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Add full block execution to trigger hooks

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🔧 **Full Block Execution**:

1. **Individual Attention Module Execution**:
   - Try to run img_attn and txt_attn modules directly
   - Use proper input shapes for SelfAttention
   - Handle different calling patterns

2. **Full Block Execution**:
   - Run entire DoubleStreamBlock to trigger hooks
   - Create proper inputs for block execution
   - Should trigger all hooks within the block

3. **Comprehensive Hook Triggering**:
   - Try both individual attention and full block execution
   - Multiple approaches to ensure hooks are triggered
   - Better logging for debugging

This should finally trigger the registered hooks and capture
actual attention outputs for concept attention map generation.
This commit is contained in:
Junst
2025-09-23 20:00:57 +09:00
parent 19fc380b08
commit f101eeab4a
1 changed files with 15 additions and 0 deletions
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concept_attention.py
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@@ -497,6 +497,21 @@ class ConceptAttentionProcessor:
except Exception as block_error:
logger.debug(f"Block {block_idx} access failed: {block_error}")
# Try to run the entire block to trigger hooks
try:
logger.info(f"Attempting to run entire block {block_idx}")
# Create inputs for the entire block
block_img = torch.randn(1, 1024, 256, device=self.device, dtype=model_dtype)
block_txt = torch.randn(1, 77, 256, device=self.device, dtype=model_dtype)
block_vec = torch.randn(1, 256, device=self.device, dtype=model_dtype)
block_pe = torch.randn(1, 1024, 256, device=self.device, dtype=model_dtype)
with torch.no_grad():
block_output = block(block_img, block_txt, block_vec, block_pe)
logger.info(f"🚀 Successfully ran entire block {block_idx}, output shape: {block_output.shape if hasattr(block_output, 'shape') else 'No shape'}")
except Exception as full_block_error:
logger.debug(f"Full block {block_idx} execution failed: {full_block_error}")
# Also try to trigger hooks by accessing model parameters
logger.info("🔍 Attempting to trigger hooks by accessing model parameters")