OAI: Add skip_special_tokens parameter

Allows the ability to decode special tokens if the user wishes.

Signed-off-by: kingbri <bdashore3@proton.me>

backends/exllamav2/model.py

@@ -17,6 +17,7 @@ from exllamav2 import (
     ExLlamaV2Lora,
 )
 from exllamav2.generator import ExLlamaV2StreamingGenerator, ExLlamaV2Sampler
+from inspect import signature
 from itertools import zip_longest
 from loguru import logger
 from typing import List, Optional, Union
@@ -663,16 +664,6 @@ class ExllamaV2Container:
     def check_unsupported_settings(self, **kwargs):
         """Check and warn the user if a sampler is unsupported. Meant for dev wheels!"""
 
-        if unwrap(kwargs.get("speculative_ngram"), False) and not hasattr(
-            ExLlamaV2StreamingGenerator, "speculative_ngram"
-        ):
-            logger.warning(
-                "Speculative ngram is not supported by the currently "
-                "installed ExLlamaV2 version."
-            )
-
-            kwargs.pop("speculative_ngram")
-
         return kwargs
 
     async def generate_gen(
@@ -907,6 +898,42 @@ class ExllamaV2Container:
             kwargs.get("max_tokens"), self.config.max_seq_len - prompt_tokens
         )
 
+        # This is an inverse of skip_special_tokens
+        decode_special_tokens = unwrap(not kwargs.get("skip_special_tokens"), False)
+
+        begin_stream_args = {
+            "token_healing": token_healing,
+            "loras": self.active_loras,
+            "return_probabilities": request_logprobs > 0,
+            "return_top_tokens": request_logprobs,
+            "return_logits": request_logprobs > 0,
+            "abort_event": abort_event,
+        }
+
+        if self.use_cfg:
+            begin_stream_args.update(
+                {
+                    "input_mask": mask,
+                    "position_offsets": offsets,
+                }
+            )
+
+        # Check if decode_special_tokens is supported
+        # TODO: Remove when a new version of ExllamaV2 is released
+        if decode_special_tokens:
+            begin_stream_signature = signature(self.generator.begin_stream_ex)
+
+            try:
+                _bound_vars = begin_stream_signature.bind_partial(
+                    decode_special_tokens=True
+                )
+                begin_stream_args["decode_special_tokens"] = decode_special_tokens
+            except TypeError:
+                logger.warning(
+                    "skip_special_tokens is not supported by the currently "
+                    "installed ExLlamaV2 version."
+                )
+
         # Log generation options to console
         # Some options are too large, so log the args instead
         log_generation_params(
@@ -920,6 +947,7 @@ class ExllamaV2Container:
             eos_token_id=eos_tokens,
             add_bos_token=add_bos_token,
             ban_eos_token=ban_eos_token,
+            skip_special_tokens=not decode_special_tokens,
             speculative_ngram=self.generator.speculative_ngram,
             logprobs=request_logprobs,
             stop_conditions=stop_conditions,
@@ -948,31 +976,10 @@ class ExllamaV2Container:
                 active_ids = ids[:, max(0, overflow) :]
                 chunk_tokens = self.config.max_seq_len - active_ids.shape[-1]
 
-                # Split for exllama versions that have CFG
-                if self.use_cfg:
-                    self.generator.begin_stream_ex(
-                        active_ids,
-                        gen_settings,
-                        token_healing=token_healing,
-                        loras=self.active_loras,
-                        input_mask=mask,
-                        position_offsets=offsets,
-                        return_probabilities=request_logprobs > 0,
-                        return_top_tokens=request_logprobs,
-                        return_logits=request_logprobs > 0,
-                        abort_event=abort_event,
-                    )
-                else:
-                    self.generator.begin_stream_ex(
-                        active_ids,
-                        gen_settings,
-                        token_healing=token_healing,
-                        loras=self.active_loras,
-                        return_probabilities=request_logprobs > 0,
-                        return_top_tokens=request_logprobs,
-                        return_logits=request_logprobs > 0,
-                        abort_event=abort_event,
-                    )
+                # Kick off the streaming generation
+                self.generator.begin_stream_ex(
+                    active_ids, gen_settings, **begin_stream_args
+                )
 
                 # Reset offsets for subsequent passes if the context is truncated
                 offsets = None

common/sampling.py

@@ -106,6 +106,11 @@ class BaseSamplerRequest(BaseModel):
         examples=[False],
     )
 
+    skip_special_tokens: Optional[bool] = Field(
+        default_factory=lambda: get_default_sampler_value("ban_eos_token", True),
+        examples=[True],
+    )
+
     logit_bias: Optional[Dict[int, float]] = Field(
         default_factory=lambda: get_default_sampler_value("logit_bias"),
         examples=[{"1": 10, "2": 50}],
@@ -246,6 +251,7 @@ class BaseSamplerRequest(BaseModel):
             "stop": self.stop,
             "add_bos_token": self.add_bos_token,
             "ban_eos_token": self.ban_eos_token,
+            "skip_special_tokens": self.skip_special_tokens,
             "token_healing": self.token_healing,
             "logit_bias": self.logit_bias,
             "temperature": self.temperature,