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minor cosmetic updates to lpg and checkpoint conversion syntax (#846)
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minor updates to lpg and checkpoint conversion
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vivianrwu authored Oct 8, 2024
1 parent 559e4c8 commit b0588cc
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12 changes: 9 additions & 3 deletions benchmarks/benchmark/tools/profile-generator/README.md
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Expand Up @@ -25,7 +25,7 @@ It currently supports the following frameworks:
- text generation inference (tgi)
- vllm
- sax
-jetstream
- jetstream

## Instructions

Expand All @@ -50,6 +50,12 @@ not logged into gcloud, run the following:
gcloud auth application-default login
```

If you do not already have an output bucket, create one by running:

```
gcloud storage buckets create gs://OUTPUT_BUCKET
```

To give viewer permissions on the gcs bucket to the gcloud service account,
run the following:

Expand Down Expand Up @@ -88,13 +94,13 @@ gcloud artifacts repositories create ai-benchmark --location=us-central1 --repos

### Step 4: create and configure terraform.tfvars

Create a `terraform.tfvars` file. `./sample-tfvars` is provided as an example
Create a `terraform.tfvars` file. `./sample.tfvars` is provided as an example
file. You can copy the file as a starting point.
Note that at a minimum you will have to change the existing
`credentials_config`, `project_id`, and `artifact_registry`.

```bash
cp ./sample-tfvars terraform.tfvars
cp ./sample.tfvars terraform.tfvars
```

Fill out your `terraform.tfvars` with the desired model and server configuration, referring to the list of required and optional variables [here](#variables). The following variables are required:
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Expand Up @@ -555,8 +555,8 @@ def main(args: argparse.Namespace):

# NOTE: The latency below includes requests awaiting time on server side.
# It's not comparable with the model inference latency for batch size 1.
**(get_stats_for_set("latency", "Average milliseconds/request (includes waiting time on server)" ,[1000 * latency for _, _, latency in REQUEST_LATENCY])),
**(get_stats_for_set("per_output_token_latency", "Average milliseconds/output_token (includes waiting time on server)", [1000 * latency / output_len for _, output_len, latency in REQUEST_LATENCY])),
**(get_stats_for_set("latency", "milliseconds/request (includes waiting time on server)" ,[1000 * latency for _, _, latency in REQUEST_LATENCY])),
**(get_stats_for_set("per_output_token_latency", "milliseconds/output_token (includes waiting time on server)", [1000 * latency / output_len for _, output_len, latency in REQUEST_LATENCY])),
**(get_stats_for_set("input_len", "input length", [float(prompt_len) for prompt_len, _, _ in REQUEST_LATENCY])),
**(get_stats_for_set("output_len", "output length", [float(output_len) for _, output_len, _ in REQUEST_LATENCY]))
}
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Expand Up @@ -114,7 +114,7 @@ convert_maxtext_checkpoint() {
git checkout ${VERSION}
python3 -m pip install -r requirements.txt

if [ $VERSION == "jetstream-v0.2.2" || $VERSION == "jetstream-v0.2.1" || $VERSION == "jetstream-v0.2.0" ]; then
if [[ $VERSION == "jetstream-v0.2.2" || $VERSION == "jetstream-v0.2.1" || $VERSION == "jetstream-v0.2.0" ]]; then
pip3 install orbax-checkpoint==0.5.20
else
pip3 install orbax-checkpoint==0.6.0
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