Samplers: Add frequency and presence penalty

Un-alias repetition penalty from the frequency penalty parameter.

Signed-off-by: kingbri <[email protected]>

OAI/types/common.py

@@ -58,11 +58,6 @@ class CommonCompletionRequest(BaseModel):
     # Default to 150 as 16 makes no sense as a default
     max_tokens: Optional[int] = 150
 
-    # Aliased to repetition_penalty
-    frequency_penalty: Optional[float] = Field(
-        description="Aliased to Repetition Penalty", default=0.0
-    )
-
     # Sampling params
     token_healing: Optional[bool] = False
     temperature: Optional[float] = 1.0
@@ -73,6 +68,8 @@ class CommonCompletionRequest(BaseModel):
     typical: Optional[float] = 1.0
     min_p: Optional[float] = 0.0
     tfs: Optional[float] = 1.0
+    frequency_penalty: Optional[float] = 0.0
+    presence_penalty: Optional[float] = 0.0
     repetition_penalty: Optional[float] = 1.0
     repetition_decay: Optional[int] = 0
     mirostat_mode: Optional[int] = 0
@@ -94,13 +91,6 @@ def to_gen_params(self):
         if isinstance(self.stop, str):
             self.stop = [self.stop]
 
-        # Set repetition_penalty to frequency_penalty if repetition_penalty
-        # isn't already defined
-        if (
-            self.repetition_penalty is None or self.repetition_penalty == 1.0
-        ) and self.frequency_penalty:
-            self.repetition_penalty = self.frequency_penalty
-
         return {
             "stop": self.stop,
             "max_tokens": self.max_tokens,
@@ -116,6 +106,8 @@ def to_gen_params(self):
             "typical": self.typical,
             "min_p": self.min_p,
             "tfs": self.tfs,
+            "frequency_penalty": self.frequency_penalty,
+            "presence_penalty": self.presence_penalty,
             "repetition_penalty": self.repetition_penalty,
             "repetition_range": unwrap(self.repetition_range, -1),
             "repetition_decay": self.repetition_decay,

model.py

@@ -529,6 +529,22 @@ def generate_gen(self, prompt: str, **kwargs):
                 "installed ExLlamaV2 version."
             )
 
+        if (unwrap(kwargs.get("frequency_penalty"), 0.0)) != 0.0 and not hasattr(
+            gen_settings, "token_frequency_penalty"
+        ):
+            logger.warning(
+                "Frequency penalty is not supported by the currently "
+                "installed ExLlamaV2 version."
+            )
+
+        if (unwrap(kwargs.get("presence_penalty"), 0.0)) != 0.0 and not hasattr(
+            gen_settings, "token_presence_penalty"
+        ):
+            logger.warning(
+                "Presence penalty is not supported by the currently "
+                "installed ExLlamaV2 version."
+            )
+
         # Apply settings
         gen_settings.temperature = unwrap(kwargs.get("temperature"), 1.0)
         gen_settings.temperature_last = unwrap(kwargs.get("temperature_last"), False)
@@ -543,6 +559,12 @@ def generate_gen(self, prompt: str, **kwargs):
         # Default tau and eta fallbacks don't matter if mirostat is off
         gen_settings.mirostat_tau = unwrap(kwargs.get("mirostat_tau"), 1.5)
         gen_settings.mirostat_eta = unwrap(kwargs.get("mirostat_eta"), 0.1)
+        gen_settings.token_frequency_penalty = unwrap(
+            kwargs.get("frequency_penalty"), 0.0
+        )
+        gen_settings.token_presence_penalty = unwrap(
+            kwargs.get("presence_penalty"), 0.0
+        )
         gen_settings.token_repetition_penalty = unwrap(
             kwargs.get("repetition_penalty"), 1.0
         )