[Doc] Fix batch-level DP example

[DarkLight1337]

Purpose

The example doesn't work in offline inference and is not efficient. So just remove use of DP size

Test Plan

Test Result

(Optional) Documentation Update

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

[youkaichao]

Suggested change

	# The vision encoder uses TP=4 (not DP=1) to shard the input data,
	# so the TP size becomes the effective DP size.
	# with `mm_encoder_tp_mode="data"`,
	# the vision encoder runs in data parallel mode,
	# uses TP=4 as its data parallel size to shard the input data.
	# Note that this is irrelevant with the data parallel size of the language model part.

[DarkLight1337]

Updated, see if it is ok now

[gemini-code-assist]

Code Review

This pull request correctly fixes a broken example in the documentation for batch-level data parallelism in multi-modal encoders. The removal of data_parallel_size=2 is appropriate for an offline inference example using LLM() and clarifies the purpose of mm_encoder_tp_mode. The accompanying comment change is also consistent. This is a good documentation fix.

[github-actions]

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