reverts accidental change that removes attn_mask in attn. Improves fl… (#11065)

reverts accidental change that removes attn_mask in attn. Improves flux ptxla by using flash block sizes. Moves encoding outside the for loop.
Co-authored-by: Juan Acevedo <jfacevedo@google.com>

examples/research_projects/pytorch_xla/inference/flux/flux_inference.py

@@ -9,6 +9,7 @@ import torch_xla.debug.metrics as met
 import torch_xla.debug.profiler as xp
 import torch_xla.distributed.xla_multiprocessing as xmp
 import torch_xla.runtime as xr
+from torch_xla.experimental.custom_kernel import FlashAttention
 
 from diffusers import FluxPipeline
 
@@ -36,6 +37,19 @@ def _main(index, args, text_pipe, ckpt_id):
         ckpt_id, text_encoder=None, tokenizer=None, text_encoder_2=None, tokenizer_2=None, torch_dtype=torch.bfloat16
     ).to(device0)
     flux_pipe.transformer.enable_xla_flash_attention(partition_spec=("data", None, None, None), is_flux=True)
+    FlashAttention.DEFAULT_BLOCK_SIZES = {
+        "block_q": 1536,
+        "block_k_major": 1536,
+        "block_k": 1536,
+        "block_b": 1536,
+        "block_q_major_dkv": 1536,
+        "block_k_major_dkv": 1536,
+        "block_q_dkv": 1536,
+        "block_k_dkv": 1536,
+        "block_q_dq": 1536,
+        "block_k_dq": 1536,
+        "block_k_major_dq": 1536,
+    }
 
     prompt = "photograph of an electronics chip in the shape of a race car with trillium written on its side"
     width = args.width
@@ -69,14 +83,14 @@ def _main(index, args, text_pipe, ckpt_id):
     xm.set_rng_state(seed=unique_seed, device=device0)
     times = []
     logger.info("starting inference run...")
+    with torch.no_grad():
+        prompt_embeds, pooled_prompt_embeds, text_ids = text_pipe.encode_prompt(
+            prompt=prompt, prompt_2=None, max_sequence_length=512
+        )
+    prompt_embeds = prompt_embeds.to(device0)
+    pooled_prompt_embeds = pooled_prompt_embeds.to(device0)
     for _ in range(args.itters):
         ts = perf_counter()
-        with torch.no_grad():
-            prompt_embeds, pooled_prompt_embeds, text_ids = text_pipe.encode_prompt(
-                prompt=prompt, prompt_2=None, max_sequence_length=512
-            )
-        prompt_embeds = prompt_embeds.to(device0)
-        pooled_prompt_embeds = pooled_prompt_embeds.to(device0)
 
         if args.profile:
             xp.trace_detached(f"localhost:{profiler_port}", str(profile_path), duration_ms=profile_duration)
@@ -92,7 +106,7 @@ def _main(index, args, text_pipe, ckpt_id):
         if index == 0:
             logger.info(f"inference time: {inference_time}")
         times.append(inference_time)
-    logger.info(f"avg. inference over {args.itters} iterations took {sum(times)/len(times)} sec.")
+    logger.info(f"avg. inference over {args.itters} iterations took {sum(times) / len(times)} sec.")
     image.save(f"/tmp/inference_out-{index}.png")
     if index == 0:
         metrics_report = met.metrics_report()

src/diffusers/models/attention_processor.py

@@ -2339,7 +2339,9 @@ class FluxAttnProcessor2_0:
             query = apply_rotary_emb(query, image_rotary_emb)
             key = apply_rotary_emb(key, image_rotary_emb)
 
-        hidden_states = F.scaled_dot_product_attention(query, key, value, dropout_p=0.0, is_causal=False)
+        hidden_states = F.scaled_dot_product_attention(
+            query, key, value, attn_mask=attention_mask, dropout_p=0.0, is_causal=False
+        )
 
         hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, attn.heads * head_dim)
         hidden_states = hidden_states.to(query.dtype)