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Fixes Divide by zero error #61

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Fixes Divide by zero error #61

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52 changes: 32 additions & 20 deletions token_benchmark_ray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@

from transformers import LlamaTokenizerFast


def get_token_throughput_latencies(
model: str,
mean_input_tokens: int,
Expand Down Expand Up @@ -63,7 +64,7 @@ def get_token_throughput_latencies(
"hf-internal-testing/llama-tokenizer"
)
get_token_length = lambda text: len(tokenizer.encode(text))

if not additional_sampling_params:
additional_sampling_params = {}

Expand All @@ -75,17 +76,19 @@ def get_token_throughput_latencies(
num_output_tokens_list = []
prompts = []
for i in range(max_num_completed_requests):
num_output_tokens = (sample_random_positive_int(
num_output_tokens = sample_random_positive_int(
mean_output_tokens, stddev_output_tokens
))
)
num_output_tokens_list.append(num_output_tokens)

prompts.append(randomly_sample_sonnet_lines_prompt(
prompt_tokens_mean=mean_input_tokens,
prompt_tokens_stddev=stddev_input_tokens,
expect_output_tokens=num_output_tokens,
tokenizer=tokenizer
))
prompts.append(
randomly_sample_sonnet_lines_prompt(
prompt_tokens_mean=mean_input_tokens,
prompt_tokens_stddev=stddev_input_tokens,
expect_output_tokens=num_output_tokens,
tokenizer=tokenizer,
)
)
start_time = time.monotonic()
iter = 0
pbar = tqdm(total=max_num_completed_requests)
Expand Down Expand Up @@ -113,13 +116,18 @@ def get_token_throughput_latencies(
for out in outs:
request_metrics, gen_text, _ = out
num_output_tokens = get_token_length(gen_text)
if num_output_tokens:
if num_output_tokens:
request_metrics[common_metrics.INTER_TOKEN_LAT] /= num_output_tokens
else:
request_metrics[common_metrics.INTER_TOKEN_LAT] = 0
request_metrics[common_metrics.NUM_OUTPUT_TOKENS] = num_output_tokens
request_metrics[common_metrics.NUM_TOTAL_TOKENS] = request_metrics[common_metrics.NUM_INPUT_TOKENS] + num_output_tokens
request_metrics[common_metrics.REQ_OUTPUT_THROUGHPUT] = num_output_tokens / request_metrics[common_metrics.E2E_LAT]
request_metrics[common_metrics.NUM_TOTAL_TOKENS] = (
request_metrics[common_metrics.NUM_INPUT_TOKENS] + num_output_tokens
)
if request_metrics[common_metrics.E2E_LAT]:
request_metrics[common_metrics.REQ_OUTPUT_THROUGHPUT] = (
num_output_tokens / request_metrics[common_metrics.E2E_LAT]
)
all_metrics.append(request_metrics)
completed_requests.extend(all_metrics)
pbar.update(len(completed_requests) - num_completed_requests)
Expand All @@ -136,14 +144,18 @@ def get_token_throughput_latencies(
for out in outs:
request_metrics, gen_text, _ = out
num_output_tokens = get_token_length(gen_text)
if num_output_tokens:
if num_output_tokens:
request_metrics[common_metrics.INTER_TOKEN_LAT] /= num_output_tokens
else:
request_metrics[common_metrics.INTER_TOKEN_LAT] = 0
request_metrics[common_metrics.NUM_OUTPUT_TOKENS] = num_output_tokens
request_metrics[common_metrics.NUM_TOTAL_TOKENS] = request_metrics[common_metrics.NUM_INPUT_TOKENS] + num_output_tokens
request_metrics[common_metrics.REQ_OUTPUT_THROUGHPUT] = num_output_tokens / request_metrics[common_metrics.E2E_LAT]

request_metrics[common_metrics.NUM_TOTAL_TOKENS] = (
request_metrics[common_metrics.NUM_INPUT_TOKENS] + num_output_tokens
)
request_metrics[common_metrics.REQ_OUTPUT_THROUGHPUT] = (
num_output_tokens / request_metrics[common_metrics.E2E_LAT]
)

all_metrics.append(request_metrics)
completed_requests.extend(all_metrics)

Expand All @@ -161,7 +173,7 @@ def get_token_throughput_latencies(
}

metadata["results"] = ret

return metadata, completed_requests


Expand Down Expand Up @@ -200,14 +212,14 @@ def flatten(item):

df = pd.DataFrame(metrics)
df_without_errored_req = df[df[common_metrics.ERROR_CODE].isna()]

for key in [
common_metrics.INTER_TOKEN_LAT,
common_metrics.TTFT,
common_metrics.E2E_LAT,
common_metrics.REQ_OUTPUT_THROUGHPUT,
common_metrics.NUM_INPUT_TOKENS,
common_metrics.NUM_OUTPUT_TOKENS
common_metrics.NUM_OUTPUT_TOKENS,
]:
print(key)
ret[key] = {}
Expand Down Expand Up @@ -259,7 +271,7 @@ def flatten(item):

ret[common_metrics.NUM_COMPLETED_REQUESTS] = num_completed_requests
ret[common_metrics.COMPLETED_REQUESTS_PER_MIN] = num_completed_requests_per_min

return ret


Expand Down