Remove no longer necessary llama-cpp-python patch

modules/llama_cpp_python_hijack.py

@@ -1,8 +1,5 @@
 import importlib
 import platform
-from typing import Sequence
-
-from tqdm import tqdm
 
 from modules import shared
 from modules.cache_utils import process_llamacpp_cache
@@ -49,48 +46,6 @@ def llama_cpp_lib():
     return None
 
 
-def eval_with_progress(self, tokens: Sequence[int]):
-    """
-    A copy of
-
-    https://github.com/abetlen/llama-cpp-python/blob/main/llama_cpp/llama.py
-
-    with tqdm to show prompt processing progress.
-    """
-    assert self._ctx.ctx is not None
-    assert self._batch.batch is not None
-    self._ctx.kv_cache_seq_rm(-1, self.n_tokens, -1)
-
-    if len(tokens) > 1:
-        progress_bar = tqdm(range(0, len(tokens), self.n_batch), desc="Prompt evaluation", leave=False)
-    else:
-        progress_bar = range(0, len(tokens), self.n_batch)
-
-    for i in progress_bar:
-        batch = tokens[i : min(len(tokens), i + self.n_batch)]
-        n_past = self.n_tokens
-        n_tokens = len(batch)
-        self._batch.set_batch(
-            batch=batch, n_past=n_past, logits_all=self.context_params.logits_all
-        )
-        self._ctx.decode(self._batch)
-        # Save tokens
-        self.input_ids[n_past : n_past + n_tokens] = batch
-        # Save logits
-        if self.context_params.logits_all:
-            rows = n_tokens
-            cols = self._n_vocab
-            logits = self._ctx.get_logits()[: rows * cols]
-            self.scores[n_past : n_past + n_tokens, :].reshape(-1)[: :] = logits
-        else:
-            rows = 1
-            cols = self._n_vocab
-            logits = self._ctx.get_logits()[: rows * cols]
-            self.scores[n_past + n_tokens - 1, :].reshape(-1)[: :] = logits
-        # Update n_tokens
-        self.n_tokens += n_tokens
-
-
 def monkey_patch_llama_cpp_python(lib):
     if getattr(lib.Llama, '_is_patched', False):
         # If the patch is already applied, do nothing
@@ -107,7 +62,6 @@ def monkey_patch_llama_cpp_python(lib):
         for output in self.original_generate(*args, **kwargs):
             yield output
 
-    lib.Llama.eval = eval_with_progress
     lib.Llama.original_generate = lib.Llama.generate
     lib.Llama.generate = my_generate