[Encoder Decoder] Add flash_attn kernel support for encoder-decoder models

tests/encoder_decoder/test_e2e_correctness.py

@@ -7,12 +7,18 @@
 import pytest
 from transformers import AutoModelForSeq2SeqLM
 
+from vllm.attention.selector import (_Backend,
+                                     global_force_attn_backend_context_manager)
 from vllm.platforms import current_platform
 from vllm.sequence import SampleLogprobs
 
 from ..conftest import DecoderPromptType
 from ..models.utils import check_logprobs_close
 
+LIST_ENC_DEC_SUPPORTED_BACKENDS = [
+    _Backend.XFORMERS, _Backend.FLASH_ATTN, None
+]
+
 
 def vllm_to_hf_output(
     vllm_output: Tuple[List[int], str, Optional[SampleLogprobs]],
@@ -29,7 +35,8 @@ def vllm_to_hf_output(
 
 
 @pytest.mark.parametrize("model", ["facebook/bart-large-cnn"])
-@pytest.mark.parametrize("dtype", ["bfloat16"])
+@pytest.mark.parametrize("dtype", ["float"])
+@pytest.mark.parametrize("attn_backend", LIST_ENC_DEC_SUPPORTED_BACKENDS)
 @pytest.mark.parametrize("max_tokens", [128])
 @pytest.mark.parametrize("num_logprobs", [5])
 @pytest.mark.parametrize("decoder_prompt_type", list(DecoderPromptType))
@@ -48,6 +55,7 @@ def test_encoder_decoder_e2e(
     num_logprobs: int,
     decoder_prompt_type: DecoderPromptType,
     enforce_eager: bool,
+    attn_backend: _Backend,
 ) -> None:
     '''
     End-to-End (E2E) test for the encoder-decoder framework.
@@ -56,43 +64,49 @@ def test_encoder_decoder_e2e(
     implementations to ensure that both implementations produce consistent
     and correct results.
     '''
-    test_case_prompts = example_encoder_decoder_prompts[decoder_prompt_type]
+    with global_force_attn_backend_context_manager(attn_backend):
+        if attn_backend == _Backend.FLASH_ATTN:
+            # Flash Attention works only with bfloat16 data-type
+            dtype = 'bfloat16'
+        test_case_prompts = example_encoder_decoder_prompts[
+            decoder_prompt_type]
 
-    # Configuration settings for HF baseline
-    hf_kwargs = {
-        "top_k": None,
-        "num_beams": 1,
-        "repetition_penalty": 1.0,
-        "top_p": 1.0,
-        "length_penalty": 1.0,
-        "early_stopping": False,
-        "no_repeat_ngram_size": None,
-        "min_length": 0
-    }
+        # Configuration settings for HF baseline
+        hf_kwargs = {
+            "top_k": None,
+            "num_beams": 1,
+            "repetition_penalty": 1.0,
+            "top_p": 1.0,
+            "length_penalty": 1.0,
+            "early_stopping": False,
+            "no_repeat_ngram_size": None,
+            "min_length": 0
+        }
 
-    with hf_runner(model, dtype=dtype,
-                   auto_cls=AutoModelForSeq2SeqLM) as hf_model:
-        hf_outputs = (hf_model.generate_encoder_decoder_greedy_logprobs_limit(
-            test_case_prompts,
-            max_tokens,
-            num_logprobs,
-            **hf_kwargs,
-        ))
-    with vllm_runner(model, dtype=dtype,
-                     enforce_eager=enforce_eager) as vllm_model:
-        vllm_outputs = vllm_model.generate_encoder_decoder_greedy_logprobs(
-            test_case_prompts, max_tokens, num_logprobs)
+        with hf_runner(model, dtype=dtype,
+                       auto_cls=AutoModelForSeq2SeqLM) as hf_model:
+            hf_outputs = (
+                hf_model.generate_encoder_decoder_greedy_logprobs_limit(
+                    test_case_prompts,
+                    max_tokens,
+                    num_logprobs,
+                    **hf_kwargs,
+                ))
+        with vllm_runner(model, dtype=dtype,
+                         enforce_eager=enforce_eager) as vllm_model:
+            vllm_outputs = vllm_model.generate_encoder_decoder_greedy_logprobs(
+                test_case_prompts, max_tokens, num_logprobs)
 
-    hf_skip_tokens = (1
-                      if decoder_prompt_type == DecoderPromptType.NONE else 0)
+        hf_skip_tokens = (1 if decoder_prompt_type == DecoderPromptType.NONE
+                          else 0)
 
-    check_logprobs_close(
-        outputs_0_lst=hf_outputs,
-        outputs_1_lst=[
-            vllm_to_hf_output(vllm_output, decoder_prompt_type)
-            for vllm_output in vllm_outputs
-        ],
-        name_0="hf",
-        name_1="vllm",
-        num_outputs_0_skip_tokens=hf_skip_tokens,
-    )
+        check_logprobs_close(
+            outputs_0_lst=hf_outputs,
+            outputs_1_lst=[
+                vllm_to_hf_output(vllm_output, decoder_prompt_type)
+                for vllm_output in vllm_outputs
+            ],
+            name_0="hf",
+            name_1="vllm",
+            num_outputs_0_skip_tokens=hf_skip_tokens,
+        )