From 5de954f0e3356fe961b503a8a587dfad74aab2da Mon Sep 17 00:00:00 2001 From: 1000850000 user Date: Mon, 27 May 2024 06:54:19 +0000 Subject: [PATCH] made changes to results gathering --- scripts/benchmarks/display_bench_results.py | 10 +- scripts/benchmarks/refs/a100_80gb.csv | 122 ++++++++++---------- scripts/run_benchmarks.sh | 30 +++-- 3 files changed, 80 insertions(+), 82 deletions(-) diff --git a/scripts/benchmarks/display_bench_results.py b/scripts/benchmarks/display_bench_results.py index 63efaf40..b590f26c 100644 --- a/scripts/benchmarks/display_bench_results.py +++ b/scripts/benchmarks/display_bench_results.py @@ -6,14 +6,14 @@ from scripts.benchmarks.benchmark import gather_report, DIR_SAMP_CONFIGS from typing import List -def main(*directories: str, output_filename: str = "results.csv", remove_columns: List[str]): +def main(*directories: str, output_filename: str = "results.csv", remove_columns: List[str] = None): "gather outputs from a list of directories and output to a csv" df, constant = gather_report(*directories, raw=False) # filter result columns to keep by the inverse of remove_columns - df = df[df.columns[~df.columns.isin(remove_columns)]] - # remove root dir from config filename - df["acceleration_framework_config_file"] = df["acceleration_framework_config_file"].str.replace(f"{DIR_SAMP_CONFIGS}", "sample-configurations") + if remove_columns: + df = df[df.columns[~df.columns.isin(remove_columns)]] + errors = [] try: # remove error messages if any @@ -50,7 +50,7 @@ def main(*directories: str, output_filename: str = "results.csv", remove_columns ) parser.add_argument( "--remove_columns", - nargs="+", + nargs="*", help="list of columns to ignore from results.csv", ) diff --git a/scripts/benchmarks/refs/a100_80gb.csv b/scripts/benchmarks/refs/a100_80gb.csv index 0fc08f76..4434d864 100644 --- a/scripts/benchmarks/refs/a100_80gb.csv +++ b/scripts/benchmarks/refs/a100_80gb.csv @@ -1,61 +1,61 @@ 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o_proj,13219430400.0,0.9310146331787109,300.5119,0.799,0.1,1635.609 +,True,baseline-peft-bnb,32,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,1,80893.0,,lora,4,16,q_proj k_proj v_proj o_proj,,,,,, +0.04,True,baseline-peft-bnb,33,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,2,52634.0,46524471808.0,lora,2,16,q_proj k_proj v_proj o_proj,19172741120.0,1.0399916648864747,584.3145,0.205,0.051,420.595 +,True,baseline-peft-bnb,34,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,1,79557.0,,lora,8,16,q_proj k_proj v_proj o_proj,,,,,, +,True,baseline-peft-bnb,35,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,2,80749.0,,lora,4,16,q_proj k_proj v_proj o_proj,,,,,, +0.04,True,accelerated-peft-bnb,36,2e-4,16,0.0,mistralai/Mistral-7B-v0.1,1,19931.0,15860019712.0,lora,4,16,q_proj k_proj v_proj o_proj,4843384320.0,0.9652111371358235,143.3569,0.837,0.209,3428.645 +0.04,True,accelerated-peft-bnb,37,2e-4,16,0.0,mistralai/Mistral-7B-v0.1,2,13497.0,9974622720.0,lora,2,16,q_proj k_proj v_proj o_proj,2727018496.0,0.9277165730794271,86.4307,1.388,0.347,2843.435 +0.09,True,accelerated-peft-bnb,38,2e-4,16,0.0,mistralai/Mistral-7B-v0.1,1,34355.0,26849751552.0,lora,8,16,q_proj k_proj v_proj o_proj,4843777536.0,0.9493892669677735,279.7156,0.858,0.107,3514.427 +0.09,True,accelerated-peft-bnb,39,2e-4,16,0.0,mistralai/Mistral-7B-v0.1,2,21479.0,16587205120.0,lora,4,16,q_proj k_proj v_proj o_proj,2727215104.0,0.9110882759094239,149.3914,1.607,0.201,3290.15 +0.04,True,accelerated-peft-bnb,40,2e-4,16,0.0,mistralai/Mixtral-8x7B-Instruct-v0.1,1,38405.0,36218024448.0,lora,4,16,q_proj k_proj v_proj o_proj,25201389056.0,0.9741149584452311,278.5888,0.431,0.108,1764.32 +0.04,True,accelerated-peft-bnb,41,2e-4,16,0.0,mistralai/Mixtral-8x7B-Instruct-v0.1,2,25592.0,21906697728.0,lora,2,16,q_proj k_proj v_proj o_proj,13219233792.0,0.9300654411315918,172.7359,0.695,0.174,1422.75 +0.09,True,accelerated-peft-bnb,42,2e-4,16,0.0,mistralai/Mixtral-8x7B-Instruct-v0.1,1,50875.0,47207756288.0,lora,8,16,q_proj k_proj v_proj o_proj,25201782272.0,0.9748441060384114,512.2298,0.469,0.059,1919.139 +0.09,True,accelerated-peft-bnb,43,2e-4,16,0.0,mistralai/Mixtral-8x7B-Instruct-v0.1,2,32957.0,29369087488.0,lora,4,16,q_proj k_proj v_proj o_proj,13219430400.0,0.9301350593566895,287.6381,0.834,0.104,1708.814 +0.04,True,accelerated-peft-bnb,44,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,1,72829.0,68159977472.0,lora,4,16,q_proj k_proj v_proj o_proj,37346815488.0,1.118430455525716,1075.2044,0.112,0.028,457.141 +0.04,True,accelerated-peft-bnb,45,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,2,52632.0,46524471808.0,lora,2,16,q_proj k_proj v_proj o_proj,19172741120.0,1.040946865081787,586.651,0.205,0.051,418.92 +,True,accelerated-peft-bnb,46,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,1,80405.0,,lora,8,16,q_proj k_proj v_proj o_proj,,,,,, +,True,accelerated-peft-bnb,47,2e-4,16,0.0,NousResearch/Llama-2-70b-hf,2,80954.0,,lora,4,16,q_proj k_proj v_proj o_proj,,,,,, +0.04,True,accelerated-peft-autogptq,48,2e-4,16,0.0,TheBloke/Mistral-7B-v0.1-GPTQ,1,20453.0,15890329088.0,lora,4,16,q_proj k_proj v_proj o_proj,4873693696.0,1.3805528958638509,151.0359,0.795,0.199,3254.326 +0.04,True,accelerated-peft-autogptq,49,2e-4,16,0.0,TheBloke/Mistral-7B-v0.1-GPTQ,2,17198.0,9952175616.0,lora,2,16,q_proj k_proj v_proj o_proj,3005709312.0,1.1706618309020995,87.4109,1.373,0.343,2811.548 +0.09,True,accelerated-peft-autogptq,50,2e-4,16,0.0,TheBloke/Mistral-7B-v0.1-GPTQ,1,34247.0,26880060928.0,lora,8,16,q_proj k_proj v_proj o_proj,4874086912.0,1.2741642634073893,282.6391,0.849,0.106,3478.076 +0.09,True,accelerated-peft-autogptq,51,2e-4,16,0.0,TheBloke/Mistral-7B-v0.1-GPTQ,2,24783.0,16262768128.0,lora,4,16,q_proj k_proj v_proj o_proj,3005905920.0,1.043952751159668,152.5473,1.573,0.197,3222.083 +0.04,True,accelerated-peft-autogptq,52,2e-4,16,0.0,TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ,1,37461.0,35528093184.0,lora,4,16,q_proj k_proj v_proj o_proj,24511457792.0,0.9936613400777181,263.6066,0.455,0.114,1864.597 +0.04,True,accelerated-peft-autogptq,53,2e-4,16,0.0,TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ,2,46641.0,25708175360.0,lora,2,16,q_proj k_proj v_proj o_proj,12788874240.0,0.9420519828796386,167.065,0.718,0.18,1471.045 +0.09,True,accelerated-peft-autogptq,54,2e-4,16,0.0,TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ,1,49925.0,46517825024.0,lora,8,16,q_proj k_proj v_proj o_proj,24511851008.0,0.9855653127034505,498.9022,0.481,0.06,1970.406 +0.09,True,accelerated-peft-autogptq,55,2e-4,16,0.0,TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ,2,52358.0,27739090432.0,lora,4,16,q_proj k_proj v_proj o_proj,12789070848.0,0.9389812151590983,281.8034,0.852,0.106,1744.195 +0.04,True,accelerated-peft-autogptq,56,2e-4,16,0.0,TheBloke/Llama-2-70B-GPTQ,1,71565.0,65895347200.0,lora,4,16,q_proj k_proj v_proj o_proj,36290144768.0,1.0755928039550782,1060.8387,0.113,0.028,463.331 +0.04,True,accelerated-peft-autogptq,57,2e-4,16,0.0,TheBloke/Llama-2-70B-GPTQ,2,80387.0,45397678592.0,lora,2,16,q_proj k_proj v_proj o_proj,18649885696.0,1.0256956418355305,576.0422,0.208,0.052,426.635 +,True,accelerated-peft-autogptq,58,2e-4,16,0.0,TheBloke/Llama-2-70B-GPTQ,1,80293.0,,lora,8,16,q_proj k_proj v_proj o_proj,,,,,, +0.08,True,accelerated-peft-autogptq,59,2e-4,16,0.0,TheBloke/Llama-2-70B-GPTQ,2,80363.0,70667573760.0,lora,4,16,q_proj k_proj v_proj o_proj,18650082304.0,1.0266701062520345,1089.3291,0.22,0.028,451.214 diff --git a/scripts/run_benchmarks.sh b/scripts/run_benchmarks.sh index 2c526bcb..e08125b3 100644 --- a/scripts/run_benchmarks.sh +++ b/scripts/run_benchmarks.sh @@ -34,19 +34,6 @@ BENCH_RESULT_FILE=benchmarks.csv PIP_REQUIREMENTS_FILE=requirements.txt # ------------- DROP COLUMNS FRO RESULTS ----------------- -RESULTS_FILTER_DEFAULTS=( - 'before_init_mem_cpu' - 'before_init_mem_gpu' - 'init_mem_cpu_alloc_delta' - 'init_mem_cpu_peaked_delta' - 'init_mem_gpu_alloc_delta' - 'init_mem_gpu_peaked_delta' - 'train_mem_cpu_alloc_delta' - 'train_mem_cpu_peaked_delta' - 'train_mem_gpu_alloc_delta' - 'train_mem_gpu_peaked_delta' - ) - # env inputs DRY_RUN=${DRY_RUN:-"false"} NO_DATA_PROCESSING=${NO_DATA_PROCESSING:-"false"} @@ -58,14 +45,12 @@ NUM_GPUS_MATRIX=${1-"1 2"} RESULT_DIR=${2:-"benchmark_outputs"} SCENARIOS_CONFIG=${3:-$SCENARIOS_CONFIG} SCENARIOS_FILTER=${4-$SCNTAG_PEFT_AUTOGPTQ} -RESULTS_FILTER=${5-"${RESULTS_FILTER_DEFAULTS[*]}"} echo "NUM_GPUS_MATRIX: $NUM_GPUS_MATRIX" echo "RESULT_DIR: $RESULT_DIR" echo "SCENARIOS_CONFIG: $SCENARIOS_CONFIG" echo "SCENARIOS_FILTER: $SCENARIOS_FILTER" echo "MEMORY_LOGGING: $MEMORY_LOGGING" -echo "Removing Columns from Report - ${RESULTS_FILTER}" if [ -n "$RESULT_DIR" ]; then echo "The results directory is not empty. " @@ -127,7 +112,20 @@ python $WORKING_DIR/benchmark.py \ # produce the final CSV for checkin # need to set PYTHONPATH because there is an import inside # this will write to the BENCH_RESULT_FILE +# Remove the columns with values already represented by other metrics in the summary report PYTHONPATH=. \ python $WORKING_DIR/display_bench_results.py benchmark_outputs \ --result_file $BENCH_RESULT_FILE \ - --remove_columns $RESULTS_FILTER + --remove_columns \ + 'before_init_mem_cpu' \ + 'before_init_mem_gpu' \ + 'init_mem_cpu_alloc_delta' \ + 'init_mem_cpu_peaked_delta' \ + 'init_mem_gpu_alloc_delta' \ + 'init_mem_gpu_peaked_delta' \ + 'train_mem_cpu_alloc_delta' \ + 'train_mem_cpu_peaked_delta' \ + 'train_mem_gpu_alloc_delta' \ + 'train_mem_gpu_peaked_delta' \ + 'acceleration_framework_config_file' +