Fix buffer tests and truncate

ml-agents/mlagents/trainers/buffer.py

         we're not truncating at each update. Note that we must truncate an integer number of sequence_lengths
         param: max_length: The length at which to truncate the buffer.
         """
-        current_length = len(next(iter(self)))
+        current_length = len(next(iter(self.values())))
         # make max_length an integer number of sequence_lengths
         max_length -= max_length % sequence_length
         if current_length > max_length:

ml-agents/mlagents/trainers/tests/test_buffer.py

         assert la[i] == lb[i]
 
 
-def construct_fake_buffer():
+def construct_fake_processing_buffer():
-            b["vector_observation"].append(
+            b[fake_agent_id]["vector_observation"].append(
                 [
                     100 * fake_agent_id + 10 * step + 1,
                     100 * fake_agent_id + 10 * step + 2,
-            b["action"].append(
+            b[fake_agent_id]["action"].append(
                 [
                     100 * fake_agent_id + 10 * step + 4,
                     100 * fake_agent_id + 10 * step + 5,
 
 
 def test_buffer():
-    b = construct_fake_buffer()
+    b = construct_fake_processing_buffer()
     a = b[1]["vector_observation"].get_batch(
         batch_size=2, training_length=1, sequential=True
     )
 
 
 def test_buffer_sample():
-    b = construct_fake_buffer()
+    b = construct_fake_processing_buffer()
     update_buffer = AgentBuffer()
     b.append_update_buffer(update_buffer, 3, batch_size=None, training_length=2)
     b.append_update_buffer(update_buffer, 2, batch_size=None, training_length=2)
 
 
 def test_buffer_truncate():
-    b = construct_fake_buffer()
+    b = construct_fake_processing_buffer()
-    assert len(b.update_buffer["action"]) == 2
+    assert len(update_buffer["action"]) == 2
 
     b.append_update_buffer(update_buffer, 3, batch_size=None, training_length=2)
     b.append_update_buffer(update_buffer, 2, batch_size=None, training_length=2)