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Test chunked #17

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Test chunked #17

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13 changes: 10 additions & 3 deletions llm_bench/load_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,6 +113,8 @@ def __init__(self, distribution: str, mean: int, cap: Optional[int], alpha: floa
raise ValueError(f"Unknown distribution {self.distribution}")

def sample(self) -> int:
return 0

for _ in range(1000):
sample = self.sample_func()
if sample <= 0:
Expand Down Expand Up @@ -250,7 +252,7 @@ def format_payload(self, prompt, max_tokens, images):
"max_tokens": max_tokens,
"stream": self.parsed_options.stream,
"temperature": self.parsed_options.temperature,
"n": self.parsed_options.n,
# "n": self.parsed_options.n,
}
if self.parsed_options.chat:
if images is None:
Expand Down Expand Up @@ -278,7 +280,7 @@ def format_payload(self, prompt, max_tokens, images):
def parse_output_json(self, data, prompt):
usage = data.get("usage", None)

assert len(data["choices"]) == 1, f"Too many choices {len(data['choices'])}"
# assert len(data["choices"]) == 1, f"Too many choices {len(data['choices'])}"
choice = data["choices"][0]
if self.parsed_options.chat:
if self.parsed_options.stream:
Expand All @@ -300,8 +302,13 @@ def parse_output_json(self, data, prompt):
class FireworksProvider(OpenAIProvider):
def format_payload(self, prompt, max_tokens, images):
data = super().format_payload(prompt, max_tokens, images)
data["min_tokens"] = max_tokens
data["prompt"] = [prompt] * self.parsed_options.n
data["min_tokens"] = 1
data["max_tokens"] = 1
data["prompt_cache_max_len"] = self.parsed_options.prompt_cache_max_len
# data["echo"] = True
# data["logprobs"] = 0

return data


Expand Down