_discounts[-1] is None and (np_discounts[:-1] == 0).all()):
         # Should have [0, 0, 0, None] due to zero padding.
         raise ValueError('Should only have a None discount for FIRST.')