Add support for flexible MTP layer architecture in MaxText.

[parambole]

This change allows specifying a different decoder layer type for Multi-Token Prediction (MTP) blocks than the one used in the base model.

• Modified get_decoder_layers in decoders.py and nnx_decoders.py to accept an optional decoder_block_type parameter.
• Updated models.py to read mtp_decoder_type from config and use it to fetch the appropriate layer for MTP blocks, falling back to the base model's last layer if not specified.
• Added mtp_decoder_type to base.yml and types.py.
• Added a new unit test FlexibleMultiTokenPredictionBlockTest to multi_token_prediction_test.py to verify this behavior.

Verified on TPU VM with Llama base + Gemma2 MTP and Mixtral base + Llama MTP.

Description

Start with a short description of what the PR does and how this is a change from
the past.

The rest of the description includes relevant details and context, examples:

• why is this change being made,
• the problem being solved and any relevant context,
• why this is a good solution,
• some information about the specific implementation,
• shortcomings of the solution and possible future improvements.

If the change fixes a bug or a Github issue, please include a link, e.g.,:
FIXES: b/123456
FIXES: #123456

Notice 1: Once all tests pass, the "pull ready" label will automatically be assigned.
This label is used for administrative purposes. Please do not add it manually.

Notice 2: For external contributions, our settings currently require an approval from a MaxText maintainer to trigger CI tests.

Tests

Please describe how you tested this change, and include any instructions and/or
commands to reproduce.

Checklist

Before submitting this PR, please make sure (put X in square brackets):

• I have performed a self-review of my code. For an optional AI review, add the gemini-review label.
• I have necessary comments in my code, particularly in hard-to-understand areas.
• I have run end-to-end tests tests and provided workload links above if applicable.
• I have made or will make corresponding changes to the doc if needed, including adding new documentation pages to the relevant Table of Contents (toctree directive) as explained in our documentation.

[codecov]

Codecov Report

❌ Patch coverage is 36.00000% with 16 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
src/maxtext/models/models.py	17.64%	14 Missing ⚠️
src/maxtext/layers/nnx_decoders.py	60.00%	1 Missing and 1 partial ⚠️

📢 Thoughts on this report? Let us know!