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Clean up CLI output #473

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Merged
merged 1 commit into from
Apr 25, 2024
Merged

Clean up CLI output #473

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2 changes: 1 addition & 1 deletion build/builder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -340,7 +340,7 @@ def _initialize_model(
quantize,
tokenizer=None,
):
print("Loading model ...")
print("Loading model...")

if builder_args.gguf_path and (builder_args.dso_path or builder_args.pte_path):
print("Setting gguf_kwargs for generate.")
Expand Down
2 changes: 0 additions & 2 deletions build/model.py
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Expand Up @@ -68,7 +68,6 @@ def from_params(cls, params_path):

@classmethod
def from_table(cls, name: str):
print(f"name {name}")
json_path = config_path / f"{name}.json"
if json_path.is_file():
return ModelArgs.from_params(json_path)
Expand All @@ -82,7 +81,6 @@ def from_table(cls, name: str):

@classmethod
def from_name(cls, name: str):
print(f"name {name}")
json_path = config_path / f"{name}.json"
if Path(json_path).is_file():
return ModelArgs.from_params(json_path)
Expand Down
16 changes: 8 additions & 8 deletions generate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -539,9 +539,7 @@ def _main(
if generator_args.chat_mode:
max_seq_length = 2048
print(f"Entering Chat Mode. Will continue chatting back and forth with the language model until the models max context length of {max_seq_length} tokens is hit or until the user says /bye")
get_system_prompt = input("Do you want to enter a system prompt? Enter y for yes and anything else for no. \n")
if (get_system_prompt == "y" or get_system_prompt == "Y"):
system_prompt = input("What is your system prompt? \n")
system_prompt = input("System Prompt [Optional]: ")
if is_llama3_model:
chat_formatter = ChatFormat(tokenizer)
else:
Expand All @@ -567,12 +565,12 @@ def _main(
i += 1
device_sync(device=builder_args.device)
if i >= 0 and generator_args.chat_mode:
prompt = input("What is your prompt? \n")
prompt = input("User: ")
if (prompt == "/bye"):
print("Exiting Chat.\n")
break
if not is_llama3_model:
if system_prompt is not None:
if system_prompt:
prompt = f"{B_INST} {B_SYS}\n{system_prompt.strip()}\n{E_SYS}\n\n{prompt.strip} {E_INST}"
system_prompt = None # can only provide system prompt on first interaction
else:
Expand All @@ -581,7 +579,7 @@ def _main(
tokenizer, prompt, bos=True, device=builder_args.device
)
else:
if system_prompt is not None:
if system_prompt:
encoded = chat_formatter.encode_dialog_prompt([{"role" : "system", "content" : system_prompt}, {"role" : "user", "content" : prompt}])
system_prompt = None
elif(i == 0):
Expand All @@ -595,6 +593,8 @@ def _main(
break

if generator_args.chat_mode and i >= 0:
print("Model: ", end="")

buffer = []
period_id = tokenizer.encode(".")[0]
done_generating = False
Expand Down Expand Up @@ -667,10 +667,10 @@ def callback(x):
tokens_generated = y.size(0) - prompt_length
tokens_sec = tokens_generated / t
aggregate_metrics["tokens_per_sec"].append(tokens_sec)
logging.info(
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Hmm, what's wrong with this being an info? I think for generate it's pretty important to see the perf, isn't it?

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These are being printed after every model response, which breaks up the chat session. It is still printed at info level at the end of conversation (verified for both chat and generate).

logging.debug(
f"Time for inference {i + 1}: {t:.02f} sec total, {tokens_sec:.02f} tokens/sec"
)
logging.info(f"Bandwidth achieved: {model_size * tokens_sec / 1e9:.02f} GB/s")
logging.debug(f"Bandwidth achieved: {model_size * tokens_sec / 1e9:.02f} GB/s")

if (start_pos >= max_seq_length):
print("Max Sequence Length Reached. Ending Conversation.")
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4 changes: 2 additions & 2 deletions tokenizer/tiktoken.py
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Expand Up @@ -85,7 +85,7 @@ def __init__(self, model_path: str):
mergeable_ranks=mergeable_ranks,
special_tokens=self.special_tokens,
)
logger.info(f"Reloaded Tiktoken model from {model_path}")
logger.debug(f"Reloaded Tiktoken model from {model_path}")

# BOS / EOS token IDs
self.n_words: int = self.model.n_vocab
Expand All @@ -96,7 +96,7 @@ def __init__(self, model_path: str):
self.special_tokens["<|end_of_text|>"],
self.special_tokens["<|eot_id|>"],
}
logger.info(
logger.debug(
f"#words: {self.n_words} - BOS ID: {self._bos_id} - EOS ID: {self._eos_id}"
)

Expand Down