fix mask dtype differ from latent

[qzzz95]

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[gemini-code-assist]

Summary of Changes

Hello @qzzz95, 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 resolves a critical data type discrepancy within the flux_image pipeline. It specifically targets the prepare_masked_latent function, where the interpolated mask tensor's data type is now explicitly aligned with that of the latent tensor. This change is crucial for maintaining tensor compatibility and preventing issues during subsequent operations, such as concatenation, thereby enhancing the robustness of the image processing workflow.

Highlights

• Data Type Consistency: Ensures the interpolated mask tensor explicitly matches the data type of the latent tensor.
• Error Prevention: Addresses a potential data type mismatch in the flux_image pipeline, preventing runtime errors or unexpected behavior during tensor operations like concatenation.

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[gemini-code-assist]

Code Review

This pull request addresses a data type mismatch between the mask and latent tensors within the prepare_masked_latent function. By explicitly casting the interpolated mask to the dtype of the latent tensor, the change ensures that their concatenation does not result in unintended type promotion. This is a good fix that improves the robustness and correctness of the pipeline, especially in mixed-precision scenarios.