Fix hunyuan 1.5 get_byt5_text_tokens

[helloyongyang]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @helloyongyang, 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 introduces a dedicated function to handle the tokenization of text prompts for the byT5 model within the hunyuan15 input encoder. This change aims to standardize and encapsulate the tokenization process, ensuring that text inputs are correctly prepared with appropriate padding, truncation, and special tokens for model consumption, addressing a potential issue or improving existing tokenization practices.

Highlights

• New Tokenization Utility: A new method, get_byt5_text_tokens, has been added to model.py to specifically handle the tokenization of text prompts for the byT5 model.
• Standardized byT5 Tokenization: This new function encapsulates the logic for tokenizing text using the byT5 tokenizer, ensuring consistent application of parameters like max_length, padding, truncation, and add_special_tokens.

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[gemini-code-assist]

Code Review

This pull request introduces a new helper method get_byt5_text_tokens to encapsulate the tokenization logic for the byT5 model. This is a good refactoring for clarity. My review includes a suggestion to mark this new method as a static method, as it does not depend on the instance's state, which improves code clarity.

[gemini-code-assist]

Since this method doesn't use the instance (self), it can be defined as a static method. This makes it clear that the method's behavior is independent of the object's state. To do this, add the @staticmethod decorator and remove the self parameter.

    @staticmethod
    def get_byt5_text_tokens(byt5_tokenizer, byt5_max_length, text_prompt):