spec: add EAGLE3 speculative decoding support (#18039)

* llama : enable layer input extraction

* spec: support eagle3

* eagle3: fix params bug

* eagle3: support Gemma4 eagle3 from RedHatAI

* eagle3: set sync when get features from target

Co-authored-by: tnhnyzc <115956684+tnhnyzc@users.noreply.github.com>

* eagle3 : fix ubatch handling in embd_layer_inp extraction and encoder

Co-authored-by: Doğaç Eldenk <dogacel@gmail.com>

* eagle3: adapt to upstream changes

* eagle3: fix rebase issues and adapt to upstream changes

* eagle3:exclude the eagle3 arch from test-llama-archs

* eagle3: fix editorconfig check failures

* eagle3: fix multi-seq issue in d2t vocab mapping

* cont : minor style / clean-up

* spec : remove `common_speculative_setup_draft_model()`

* llama : clean-up unused API

* eagle3: set d2t vocab mapping in decode graph

* cont : assert layer inputs are configured

* hparams : use n_embd_inp instead of n_embd_target_features

* eagle3: make output.weight optional and inherit from target model when needed

* haparams : generic norm-before-residual param

* llama-ext : consistent names

* cont : fix

* hparams : remove target_hidden_size

* cparams : rename output_layer_inp -> embeddings_layer_inp

* arch : reuse ATTN_NORM_2 instead of adding new hidden norm

* llama : clean-up names

* cont : add assert + comment

* Update conversion/llama.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: tnhnyzc <115956684+tnhnyzc@users.noreply.github.com>
Co-authored-by: Doğaç Eldenk <dogacel@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

conversion/base.py

@@ -94,6 +94,7 @@ class ModelBase:
     metadata: gguf.Metadata
     dir_model_card: Path
     remote_hf_model_id: str | None
+    target_model_dir: Path | None
 
     # subclasses should define this!
     model_arch: gguf.MODEL_ARCH
@@ -119,6 +120,7 @@ class ModelBase:
                  small_first_shard: bool = False, hparams: dict[str, Any] | None = None, remote_hf_model_id: str | None = None,
                  disable_mistral_community_chat_template: bool = False,
                  sentence_transformers_dense_modules: bool = False,
+                 target_model_dir: Path | None = None,
                  fuse_gate_up_exps: bool = False,
                  fp8_as_q8: bool = False):
         if type(self) is ModelBase or \
@@ -139,6 +141,7 @@ class ModelBase:
         self.dry_run = dry_run
         self.remote_hf_model_id = remote_hf_model_id
         self.sentence_transformers_dense_modules = sentence_transformers_dense_modules
+        self.target_model_dir = target_model_dir
         self.fuse_gate_up_exps = fuse_gate_up_exps
         self._gate_exp_buffer: dict[int, Tensor] = {}
         self._up_exp_buffer: dict[int, Tensor] = {}
@@ -2481,6 +2484,7 @@ class LazyTorchTensor(gguf.LazyBase):
         torch.float16: np.float16,
         torch.float32: np.float32,
         torch.uint8: np.uint8,
+        torch.int64: np.int64,
     }
 
     # only used when byteswapping data. Only correct size is needed