Support for Flash Attention 3 (#38972)

* Support `flash_attn_3`
Implements fwd and tests for Flash Attention 3 https://github.com/Dao-AILab/flash-attention/commits/main/hopper

- Includes checks for dropout>0 and ALiBi in `modeling_utils.PreTrainedModel._check_and_enable_flash_attn_3` (Dropout will likely be supported soon, so this will need to be updated and `modeling_flash_attention_utils._flash_attention_forward` at the `if _IS_FLASH_ATTN_3_AVAILABLE: ...`

An example Llama implementation is included in `modeling_llama.py` but other models would still need to be updated

Based on https://github.com/huggingface/transformers/pull/36190 which has model implementations and examples which could be merged

* Add tests for Flash Attention 2 and 3 parity

* ci fix

* FA2 compatibiity
- `_prepare_flash_attention_from_position_ids` ->`prepare_fa2_from_position_ids`
- Remove bettertransformer check in Flash Attention 3
- Merge tests
- Add licensing

* ci fix

* Test naming consistency

* ci fix

* Deprecation warning for `prepare_fa2_from_position_ids`

* ci fix

tests/utils/test_modeling_utils.py

@@ -77,6 +77,7 @@ from transformers.utils import (
 )
 from transformers.utils.import_utils import (
     is_flash_attn_2_available,
+    is_flash_attn_3_available,
     is_flax_available,
     is_tf_available,
     is_torch_npu_available,
@@ -676,6 +677,9 @@ class ModelUtilsTest(TestCasePlus):
         if is_flash_attn_available():
             attn_implementation_available.append("flash_attention_2")
 
+        if is_flash_attn_3_available():
+            attn_implementation_available.append("flash_attention_3")
+
         for requested_attn_implementation in attn_implementation_available:
             model = AutoModelForCausalLM.from_pretrained(
                 TINY_MISTRAL, attn_implementation=requested_attn_implementation
@@ -700,6 +704,9 @@ class ModelUtilsTest(TestCasePlus):
         if is_flash_attn_available():
             attn_implementation_available.append("flash_attention_2")
 
+        if is_flash_attn_3_available():
+            attn_implementation_available.append("flash_attention_3")
+
         for requested_attn_implementation in attn_implementation_available:
             config = AutoConfig.from_pretrained(TINY_MISTRAL, attn_implementation=requested_attn_implementation)
             # Ensure the config was set correctly