-
Notifications
You must be signed in to change notification settings - Fork 32
/
debug.sh
executable file
·57 lines (52 loc) · 3.25 KB
/
debug.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
# script for a debug/developer workflow
# 1. Deletes the existing pfmbench package from the conda env
# 2. Builds and installs a new one
# 3. Runs fmbench as usual
CONDA_ENV_PATH=$CONDA_PREFIX/lib/python3.11/site-packages
CONFIG_FILE_PATH=src/fmbench/configs/bedrock/config-bedrock-llama3-1.yml
CONFIG_FILE_PATH=src/fmbench/configs/llama3.1/8b/config-llama3.1-8b-g5-ec2.yml
#src/fmbench/configs/multimodal/bedrock/config-llama-3-2-11b-vision-instruct-scienceqa.yml
#src/fmbench/configs/multimodal/bedrock/config-llama-3-2-11b-vision-instruct-image-dataset.yml
#src/fmbench/configs/llama3.1/8b/config-llama3.1-8b-g6e.2xl-tp-1-mc-max-djl.yml
#config-ec2-llama3-1-8b-g6e-2xlarge-byoe-ollama.yml
#src/fmbench/configs/bedrock/config-bedrock-llama3-2.yml
#src/fmbench/configs/llama3.1/8b/config-llama3.1-8b-trn1-32xl-deploy-tp-8-ec2.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-trn1-32xlarge-triton-vllm.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-trn1-32xlarge-triton-vllm.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-trn1-32xlarge-triton-djl.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-trn1-32xlarge-triton-djl.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-trn1-32xlarge-triton-vllm.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-g5.12xl-tp-4-mc-max-djl-ec2.yml
#src/fmbench/configs/llama3.1/8b/config-llama3.1-8b-trn32xl-triton.yml
#config-llama3-8b-g5.12xl-tp-4-mc-max-djl-ec2.yml
#config-llama3-8b-g5.12xl-tp-4-mc-max-triton-ec2.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-g5.12xl-tp-2-mc-max-triton-ec2.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-g5.12xl-tp-2-mc-max-triton-ec2.yml
#config-llama3.1-8b-g5.24xl-tp-4-mc-max-ec2.yml
#config-llama3.1-8b-g5.12xl-tp-4-mc-max-ec2.yml
#config-ec2-llama3-1-8b-p5-tp-2-mc-max.yml
#config-llama3.1-8b-trn1-32xl-deploy-tp-8-ec2.yml
#src/fmbench/configs/llama3.1/8b/config-ec2-llama3-1-8b-p5.yml
#src/fmbench/configs/mistral/config-mistral-v3-inf2-48xl-deploy-ec2-tp24.yml
#src/fmbench/configs/llama3.1/8b/config-llama3.1-8b-g5.yml
#src/fmbench/configs/llama3/8b/config-ec2-llama3-8b-m7a-16xlarge.yml
#src/fmbench/configs/mistral/config-mistral-v3-inf2-48xl-deploy-ec2-tp24.yml
#bedrock/config-bedrock-llama3-1-no-streaming.yml
#src/fmbench/configs/bedrock/config-bedrock.yml
#src/fmbench/configs/llama3/8b/config-llama3-8b-g5-streaming.yml
#config-bedrock-llama3-streaming.yml #config-llama3-8b-g5-stream.yml
LOGFILE=fmbench.log
# delete existing install
rm -rf $CONDA_ENV_PATH/fmbench*
# build a new version
poetry build
pip install -U dist/*.whl
# run the newly installed version
echo "going to run fmbench now"
fmbench --config-file $CONFIG_FILE_PATH --local-mode yes --write-bucket placeholder --tmp-dir /tmp> $LOGFILE 2>&1
# Use FMBench to benchmark models on hosted on EC2 using the command below. If you want to write the metrics and results to an
# s3 bucket, replace `placeholder` with the name of that s3 bucket in your AWS account. Optionally, you can send the results to
# a custom tmp directory by setting the '--tmp-dir' argument followed by the path to that custom tmp directory. If '--tmp-dir' is not
# provided, the default 'tmp' directory will be used.
#fmbench --config-file $CONFIG_FILE_PATH --local-mode yes --write-bucket placeholder --tmp-dir /path/to/your_tmp_directory > $LOGFILE 2>&1
echo "all done"