update

src/diffusers/models/unets/unet_2d_condition.py

@@ -55,6 +55,42 @@ from .unet_2d_blocks import (
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
+def _check_to_assign_to_num_attention_heads(attention_head_dim, down_block_types, mid_block_type, up_block_types):
+    # If a new config is passed with the correct value for `num_attention_heads` and `attention_head_dim` is None,
+    # we do not need to reassign anything
+    if attention_head_dim is None:
+        return False
+
+    elif (
+        "CrossAttnDownBlock2D" in down_block_types
+        or "CrossAttnDownBlock2D" in up_block_types
+        or mid_block_type == "UNetMidBlock2DCrossAttn"
+    ):
+        return True
+
+    return False
+
+
+def _set_attention_parameters(num_attention_heads, attention_head_dim, block_out_channels):
+    if num_attention_heads is None:
+        if isinstance(attention_head_dim, int):
+            attention_head_dim = (attention_head_dim,) * len(block_out_channels)
+
+        num_attention_heads = [
+            out_channel // attention_head_dim[i] for i, out_channel in enumerate(block_out_channels)
+        ]
+
+    elif attention_head_dim is None:
+        if isinstance(num_attention_heads, int):
+            num_attention_heads = (num_attention_heads,) * len(block_out_channels)
+
+        attention_head_dim = [
+            out_channel // num_attention_heads[i] for i, out_channel in enumerate(block_out_channels)
+        ]
+
+    return num_attention_heads, attention_head_dim
+
+
 @dataclass
 class UNet2DConditionOutput(BaseOutput):
     """
@@ -225,18 +261,22 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin,
 
         self.sample_size = sample_size
 
-        if num_attention_heads is not None:
+        if (num_attention_heads is not None) and (attention_head_dim is not None):
             raise ValueError(
-                "At the moment it is not possible to define the number of attention heads via `num_attention_heads` because of a naming issue as described in https://github.com/huggingface/diffusers/issues/2011#issuecomment-1547958131. Passing `num_attention_heads` will only be supported in diffusers v0.19."
+                "It is not possible to configure the UNet with both `num_attention_heads` and `attention_head_dim` at the same time. Please set only one of these values."
             )
 
-        # If `num_attention_heads` is not defined (which is the case for most models)
+        _should_assign_num_attention_heads = _check_to_assign_to_num_attention_heads(
-        # it will default to `attention_head_dim`. This looks weird upon first reading it and it is.
+            attention_head_dim, down_block_types, mid_block_type, up_block_types
-        # The reason for this behavior is to correct for incorrectly named variables that were introduced
+        )
-        # when this library was created. The incorrect naming was only discovered much later in https://github.com/huggingface/diffusers/issues/2011#issuecomment-1547958131
+        if _should_assign_num_attention_heads:
-        # Changing `attention_head_dim` to `num_attention_heads` for 40,000+ configurations is too backwards breaking
+            num_attention_heads = attention_head_dim
-        # which is why we correct for the naming here.
+            attention_head_dim = None
-        num_attention_heads = num_attention_heads or attention_head_dim
+            logger.warning(
+                "`attention_head_dim` has been incorrectly configured for this model and will be reassigned to `num_attention_heads`"
+                "Further referance: https://github.com/huggingface/diffusers/issues/2011#issuecomment-1547958131"
+            )
+            self.register_to_config(num_attention_heads=num_attention_heads, attention_head_dim=attention_head_dim)
 
         # Check inputs
         if len(down_block_types) != len(up_block_types):
@@ -254,16 +294,6 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin,
                 f"Must provide the same number of `only_cross_attention` as `down_block_types`. `only_cross_attention`: {only_cross_attention}. `down_block_types`: {down_block_types}."
             )
 
-        if not isinstance(num_attention_heads, int) and len(num_attention_heads) != len(down_block_types):
-            raise ValueError(
-                f"Must provide the same number of `num_attention_heads` as `down_block_types`. `num_attention_heads`: {num_attention_heads}. `down_block_types`: {down_block_types}."
-            )
-
-        if not isinstance(attention_head_dim, int) and len(attention_head_dim) != len(down_block_types):
-            raise ValueError(
-                f"Must provide the same number of `attention_head_dim` as `down_block_types`. `attention_head_dim`: {attention_head_dim}. `down_block_types`: {down_block_types}."
-            )
-
         if isinstance(cross_attention_dim, list) and len(cross_attention_dim) != len(down_block_types):
             raise ValueError(
                 f"Must provide the same number of `cross_attention_dim` as `down_block_types`. `cross_attention_dim`: {cross_attention_dim}. `down_block_types`: {down_block_types}."
@@ -410,6 +440,11 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin,
         self.down_blocks = nn.ModuleList([])
         self.up_blocks = nn.ModuleList([])
 
+        # Compute both attention_head_dim and num_attention_heads for each block
+        num_attention_heads, attention_head_dim = _set_attention_parameters(
+            num_attention_heads, attention_head_dim, block_out_channels
+        )
+
         if isinstance(only_cross_attention, bool):
             if mid_block_only_cross_attention is None:
                 mid_block_only_cross_attention = only_cross_attention
@@ -419,12 +454,6 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin,
         if mid_block_only_cross_attention is None:
             mid_block_only_cross_attention = False
 
-        if isinstance(num_attention_heads, int):
-            num_attention_heads = (num_attention_heads,) * len(down_block_types)
-
-        if isinstance(attention_head_dim, int):
-            attention_head_dim = (attention_head_dim,) * len(down_block_types)
-
         if isinstance(cross_attention_dim, int):
             cross_attention_dim = (cross_attention_dim,) * len(down_block_types)