remove redundant config #134
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Summary of Changes
Hello @akaitsuki-ii, 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 focuses on code hygiene by eliminating configuration parameters that are no longer necessary or are redundant. The changes streamline the initialization of the QwenImagePipeline and simplify how the tokenizer's maximum length is determined, leading to a cleaner and potentially more robust codebase.
Highlights
- Configuration Cleanup: Removed two seemingly redundant configuration attributes,
self.tokenizer_max_lengthandself.default_sample_size, from theQwenImagePipelineclass's initialization. - Tokenizer Max Length Calculation: Simplified the
max_lengthcalculation within theencode_promptmethod by removing theminoperation that previously constrainedmax_sequence_lengthwith the now-removedself.tokenizer_max_length.
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Code Review
This pull request removes redundant configuration variables from the QwenImagePipeline, simplifying the code and ensuring the max_sequence_length parameter behaves as expected. A suggestion has been made to add a check for max_sequence_length to prevent potential issues with extremely long sequences.
| drop_idx = self.prompt_template_encode_start_idx | ||
| texts = [template.format(txt) for txt in prompt] | ||
| outputs = self.tokenizer(texts, max_length=min(max_sequence_length, self.tokenizer_max_length) + drop_idx) | ||
| outputs = self.tokenizer(texts, max_length=max_sequence_length + drop_idx) |
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The max_length argument is now directly used without considering self.tokenizer_max_length. It's crucial to ensure that max_sequence_length is appropriately constrained to prevent potential out-of-memory errors or unexpected behavior with extremely long sequences. Consider adding a check to ensure max_sequence_length does not exceed a reasonable limit, or document the expected behavior when it does.
outputs = self.tokenizer(texts, max_length=min(max_sequence_length + drop_idx, MAX_TOKEN_LENGTH))
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