forked from EngineX-Cambricon/enginex-mlu370-vllm
add qwen3
This commit is contained in:
Chranos
@@ -0,0 +1,12 @@
|
||||
# bash ./run-lm-eval-gsm-vllm-baseline.sh -m deepseek-ai/DeepSeek-V2-Lite-Chat -b "auto" -l 1000 -f 5 -t 2
|
||||
model_name: "deepseek-ai/DeepSeek-V2-Lite-Chat"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.671
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.664
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
trust_remote_code: True
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-hf-baseline.sh -m nm-testing/Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform -b auto -l 1000 -f 5
|
||||
model_name: "nm-testing/Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.905
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.905
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-hf-baseline.sh -m meta-llama/Meta-Llama-3-70B-Instruct -b 32 -l 250 -f 5
|
||||
model_name: "meta-llama/Meta-Llama-3-70B-Instruct"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.892
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.892
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Meta-Llama-3-8B-Instruct-W8A8-FP8-Channelwise-compressed-tensors -b auto -l 1000 -f 5 -t 1
|
||||
model_name: "nm-testing/Meta-Llama-3-8B-Instruct-W8A8-FP8-Channelwise-compressed-tensors"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.752
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.754
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Meta-Llama-3-8B-Instruct-FBGEMM-nonuniform -b auto -l 1000 -f 5 -t 1
|
||||
model_name: "nm-testing/Meta-Llama-3-8B-Instruct-FBGEMM-nonuniform"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.753
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.753
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Meta-Llama-3-8B-FP8-compressed-tensors-test -b 32 -l 1000 -f 5 -t 1
|
||||
model_name: "nm-testing/Meta-Llama-3-8B-FP8-compressed-tensors-test"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.755
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.755
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Meta-Llama-3-8B-Instruct-FP8 -b 32 -l 250 -f 5 -t 1
|
||||
model_name: "neuralmagic/Meta-Llama-3-8B-Instruct-FP8"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.753
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.753
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Meta-Llama-3-8B-Instruct-W8-Channel-A8-Dynamic-Asym-Per-Token-Test -b "auto" -l 250 -f 5 -t 1
|
||||
model_name: "nm-testing/Meta-Llama-3-8B-Instruct-W8-Channel-A8-Dynamic-Asym-Per-Token-Test"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.764
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.764
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Meta-Llama-3-8B-Instruct-W8-Channel-A8-Dynamic-Per-Token-Test -b "auto" -l 250 -f 5 -t 1
|
||||
model_name: "nm-testing/Meta-Llama-3-8B-Instruct-W8-Channel-A8-Dynamic-Per-Token-Test"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.728
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.728
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Meta-Llama-3-8B-Instruct-nonuniform-test -b auto -l 1000 -f 5 -t 1
|
||||
model_name: "nm-testing/Meta-Llama-3-8B-Instruct-nonuniform-test"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.758
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.759
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-hf-baseline.sh -m meta-llama/Meta-Llama-3-8B-Instruct -b 32 -l 250 -f 5 -t 1
|
||||
model_name: "meta-llama/Meta-Llama-3-8B-Instruct"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.756
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.752
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m HandH1998/QQQ-Llama-3-8b-g128 -b 32 -l 1000 -f 5 -t 1
|
||||
model_name: "HandH1998/QQQ-Llama-3-8b-g128"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.419
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.416
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Llama-3.2-1B-Instruct-quantized.w8a8 -b "auto" -l 1000 -f 5 -t 1
|
||||
model_name: "neuralmagic/Llama-3.2-1B-Instruct-quantized.w8a8"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.356
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.358
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m mgoin/Minitron-4B-Base-FP8 -b auto -l 1000 -f 5 -t 1
|
||||
model_name: "mgoin/Minitron-4B-Base-FP8"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.233
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.236
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash ./run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Mixtral-8x22B-Instruct-v0.1-FP8-dynamic -b "auto" -l 250 -f 5 -t 8
|
||||
model_name: "neuralmagic/Mixtral-8x22B-Instruct-v0.1-FP8-dynamic"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.86
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.86
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash ./run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Mixtral-8x7B-Instruct-v0.1-FP8 -b "auto" -l 250 -f 5 -t 4
|
||||
model_name: "neuralmagic/Mixtral-8x7B-Instruct-v0.1-FP8"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.624
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.624
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-hf-baseline.sh -m neuralmagic/Mixtral-8x7B-Instruct-v0.1 -b 32 -l 250 -f 5 -t 4
|
||||
model_name: "mistralai/Mixtral-8x7B-Instruct-v0.1"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.616
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.632
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Qwen2-1.5B-Instruct-FP8W8 -b auto -l 1000 -f 5 -t 1
|
||||
model_name: "nm-testing/Qwen2-1.5B-Instruct-FP8W8"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.578
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.585
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Qwen2-1.5B-Instruct-quantized.w8a8 -b "auto" -l 1000 -f 5 -t 1
|
||||
model_name: "neuralmagic/Qwen2-1.5B-Instruct-quantized.w8a8"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.593
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.588
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash .buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh -m nm-testing/Qwen2-1.5B-Instruct-W8A16-Channelwise -b "auto" -l 1000 -f 5 -t 1
|
||||
model_name: "nm-testing/Qwen2-1.5B-Instruct-W8A16-Channelwise"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.595
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.582
|
||||
limit: 1000
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,11 @@
|
||||
# bash ./run-lm-eval-gsm-vllm-baseline.sh -m Qwen/Qwen2-57B-A14B-Instruct -b "auto" -l 250 -f 5 -t 4
|
||||
model_name: "Qwen/Qwen2-57B-A14B-Instruct"
|
||||
tasks:
|
||||
- name: "gsm8k"
|
||||
metrics:
|
||||
- name: "exact_match,strict-match"
|
||||
value: 0.792
|
||||
- name: "exact_match,flexible-extract"
|
||||
value: 0.824
|
||||
limit: 250
|
||||
num_fewshot: 5
|
||||
@@ -0,0 +1,5 @@
|
||||
Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform.yaml
|
||||
Meta-Llama-3-70B-Instruct.yaml
|
||||
Mixtral-8x7B-Instruct-v0.1.yaml
|
||||
Qwen2-57B-A14-Instruct.yaml
|
||||
DeepSeek-V2-Lite-Chat.yaml
|
||||
@@ -0,0 +1,10 @@
|
||||
Meta-Llama-3-8B-Instruct.yaml
|
||||
Meta-Llama-3-8B-Instruct-FP8-compressed-tensors.yaml
|
||||
Meta-Llama-3.2-1B-Instruct-INT8-compressed-tensors.yaml
|
||||
Meta-Llama-3-8B-Instruct-INT8-compressed-tensors-asym.yaml
|
||||
Meta-Llama-3-8B-Instruct-nonuniform-compressed-tensors.yaml
|
||||
Meta-Llama-3-8B-Instruct-Channelwise-compressed-tensors.yaml
|
||||
Minitron-4B-Base-FP8.yaml
|
||||
Qwen2-1.5B-Instruct-INT8-compressed-tensors.yaml
|
||||
Qwen2-1.5B-Instruct-FP8W8.yaml
|
||||
Meta-Llama-3-8B-QQQ.yaml
|
||||
@@ -0,0 +1,46 @@
|
||||
#!/bin/bash
|
||||
# We can use this script to compute baseline accuracy on GSM for transformers.
|
||||
#
|
||||
# Make sure you have lm-eval-harness installed:
|
||||
# pip install lm-eval==0.4.4
|
||||
|
||||
usage() {
|
||||
echo``
|
||||
echo "Runs lm eval harness on GSM8k using huggingface transformers."
|
||||
echo "This pathway is intended to be used to create baselines for "
|
||||
echo "our automated nm-test-accuracy workflow"
|
||||
echo
|
||||
echo "usage: ${0} <options>"
|
||||
echo
|
||||
echo " -m - huggingface stub or local directory of the model"
|
||||
echo " -b - batch size to run the evaluation at"
|
||||
echo " -l - limit number of samples to run"
|
||||
echo " -f - number of fewshot samples to use"
|
||||
echo
|
||||
}
|
||||
|
||||
while getopts "m:b:l:f:" OPT; do
|
||||
case ${OPT} in
|
||||
m )
|
||||
MODEL="$OPTARG"
|
||||
;;
|
||||
b )
|
||||
BATCH_SIZE="$OPTARG"
|
||||
;;
|
||||
l )
|
||||
LIMIT="$OPTARG"
|
||||
;;
|
||||
f )
|
||||
FEWSHOT="$OPTARG"
|
||||
;;
|
||||
\? )
|
||||
usage
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
lm_eval --model hf \
|
||||
--model_args "pretrained=$MODEL,parallelize=True" \
|
||||
--tasks gsm8k --num_fewshot "$FEWSHOT" --limit "$LIMIT" \
|
||||
--batch_size "$BATCH_SIZE"
|
||||
@@ -0,0 +1,51 @@
|
||||
#!/bin/bash
|
||||
# We can use this script to compute baseline accuracy on GSM for vllm.
|
||||
# We use this for fp8, which HF does not support.
|
||||
#
|
||||
# Make sure you have lm-eval-harness installed:
|
||||
# pip install lm-eval==0.4.4
|
||||
|
||||
usage() {
|
||||
echo``
|
||||
echo "Runs lm eval harness on GSM8k using huggingface transformers."
|
||||
echo "This pathway is intended to be used to create baselines for "
|
||||
echo "our automated nm-test-accuracy workflow"
|
||||
echo
|
||||
echo "usage: ${0} <options>"
|
||||
echo
|
||||
echo " -m - huggingface stub or local directory of the model"
|
||||
echo " -b - batch size to run the evaluation at"
|
||||
echo " -l - limit number of samples to run"
|
||||
echo " -f - number of fewshot samples to use"
|
||||
echo " -t - tensor parallel size to run at"
|
||||
echo
|
||||
}
|
||||
|
||||
while getopts "m:b:l:f:t:" OPT; do
|
||||
case ${OPT} in
|
||||
m )
|
||||
MODEL="$OPTARG"
|
||||
;;
|
||||
b )
|
||||
BATCH_SIZE="$OPTARG"
|
||||
;;
|
||||
l )
|
||||
LIMIT="$OPTARG"
|
||||
;;
|
||||
f )
|
||||
FEWSHOT="$OPTARG"
|
||||
;;
|
||||
t )
|
||||
TP_SIZE="$OPTARG"
|
||||
;;
|
||||
\? )
|
||||
usage
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
lm_eval --model vllm \
|
||||
--model_args "pretrained=$MODEL,tensor_parallel_size=$TP_SIZE,distributed_executor_backend=ray,trust_remote_code=true,max_model_len=4096" \
|
||||
--tasks gsm8k --num_fewshot "$FEWSHOT" --limit "$LIMIT" \
|
||||
--batch_size "$BATCH_SIZE"
|
||||
59
vllm-v0.6.2/.buildkite/lm-eval-harness/run-tests.sh
Normal file
59
vllm-v0.6.2/.buildkite/lm-eval-harness/run-tests.sh
Normal file
@@ -0,0 +1,59 @@
|
||||
#!/bin/bash
|
||||
|
||||
usage() {
|
||||
echo``
|
||||
echo "Runs lm eval harness on GSM8k using vllm and compares to "
|
||||
echo "precomputed baseline (measured by HF transformers.)"
|
||||
echo
|
||||
echo "usage: ${0} <options>"
|
||||
echo
|
||||
echo " -c - path to the test data config (e.g. configs/small-models.txt)"
|
||||
echo " -t - tensor parallel size"
|
||||
echo
|
||||
}
|
||||
|
||||
SUCCESS=0
|
||||
|
||||
while getopts "c:t:" OPT; do
|
||||
case ${OPT} in
|
||||
c )
|
||||
CONFIG="$OPTARG"
|
||||
;;
|
||||
t )
|
||||
TP_SIZE="$OPTARG"
|
||||
;;
|
||||
\? )
|
||||
usage
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
# Parse list of configs.
|
||||
IFS=$'\n' read -d '' -r -a MODEL_CONFIGS < "$CONFIG"
|
||||
|
||||
for MODEL_CONFIG in "${MODEL_CONFIGS[@]}"
|
||||
do
|
||||
LOCAL_SUCCESS=0
|
||||
|
||||
echo "=== RUNNING MODEL: $MODEL_CONFIG WITH TP SIZE: $TP_SIZE==="
|
||||
|
||||
export LM_EVAL_TEST_DATA_FILE=$PWD/configs/${MODEL_CONFIG}
|
||||
export LM_EVAL_TP_SIZE=$TP_SIZE
|
||||
pytest -s test_lm_eval_correctness.py || LOCAL_SUCCESS=$?
|
||||
|
||||
if [[ $LOCAL_SUCCESS == 0 ]]; then
|
||||
echo "=== PASSED MODEL: ${MODEL_CONFIG} ==="
|
||||
else
|
||||
echo "=== FAILED MODEL: ${MODEL_CONFIG} ==="
|
||||
fi
|
||||
|
||||
SUCCESS=$((SUCCESS + LOCAL_SUCCESS))
|
||||
|
||||
done
|
||||
|
||||
if [ "${SUCCESS}" -eq "0" ]; then
|
||||
exit 0
|
||||
else
|
||||
exit 1
|
||||
fi
|
||||
@@ -0,0 +1,63 @@
|
||||
"""
|
||||
LM eval harness on model to compare vs HF baseline computed offline.
|
||||
Configs are found in configs/$MODEL.yaml
|
||||
|
||||
* export LM_EVAL_TEST_DATA_FILE=configs/Meta-Llama-3-70B-Instruct.yaml
|
||||
* export LM_EVAL_TP_SIZE=4
|
||||
* pytest -s test_lm_eval_correctness.py
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
import lm_eval
|
||||
import numpy
|
||||
import yaml
|
||||
|
||||
RTOL = 0.05
|
||||
TEST_DATA_FILE = os.environ.get(
|
||||
"LM_EVAL_TEST_DATA_FILE",
|
||||
".buildkite/lm-eval-harness/configs/Meta-Llama-3-8B-Instruct.yaml")
|
||||
|
||||
TP_SIZE = os.environ.get("LM_EVAL_TP_SIZE", 1)
|
||||
|
||||
|
||||
def launch_lm_eval(eval_config):
|
||||
trust_remote_code = eval_config.get('trust_remote_code', False)
|
||||
|
||||
model_args = f"pretrained={eval_config['model_name']}," \
|
||||
f"tensor_parallel_size={TP_SIZE}," \
|
||||
f"add_bos_token=true," \
|
||||
f"trust_remote_code={trust_remote_code}"
|
||||
|
||||
results = lm_eval.simple_evaluate(
|
||||
model="vllm",
|
||||
model_args=model_args,
|
||||
tasks=[task["name"] for task in eval_config["tasks"]],
|
||||
num_fewshot=eval_config["num_fewshot"],
|
||||
limit=eval_config["limit"],
|
||||
batch_size="auto")
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def test_lm_eval_correctness():
|
||||
eval_config = yaml.safe_load(
|
||||
Path(TEST_DATA_FILE).read_text(encoding="utf-8"))
|
||||
|
||||
# Launch eval requests.
|
||||
results = launch_lm_eval(eval_config)
|
||||
|
||||
# Confirm scores match ground truth.
|
||||
success = True
|
||||
for task in eval_config["tasks"]:
|
||||
for metric in task["metrics"]:
|
||||
ground_truth = metric["value"]
|
||||
measured_value = results["results"][task["name"]][metric["name"]]
|
||||
print(f'{task["name"]} | {metric["name"]}: '
|
||||
f'ground_truth={ground_truth} | measured={measured_value}')
|
||||
success = success and numpy.isclose(
|
||||
ground_truth, measured_value, rtol=RTOL)
|
||||
|
||||
# Assert at the end, print all scores even on failure for debugging.
|
||||
assert success
|
||||
Reference in New Issue
Block a user