#!/usr/bin/env python3
"""Patches applied to x-flux-comfyui for ComfyUI compatibility."""
import re

# Fix 1: xflux DoubleStreamBlock.forward doesn't accept attn_mask/transformer_options
# ComfyUI calls block(..., attn_mask=attn_mask, transformer_options=...) which fails
path1 = '/app/custom_nodes/x-flux-comfyui/xflux/src/flux/modules/layers.py'
with open(path1) as f:
    c = f.read()
old1 = '    def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor) -> tuple[Tensor, Tensor]:\n      return self.processor(self, img, txt, vec, pe)'
new1 = '    def forward(self, img: Tensor, txt: Tensor, vec: Tensor, pe: Tensor, attn_mask=None, transformer_options={}, **kwargs):\n      return self.processor(self, img, txt, vec, pe)'
assert old1 in c, f'Fix 1 pattern not found in {path1}'
with open(path1, 'w') as f:
    f.write(c.replace(old1, new1))
print('Fix 1 applied: DoubleStreamBlock.forward accepts attn_mask')

# Fix 2: IPProcessor.forward sdpa dtype mismatch (ip_query=float32, ip_key/value=bfloat16)
# Caused by projection layers loading in bfloat16 while img tensor stays float32
path2 = '/app/custom_nodes/x-flux-comfyui/layers.py'
with open(path2) as f:
    c = f.read()
old2 = '''        ip_attention = F.scaled_dot_product_attention(
            ip_query, 
            ip_key, 
            ip_value, 
            dropout_p=0.0, 
            is_causal=False
        )'''
new2 = '''        ip_attention = F.scaled_dot_product_attention(
            ip_query, 
            ip_key.to(ip_query.dtype), 
            ip_value.to(ip_query.dtype), 
            dropout_p=0.0, 
            is_causal=False
        )'''
assert old2 in c, f'Fix 2 pattern not found in {path2}'
with open(path2, 'w') as f:
    f.write(c.replace(old2, new2))
print('Fix 2 applied: IPProcessor sdpa dtype cast')

print('All fixes applied successfully.')