fix: error showing time spent in llama perf context print (#1898)

* feat: Sync with llama.cpp

Add `no_perf` field to `llama_context_params` to optionally disable performance timing measurements.

* fix: Display performance metrics by default

---------

Co-authored-by: Andrei <abetlen@gmail.com>

llama_cpp/llama.py

@@ -94,6 +94,7 @@ def __init__(
         offload_kqv: bool = True,
         flash_attn: bool = False,
         # Sampling Params
+        no_perf: bool = False,
         last_n_tokens_size: int = 64,
         # LoRA Params
         lora_base: Optional[str] = None,
@@ -173,6 +174,7 @@ def __init__(
             embedding: Embedding mode only.
             offload_kqv: Offload K, Q, V to GPU.
             flash_attn: Use flash attention.
+            no_perf: Measure performance timings.
             last_n_tokens_size: Maximum number of tokens to keep in the last_n_tokens deque.
             lora_base: Optional path to base model, useful if using a quantized base model and you want to apply LoRA to an f16 model.
             lora_path: Path to a LoRA file to apply to the model.
@@ -351,6 +353,7 @@ def __init__(
         if type_v is not None:
             self.context_params.type_v = type_v
         # Sampling Params
+        self.context_params.no_perf = no_perf
         self.last_n_tokens_size = last_n_tokens_size
 
         self.cache: Optional[BaseLlamaCache] = None
@@ -2093,6 +2096,7 @@ def __getstate__(self):
             offload_kqv=self.context_params.offload_kqv,
             flash_attn=self.context_params.flash_attn,
             # Sampling Params
+            no_perf=self.context_params.no_perf,
             last_n_tokens_size=self.last_n_tokens_size,
             # LoRA Params
             lora_base=self.lora_base,

llama_cpp/llama_cpp.py

@@ -780,6 +780,7 @@ class llama_context_params(ctypes.Structure):
         embeddings (bool): if true, extract embeddings (together with logits)
         offload_kqv (bool): whether to offload the KQV ops (including the KV cache) to GPU
         flash_attn (bool): whether to use flash attention
+        no_perf (bool): whether to measure performance timings
         abort_callback (ggml_abort_callback): abort callback if it returns true, execution of llama_decode() will be aborted
         abort_callback_data (ctypes.ctypes.c_void_p): data for abort_callback
     """
@@ -810,6 +811,7 @@ class llama_context_params(ctypes.Structure):
         embeddings: bool
         offload_kqv: bool
         flash_attn: bool
+        no_perf: bool
         abort_callback: Callable[[ctypes.c_void_p], bool]
         abort_callback_data: ctypes.c_void_p
 
@@ -839,6 +841,7 @@ class llama_context_params(ctypes.Structure):
         ("embeddings", ctypes.c_bool),
         ("offload_kqv", ctypes.c_bool),
         ("flash_attn", ctypes.c_bool),
+        ("no_perf", ctypes.c_bool),
         ("abort_callback", ggml_abort_callback),
         ("abort_callback_data", ctypes.c_void_p),
     ]