Update actor_critic_cartpole.py

[lmntrx-sys]

a fix for a value error

[gemini-code-assist]

Summary of Changes

Hello @lmntrx-sys, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request updates the actor_critic_cartpole.py example script to address a ValueError by migrating to the gymnasium library and adapting to its API changes. It also aligns tensor operations to directly use TensorFlow functions when TensorFlow is the Keras backend, ensuring the example remains functional and compatible with current library versions.

Highlights

• Library Migration: Updated the example script to use gymnasium instead of the older gym library, ensuring compatibility with the latest environment APIs.
• API Adaptation: Modified the handling of the env.reset() return value on line 101 to correctly unpack the observation (obs, _ = env.reset()), aligning with the gymnasium API which returns a tuple of (observation, info).
• Tensor Operation Alignment: Switched from keras.ops to direct tensorflow tensor operations (tf.convert_to_tensor and tf.expand_dims) on lines 106 and 107, streamlining the code when TensorFlow is configured as the Keras backend.

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[gemini-code-assist]

Code Review

This pull request updates the gym dependency to gymnasium and attempts to fix a value error. While the dependency update is correct, the implementation change introduces a critical bug by using an uninitialized variable. My review identifies this bug and suggests a fix. Additionally, I've pointed out an inconsistency where keras.ops was replaced with direct TensorFlow calls, making the code backend-specific, and I've recommended reverting to keras.ops for consistency, as the original error may have been a side effect of the other bug.

[gemini-code-assist]

The env.reset() call now returns the observation into the obs variable, but the rest of the loop expects this value to be in the state variable. This will cause a NameError on line 106 when state is used before it's assigned a value. To fix this, the observation should be assigned to state.

Suggested change

	obs, _ = env.reset()
	state, _ = env.reset()

[gemini-code-assist]

This change replaces keras.ops with direct tf calls. This makes the code backend-specific and inconsistent with other parts of the script that use keras.ops (e.g., lines 116 and 160). For Keras examples, it's best practice to use the backend-agnostic keras.ops API where possible.

The ValueError mentioned in the PR description might have been a symptom of the uninitialized state variable, which is addressed in another comment. After fixing that issue, keras.ops should be used here for consistency.

Suggested change

	state = tf.convert_to_tensor(state)
	state = tf.expand_dims(state, 0)
	state = ops.convert_to_tensor(state)
	state = ops.expand_dims(state, 0)