MLPSpeculator. (#1865)

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Fixes # (issue)


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---------
Co-authored-by: Joshua Rosenkranz <joshua.rosenkranz@gmail.com>

server/text_generation_server/layers/__init__.py

@@ -3,11 +3,11 @@ from text_generation_server.layers.tensor_parallel import (
     TensorParallelRowLinear,
     TensorParallelEmbedding,
 )
-from text_generation_server.layers.speculative import SpeculativeHead
 from text_generation_server.layers.linear import (
     get_linear,
     FastLinear,
 )
+from text_generation_server.layers.speculative import SpeculativeHead
 
 # Just to add the `load` methods.
 from text_generation_server.layers.layernorm import load_layer_norm

server/text_generation_server/layers/medusa.py

@@ -69,10 +69,13 @@ class MedusaHeadV1(nn.Module):
         from safetensors import safe_open
         import json
 
-        use_medusa = config.use_medusa
+        speculator = config.speculator
 
-        medusa_config = str(Path(use_medusa) / "config.json")
-        filename = str(Path(use_medusa) / "medusa_lm_head.safetensors")
+        path = speculator["path"]
+        medusa_config = str(Path(path) / "config.json")
+
+        for fname in speculator["model_paths"]:
+            filename = str(Path(path) / fname)
 
             with open(medusa_config, "r") as f:
                 medusa_config = json.load(f)
@@ -108,10 +111,10 @@ class MedusaHeadV2(nn.Module):
         from safetensors import safe_open
         import json
 
-        use_medusa = config.use_medusa
+        speculator = config.speculator
 
-        medusa_config = str(Path(use_medusa) / "config.json")
-        filename = str(Path(use_medusa) / "medusa_lm_head.safetensors")
+        medusa_config = str(Path(speculator) / "config.json")
+        filename = str(Path(speculator) / "medusa_lm_head.safetensors")
 
         with open(medusa_config, "r") as f:
             medusa_config = json.load(f)

server/text_generation_server/layers/mlp.py

+import torch
+import math
+from torch import nn
+from torch.nn import functional as F
+from typing import Optional, Tuple
+from text_generation_server.layers import TensorParallelEmbedding, FastLinear
+from text_generation_server.layers.tensor_parallel import TensorParallelHead
+from text_generation_server.utils.speculate import get_speculate
+
+
+class MLPSpeculatorLayerNorm(nn.Module):
+    """
+    A L2 normalization implementation
+    ...
+    Args
+    ----
+    normalized_shape : int
+        Dimensionality of input data (size of final tensor axis)
+    elementwise_scale_weight : torch.Tensor
+        learned scaling term after normalization?
+    elementwise_shift_bias : torch.Tensor
+        learned bias term after normalization?
+    eps : float
+        Safety term to prevent division by zero. Make sure the chosen value fits in the range of your encoding scheme (i.e. fp16 requires eps >= 6e-8).
+    """
+
+    def __init__(
+        self,
+        prefix,
+        config,
+        weights,
+        eps=1e-06,
+    ):
+        super(MLPSpeculatorLayerNorm, self).__init__()
+        self.weight = weights.get_tensor(f"{prefix}.weight")
+        self.bias = weights.get_tensor(f"{prefix}.bias")
+        self.eps = eps
+
+    def forward(self, x):
+        xf = x
+        xf = xf * torch.rsqrt(xf.pow(2).mean(-1, keepdim=True) + self.eps)
+        x = xf.type_as(x)
+        x = self.weight * x
+        x = x + self.bias
+        return x
+
+
+class MLPSpeculatorModel(torch.nn.Module):
+    def __init__(self, config, prefix, weights):
+        super().__init__()
+        self.config = config
+        self.n_predict = get_speculate()
+        self.hidden_size = config.hidden_size
+        self.emb = nn.ModuleList(
+            [
+                TensorParallelEmbedding(f"{prefix}.emb.{i}", weights)
+                for i in range(self.n_predict)
+            ]
+        )
+        self.proj = [
+            FastLinear.load(
+                config,
+                prefix=f"{prefix}.proj.{i}",
+                weights=weights,
+                bias=False,
+            )
+            for i in range(self.n_predict)
+        ]
+        self.head = nn.ModuleList(
+            [
+                FastLinear.load(config, f"{prefix}.head.{i}", weights, bias=False)
+                for i in range(self.n_predict)
+            ]
+        )
+        self.ln = nn.ModuleList(
+            [
+                MLPSpeculatorLayerNorm(
+                    prefix=f"{prefix}.ln.{i}",
+                    config=config,
+                    weights=weights,
+                )
+                for i in range(self.n_predict)
+            ]
+        )
+
+        # Weights ensure that state_0 accounts for 50% of state magnitude by final head in expectation
+        self.state_weight = 0.5 ** (0.5 / self.n_predict)
+        self.emb_weight = math.sqrt(1 - self.state_weight**2)
+        self.activation = nn.GELU()
+        # TODO
+        self.vsize = config.vocab_size
+        self.inner_dim = config.speculator_config["inner_dim"]
+        self.top_k_tokens_per_head = [1] * self.n_predict
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        input_ids: torch.Tensor,
+    ):
+        top_k_tokens_per_head = self.top_k_tokens_per_head
+
+        # k indicates # of candidates
+        # h indicates # of generated tokens
+        state = hidden_states
+        b = state.size(0)
+        ind = input_ids.unsqueeze(0)
+        all_probs = torch.empty(
+            b, self.n_predict, self.vsize, device=state.device
+        )  # b k h v
+        assert (
+            len(top_k_tokens_per_head) == self.n_predict
+        ), f"You must provide a topk number for each head ({self.n_predict} heads, {len(top_k_tokens_per_head)} provided)"
+        for i in range(self.n_predict):
+            # Project and predict
+            z = self.emb[i](ind)
+            z = z.mul(self.emb_weight * math.sqrt(self.inner_dim / 2))  # b k d
+            state = self.proj[i](state) * self.state_weight + z
+            state = self.activation(self.ln[i](state))  # b k d
+            probs = F.log_softmax(self.head[i](state), dim=-1)  # b k v
+            _probs, preds = probs.topk(top_k_tokens_per_head[i], dim=-1)  # b k k'
+
+            # Update candidate set with new predictions
+
+            # Update distribution set with new logits
+            all_probs[:, i] = probs.exp()
+
+            # Update state, log_probs and ind for new predictions
+            state = state.unsqueeze(2).expand(
+                -1, -1, top_k_tokens_per_head[i], -1
+            )  # b k k' d
+            state = state.reshape(-1, b, state.size(3))  # b kk' d
+            ind = preds.view(-1, b)  # b kk'
+
+        speculative_logits = all_probs
+        return speculative_logits
+
+
+class MLPSpeculatorHead(nn.Module):
+    def __init__(self, lm_head, mlp_speculator):
+        super().__init__()
+        self.lm_head = lm_head
+        self.mlp_speculator = mlp_speculator
+
+    def forward(
+        self, input: torch.Tensor
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
+        logits = self.lm_head(input)
+        # If we have too many tokens, we skip speculative logits
+        if input.shape[0] > 128:
+            return logits, None
+
+        input_ids = logits.argmax(dim=-1)
+        speculative_logits = self.mlp_speculator(input, input_ids)
+        return logits, speculative_logits
+
+    @staticmethod
+    def load(config, prefix: str, weights):
+        from pathlib import Path
+        from safetensors import safe_open
+
+        speculator_path = config.speculator["path"]
+
+        for fname in config.speculator["model_paths"]:
+            filename = str(Path(speculator_path) / fname)
+            routing = weights.routing
+            with safe_open(filename, framework="pytorch") as f:
+                for k in f.keys():
+                    if k in routing and routing[k] != filename:
+                        raise RuntimeError(
+                            f"Key {k} was found in multiple files: {filename} and {routing[k]}"
+                        )
+                    routing[k] = filename
+
+        mlp_speculator = MLPSpeculatorModel(config, "speculator", weights)
+        lm_head = TensorParallelHead.load(config, prefix, weights)
+        return MLPSpeculatorHead(lm_head, mlp_speculator)

server/text_generation_server/layers/speculative.py

 import torch
+import json
 from typing import Tuple, Optional
-from text_generation_server.layers.medusa import MedusaHeadV1, MedusaHeadV2
 from text_generation_server.layers.tensor_parallel import TensorParallelHead
+from text_generation_server.layers.medusa import MedusaHeadV1, MedusaHeadV2
+from text_generation_server.layers.mlp import MLPSpeculatorHead
 
 
 class SpeculativeHead(torch.nn.Module):
-    def __init__(self, lm_head, medusa):
+    def __init__(self, lm_head, speculator):
         super().__init__()
         self.head = lm_head
-        self.medusa = medusa
+        self.speculator = speculator
 
     @staticmethod
     def load(config, prefix: str, weights):
-        use_medusa = config.use_medusa
-        if use_medusa:
-            lm_head = None
+        speculator = config.speculator
+        if speculator:
+            speculator_path = config.speculator["path"]
+            speculator_config = str(speculator_path / "config.json")
+
+            with open(speculator_config, "r") as f:
+                speculator_config = json.load(f)
+
+            config.speculator_config = speculator_config
             try:
-                medusa = MedusaHeadV1.load(config, prefix, weights)
+                architecture = speculator_config["architectures"][0]
+
+                if architecture == "MLPSpeculatorPreTrainedModel":
+                    speculator = MLPSpeculatorHead.load(config, prefix, weights)
+                else:
+                    speculator = None
+            except KeyError:
+                try:
+                    speculator = MedusaHeadV1.load(config, prefix, weights)
                 except:
-                medusa = MedusaHeadV2(config, prefix, weights)
+                    speculator = MedusaHeadV2(config, prefix, weights)
+            lm_head = None
         else:
             lm_head = TensorParallelHead.load(config, prefix, weights)
-            medusa = None
-        return SpeculativeHead(lm_head, medusa)
+            speculator = None
+        return SpeculativeHead(lm_head, speculator)
 
     def forward(
         self, input: torch.Tensor
     ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
-        if self.medusa is not None:
-            return self.medusa(input)
+        if self.speculator is not None:
+            return self.speculator(input)
 
         assert self.head is not None
         logits = self.head(input)

server/text_generation_server/models/__init__.py

 import torch
+import os
 
 from loguru import logger
 from transformers.configuration_utils import PretrainedConfig
 from transformers.models.auto import modeling_auto
-from huggingface_hub import hf_hub_download
+from huggingface_hub import hf_hub_download, HfApi
 from typing import Optional
 from pathlib import Path
 
@@ -135,8 +136,9 @@ def get_model(
     config_dict, _ = PretrainedConfig.get_config_dict(
         model_id, revision=revision, trust_remote_code=trust_remote_code
     )
+    model_type = config_dict.get("model_type", None)
 
-    use_medusa = None
+    speculator = None
     if "medusa_num_heads" in config_dict:
         medusa_model_id = model_id
         medusa_revision = revision
@@ -156,6 +158,8 @@ def get_model(
         config_dict, _ = PretrainedConfig.get_config_dict(
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
+        # Reload model type from parent.
+        model_type = config_dict.get("model_type", None)
         is_local = Path(medusa_model_id).exists()
         if not is_local:
             medusa_config = hf_hub_download(
@@ -166,11 +170,70 @@ def get_model(
                 revision=medusa_revision,
                 filename="medusa_lm_head.safetensors",
             )
-            use_medusa = Path(medusa_config).parent
+            speculator = {
+                "path": Path(medusa_config).parent,
+                "model_paths": ["medusa_lm_head.safetensors"],
+            }
         else:
-            use_medusa = Path(medusa_model_id)
+            speculator = {
+                "path": Path(medusa_model_id),
+                "model_paths": ["medusa_lm_head.safetensors"],
+            }
 
         method = "medusa"
+    elif model_type == "mlp_speculator":
+        mlp_model_id = model_id
+        mlp_revision = revision
+        model_id = config_dict["base_model_name_or_path"]
+        revision = "main"
+        speculate_mlp = config_dict["n_predict"]
+        if speculate is not None:
+            if speculate > speculate_mlp:
+                raise RuntimeError(
+                    f"Speculate is set to `{speculate}` but this mlp_speculator models only has `{speculate_mlp}` heads, please make them match"
+                )
+            else:
+                set_speculate(speculate)
+        else:
+            set_speculate(speculate_mlp)
+
+        config_dict, _ = PretrainedConfig.get_config_dict(
+            model_id, revision=revision, trust_remote_code=trust_remote_code
+        )
+        # Reload model type from parent.
+        model_type = config_dict.get("model_type", None)
+        is_local = Path(mlp_model_id).exists()
+        extension = ".safetensors"
+        if not is_local:
+            mlp_speculator_config = hf_hub_download(
+                mlp_model_id, revision=mlp_revision, filename="config.json"
+            )
+            api = HfApi()
+            info = api.model_info(mlp_model_id, revision=mlp_revision)
+            filenames = [
+                s.rfilename
+                for s in info.siblings
+                if s.rfilename.endswith(extension)
+                and len(s.rfilename.split("/")) == 1
+                and "arguments" not in s.rfilename
+                and "args" not in s.rfilename
+                and "training" not in s.rfilename
+            ]
+            for filename in filenames:
+                hf_hub_download(
+                    mlp_model_id,
+                    revision=mlp_revision,
+                    filename=filename,
+                )
+            speculator = {
+                "path": Path(mlp_speculator_config).parent,
+                "model_paths": filenames,
+            }
+        else:
+            speculator = Path(mlp_model_id)
+            filenames = [p for p in os.listdir(speculator) if p.endswith(extension)]
+            speculator = {"path": speculator, "model_paths": filenames}
+        method = "mlp_speculator"
     else:
         method = "n-gram"
 
@@ -178,7 +241,6 @@ def get_model(
     if speculate > 0:
         logger.info(f"Using speculation {method} with {speculate} input ids.")
 
-    model_type = config_dict.get("model_type", None)
     if model_type is None:
         # TODO: fix how we determine model type for Mamba
         if "ssm_cfg" in config_dict:
@@ -202,7 +264,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -212,7 +274,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -227,7 +289,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -240,7 +302,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -250,7 +312,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -259,7 +321,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -270,7 +332,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -279,7 +341,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -288,7 +350,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -299,7 +361,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -308,7 +370,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -323,7 +385,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -334,7 +396,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -345,7 +407,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -355,7 +417,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -366,7 +428,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -377,7 +439,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -388,7 +450,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -399,7 +461,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -410,7 +472,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -424,7 +486,7 @@ def get_model(
                     model_id,
                     revision,
                     quantize=quantize,
-                    use_medusa=use_medusa,
+                    speculator=speculator,
                     dtype=dtype,
                     trust_remote_code=trust_remote_code,
                 )
@@ -435,7 +497,7 @@ def get_model(
                     model_id,
                     revision,
                     quantize=quantize,
-                    use_medusa=use_medusa,
+                    speculator=speculator,
                     dtype=dtype,
                     trust_remote_code=trust_remote_code,
                 )
@@ -444,7 +506,7 @@ def get_model(
                     model_id,
                     revision,
                     quantize=quantize,
-                    use_medusa=use_medusa,
+                    speculator=speculator,
                     dtype=dtype,
                     trust_remote_code=trust_remote_code,
                 )
@@ -458,7 +520,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -469,7 +531,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -483,7 +545,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -494,7 +556,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -520,7 +582,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -544,7 +606,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -554,7 +616,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -564,7 +626,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -574,7 +636,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -586,7 +648,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -599,7 +661,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -623,7 +685,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -632,7 +694,7 @@ def get_model(
             model_id,
             revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
@@ -644,7 +706,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
@@ -653,7 +715,7 @@ def get_model(
                 model_id,
                 revision,
                 quantize=quantize,
-                use_medusa=use_medusa,
+                speculator=speculator,
                 dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )

server/text_generation_server/models/bloom.py

@@ -42,7 +42,7 @@ class BLOOMSharded(CausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -71,7 +71,7 @@ class BLOOMSharded(CausalLM):
         )
         config.pad_token_id = 3
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
         filenames = weight_files(model_id, revision=revision, extension=".safetensors")

server/text_generation_server/models/causal_lm.py

@@ -482,12 +482,12 @@ class CausalLM(Model):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
-        if use_medusa:
-            raise RuntimeError("Medusa decoding is not enabled for AutoModel")
+        if speculator:
+            raise RuntimeError("Speculator decoding is not enabled for AutoModel")
 
         if torch.cuda.is_available():
             device = torch.device("cuda")

server/text_generation_server/models/custom_modeling/idefics2.py

@@ -683,9 +683,9 @@ class Idefics2ForConditionalGeneration(nn.Module):
     def __init__(self, prefix, config, weights):
         super().__init__()
         config.vision_config.quantize = config.quantize
-        config.vision_config.use_medusa = config.use_medusa
+        config.vision_config.speculator = config.speculator
         config.text_config.quantize = config.quantize
-        config.text_config.use_medusa = config.use_medusa
+        config.text_config.speculator = config.speculator
 
         vision_config = config.vision_config
         self.text_model = load_text_model(

server/text_generation_server/models/custom_modeling/llava_next.py

@@ -135,7 +135,7 @@ class LlavaNextForConditionalGeneration(nn.Module):
         self.vocab_size = config.text_config.vocab_size
         self.config = config
         config.text_config.quantize = config.quantize
-        config.text_config.use_medusa = config.use_medusa
+        config.text_config.speculator = config.speculator
         self.language_model = load_text_model(
             prefix="language_model" if not prefix else f"{prefix}.language_model",
             config=config.text_config,

server/text_generation_server/models/flash_causal_lm.py

@@ -1101,6 +1101,8 @@ class FlashCausalLM(Model):
             next_token_texts = []
             left = 0
 
+            logger.info(f"Accepted ids {n_accepted_ids}")
+
             current_stopped = False
             for j in range(index, index + n_accepted_ids):
                 # Generated token

server/text_generation_server/models/flash_cohere.py

@@ -24,7 +24,7 @@ class FlashCohere(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -49,7 +49,7 @@ class FlashCohere(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
 

server/text_generation_server/models/flash_dbrx.py

@@ -26,7 +26,7 @@ class FlashDbrx(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -74,7 +74,7 @@ class FlashDbrx(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
 

server/text_generation_server/models/flash_gemma.py

@@ -25,7 +25,7 @@ class FlashGemma(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -50,7 +50,7 @@ class FlashGemma(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
 

server/text_generation_server/models/flash_llama.py

@@ -27,7 +27,7 @@ class FlashLlama(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -71,7 +71,7 @@ class FlashLlama(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
 

server/text_generation_server/models/flash_mistral.py

@@ -313,7 +313,7 @@ class BaseFlashMistral(FlashCausalLM):
         config_cls=AutoConfig,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
         tokenizer_class=AutoTokenizer,
@@ -340,7 +340,7 @@ class BaseFlashMistral(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         # Set context windows
         if getattr(config, "sliding_window", None) is not None:
@@ -567,7 +567,7 @@ class FlashMistral(BaseFlashMistral):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -577,7 +577,7 @@ class FlashMistral(BaseFlashMistral):
             model_id=model_id,
             revision=revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )

server/text_generation_server/models/flash_mixtral.py

@@ -15,7 +15,7 @@ class FlashMixtral(BaseFlashMistral):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -25,7 +25,7 @@ class FlashMixtral(BaseFlashMistral):
             model_id=model_id,
             revision=revision,
             quantize=quantize,
-            use_medusa=use_medusa,
+            speculator=speculator,
             dtype=dtype,
             trust_remote_code=trust_remote_code,
         )

server/text_generation_server/models/flash_neox.py

@@ -25,7 +25,7 @@ class FlashNeoXSharded(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -51,7 +51,7 @@ class FlashNeoXSharded(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
         filenames = weight_files(model_id, revision=revision, extension=".safetensors")

server/text_generation_server/models/flash_phi.py

@@ -25,7 +25,7 @@ class FlashPhi(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -48,7 +48,7 @@ class FlashPhi(FlashCausalLM):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         torch.distributed.barrier(group=self.process_group)
 
@@ -58,7 +58,7 @@ class FlashPhi(FlashCausalLM):
             weights._set_gptq_params(model_id, revision)
 
         model = FlashPhiForCausalLM(config, weights)
-        if use_medusa:
+        if speculator:
             from text_generation_server.utils.medusa import MedusaModel
             from huggingface_hub import hf_hub_download
             import json
@@ -66,19 +66,19 @@ class FlashPhi(FlashCausalLM):
             from pathlib import Path
 
             is_local_model = (
-                Path(use_medusa).exists() and Path(use_medusa).is_dir()
+                Path(speculator).exists() and Path(speculator).is_dir()
             ) or os.getenv("WEIGHTS_CACHE_OVERRIDE", None) is not None
 
             if not is_local_model:
                 medusa_config = hf_hub_download(
-                    use_medusa, revision=revision, filename="config.json"
+                    speculator, revision=revision, filename="config.json"
                 )
                 medusa_head = hf_hub_download(
-                    use_medusa, revision=revision, filename="medusa_lm_head.pt"
+                    speculator, revision=revision, filename="medusa_lm_head.pt"
                 )
             else:
-                medusa_config = str(Path(use_medusa) / "config.json")
-                medusa_head = str(Path(use_medusa) / "medusa_lm_head.pt")
+                medusa_config = str(Path(speculator) / "config.json")
+                medusa_head = str(Path(speculator) / "medusa_lm_head.pt")
 
             with open(medusa_config, "r") as f:
                 config = json.load(f)

server/text_generation_server/models/flash_qwen2.py

@@ -30,7 +30,7 @@ class FlashQwen2(BaseFlashMistral):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -53,7 +53,7 @@ class FlashQwen2(BaseFlashMistral):
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
 
         # Set context windows
         if config.sliding_window is not None:

server/text_generation_server/models/flash_rw.py

@@ -26,7 +26,7 @@ class FlashRWSharded(FlashCausalLM):
         model_id: str,
         revision: Optional[str] = None,
         quantize: Optional[str] = None,
-        use_medusa: Optional[str] = None,
+        speculator: Optional[str] = None,
         dtype: Optional[torch.dtype] = None,
         trust_remote_code: bool = False,
     ):
@@ -66,7 +66,7 @@ class FlashRWSharded(FlashCausalLM):
         )
 
         config.quantize = quantize
-        config.use_medusa = use_medusa
+        config.speculator = speculator
         if config.quantize == "gptq":
             weights._set_gptq_params(model_id, revision)