fix simple attention processor encoder hidden states dimension ordering

src/diffusers/models/attention_processor.py

@@ -400,7 +400,6 @@ def __call__(self, attn: Attention, hidden_states, encoder_hidden_states=None, a
         residual = hidden_states
         hidden_states = hidden_states.view(hidden_states.shape[0], hidden_states.shape[1], -1).transpose(1, 2)
         batch_size, sequence_length, _ = hidden_states.shape
-        encoder_hidden_states = encoder_hidden_states.transpose(1, 2)
 
         attention_mask = attn.prepare_attention_mask(attention_mask, sequence_length, batch_size)
 
@@ -627,7 +626,6 @@ def __init__(self, slice_size):
     def __call__(self, attn: "Attention", hidden_states, encoder_hidden_states=None, attention_mask=None):
         residual = hidden_states
         hidden_states = hidden_states.view(hidden_states.shape[0], hidden_states.shape[1], -1).transpose(1, 2)
-        encoder_hidden_states = encoder_hidden_states.transpose(1, 2)
 
         batch_size, sequence_length, _ = hidden_states.shape
 

src/diffusers/pipelines/unclip/text_proj.py

@@ -77,10 +77,10 @@ def forward(self, *, image_embeddings, prompt_embeds, text_encoder_hidden_states
         # extra tokens of context that are concatenated to the sequence of outputs from the GLIDE text encoder"
         clip_extra_context_tokens = self.clip_extra_context_tokens_proj(image_embeddings)
         clip_extra_context_tokens = clip_extra_context_tokens.reshape(batch_size, -1, self.clip_extra_context_tokens)
+        clip_extra_context_tokens = clip_extra_context_tokens.permute(0, 2, 1)
 
         text_encoder_hidden_states = self.encoder_hidden_states_proj(text_encoder_hidden_states)
         text_encoder_hidden_states = self.text_encoder_hidden_states_norm(text_encoder_hidden_states)
-        text_encoder_hidden_states = text_encoder_hidden_states.permute(0, 2, 1)
-        text_encoder_hidden_states = torch.cat([clip_extra_context_tokens, text_encoder_hidden_states], dim=2)
+        text_encoder_hidden_states = torch.cat([clip_extra_context_tokens, text_encoder_hidden_states], dim=1)
 
         return text_encoder_hidden_states, additive_clip_time_embeddings

tests/pipelines/unclip/test_unclip_image_variation.py

@@ -54,6 +54,7 @@ class UnCLIPImageVariationPipelineFastTests(PipelineTesterMixin, unittest.TestCa
         "decoder_num_inference_steps",
         "super_res_num_inference_steps",
     ]
+    test_xformers_attention = False
 
     @property
     def text_embedder_hidden_size(self):