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View Code? Open in Web Editor NEWA2RL is a Python library for offline reinforcement learning
Home Page: https://awslabs.github.io/amazon-accessible-rl-sdk/
License: Apache License 2.0
A2RL is a Python library for offline reinforcement learning
Home Page: https://awslabs.github.io/amazon-accessible-rl-sdk/
License: Apache License 2.0
Propose to remove stable_baseline3
from requirements.txt
, and move the affected implementations out from a2rl
to the examples.
stable_baseline3
depends on gym-0.21
which conflicts to the newer version that a2rl
requires. The old gym
version doesn't come with complete type checks, and still with deprecated or removed gym
APIs.
Currently, a2rl
requires stable_baseline3
at these places:
data_generator_gym()
which is used only in data_properties.ipynb
.WhatifWrapper
.In all cases above, the examples still work (fortunately) with a newer gym
.
[UPDATE] Alternatively, investigate whether it's possible to switch to mushroom-rl
. It supports newer gym
, but due to Cython
requirement, need to check how easy is installation on ARM and DL1 instances.
Applying my own data to the BYO Planner code it fails for the Behavioural Clone Planner part, specifically in this line of code:
immediate_cost = df_sar[tokenizer.df_tokenized.rewards[:-1]].values
The reason why it fails is because it assumes that tokenizer.df_tokenized.rewards
is a list with more than one element and it can therefore apply [:-1]
. In my case though:
len(tokenizer.df_tokenized.rewards)
1
which leads to:
tokenizer.df_tokenized.rewards[:-1]
[]
and finally:
df_sar[tokenizer.df_tokenized.rewards[:-1]].values
array([], shape=(1, 0), dtype=float64)
Should this be instead something like:
immediate_cost = immediate_cost = df_sar[tokenizer.df_tokenized.rewards[:-1 if len(tokenizer.df_tokenized.rewards)>1 else 0]].values
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