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modified: src/flux/math.py

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  1. src/flux/__pycache__/__init__.cpython-310.pyc +0 -0
  2. src/flux/__pycache__/_version.cpython-310.pyc +0 -0
  3. src/flux/__pycache__/math.cpython-310.pyc +0 -0
  4. src/flux/__pycache__/model.cpython-310.pyc +0 -0
  5. src/flux/__pycache__/sampling.cpython-310.pyc +0 -0
  6. src/flux/__pycache__/util.cpython-310.pyc +0 -0
  7. src/flux/math.py +2 -2
  8. src/flux/modules/__pycache__/autoencoder.cpython-310.pyc +0 -0
  9. src/flux/modules/__pycache__/conditioner.cpython-310.pyc +0 -0
  10. src/flux/modules/__pycache__/layers.cpython-310.pyc +0 -0
src/flux/__pycache__/__init__.cpython-310.pyc CHANGED
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src/flux/__pycache__/_version.cpython-310.pyc CHANGED
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src/flux/__pycache__/math.cpython-310.pyc CHANGED
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src/flux/__pycache__/model.cpython-310.pyc CHANGED
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src/flux/__pycache__/sampling.cpython-310.pyc CHANGED
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src/flux/__pycache__/util.cpython-310.pyc CHANGED
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src/flux/math.py CHANGED
@@ -111,7 +111,7 @@ def scaled_dot_product_attention(query, key, value, txt_shape, img_shape, cur_st
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  attn_weight = torch.softmax(attn_weight, dim=-1)
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  attn_weight = torch.dropout(attn_weight, dropout_p, train=True)
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- if info['inverse']:
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  print(f"[DEBUG_Inverse] query:\n{query}")
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  print(f"[DEBUG_Inverse] key :\n{key}")
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  print(f"[DEBUG_Inverse] value :\n{value}")
@@ -121,7 +121,7 @@ def scaled_dot_product_attention(query, key, value, txt_shape, img_shape, cur_st
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  print(f"[DEBUG_Sample] key :\n{key}")
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  print(f"[DEBUG_Sample] value :\n{value}")
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  print(f"[DEBUG_Sample] attn_weight values:\n{attn_weight}")
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-
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  if not info['inverse']:
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  # GENERATE MASK
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  txt_img_cross = attn_weight[:, :, -img_shape:, :txt_shape] # lower left part
 
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  attn_weight = torch.softmax(attn_weight, dim=-1)
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  attn_weight = torch.dropout(attn_weight, dropout_p, train=True)
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+ ''' if info['inverse']:
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  print(f"[DEBUG_Inverse] query:\n{query}")
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  print(f"[DEBUG_Inverse] key :\n{key}")
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  print(f"[DEBUG_Inverse] value :\n{value}")
 
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  print(f"[DEBUG_Sample] key :\n{key}")
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  print(f"[DEBUG_Sample] value :\n{value}")
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  print(f"[DEBUG_Sample] attn_weight values:\n{attn_weight}")
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+ '''
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  if not info['inverse']:
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  # GENERATE MASK
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  txt_img_cross = attn_weight[:, :, -img_shape:, :txt_shape] # lower left part
src/flux/modules/__pycache__/autoencoder.cpython-310.pyc CHANGED
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src/flux/modules/__pycache__/conditioner.cpython-310.pyc CHANGED
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src/flux/modules/__pycache__/layers.cpython-310.pyc CHANGED
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