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Add testing for python custom metrics API
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#!/bin/bash | ||
# Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. | ||
# | ||
# Redistribution and use in source and binary forms, with or without | ||
# modification, are permitted provided that the following conditions | ||
# are met: | ||
# * Redistributions of source code must retain the above copyright | ||
# notice, this list of conditions and the following disclaimer. | ||
# * Redistributions in binary form must reproduce the above copyright | ||
# notice, this list of conditions and the following disclaimer in the | ||
# documentation and/or other materials provided with the distribution. | ||
# * Neither the name of NVIDIA CORPORATION nor the names of its | ||
# contributors may be used to endorse or promote products derived | ||
# from this software without specific prior written permission. | ||
# | ||
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY | ||
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR | ||
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR | ||
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, | ||
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, | ||
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR | ||
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY | ||
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
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CLIENT_PY=../python_unittest.py | ||
CLIENT_LOG="./client.log" | ||
EXPECTED_NUM_TESTS="1" | ||
TEST_RESULT_FILE='test_results.txt' | ||
source ../../common/util.sh | ||
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TRITON_DIR=${TRITON_DIR:="/opt/tritonserver"} | ||
SERVER=${TRITON_DIR}/bin/tritonserver | ||
BACKEND_DIR=${TRITON_DIR}/backends | ||
SERVER_ARGS="--model-repository=`pwd`/models --backend-directory=${BACKEND_DIR} --log-verbose=1" | ||
SERVER_LOG="./inference_server.log" | ||
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RET=0 | ||
rm -fr *.log ./models *.txt | ||
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mkdir -p models/custom_metrics/1/ | ||
cp ../../python_models/custom_metrics/model.py models/custom_metrics/1/ | ||
cp ../../python_models/custom_metrics/config.pbtxt models/custom_metrics | ||
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run_server | ||
if [ "$SERVER_PID" == "0" ]; then | ||
echo -e "\n***\n*** Failed to start $SERVER\n***" | ||
cat $SERVER_LOG | ||
exit 1 | ||
fi | ||
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set +e | ||
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export MODEL_NAME='custom_metrics' | ||
python3 $CLIENT_PY >> $CLIENT_LOG 2>&1 | ||
if [ $? -ne 0 ]; then | ||
echo -e "\n***\n*** 'Custom Metrics' test FAILED. \n***" | ||
cat $CLIENT_LOG | ||
RET=1 | ||
else | ||
check_test_results $TEST_RESULT_FILE $EXPECTED_NUM_TESTS | ||
if [ $? -ne 0 ]; then | ||
cat $CLIENT_LOG | ||
echo -e "\n***\n*** Test Result Verification Failed\n***" | ||
RET=1 | ||
fi | ||
fi | ||
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set -e | ||
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kill $SERVER_PID | ||
wait $SERVER_PID | ||
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if [ $RET -eq 1 ]; then | ||
cat $CLIENT_LOG | ||
cat $SERVER_LOG | ||
echo -e "\n***\n*** Custom Metrics test FAILED. \n***" | ||
else | ||
echo -e "\n***\n*** Custom Metrics test PASSED. \n***" | ||
fi | ||
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exit $RET |
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# Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. | ||
# | ||
# Redistribution and use in source and binary forms, with or without | ||
# modification, are permitted provided that the following conditions | ||
# are met: | ||
# * Redistributions of source code must retain the above copyright | ||
# notice, this list of conditions and the following disclaimer. | ||
# * Redistributions in binary form must reproduce the above copyright | ||
# notice, this list of conditions and the following disclaimer in the | ||
# documentation and/or other materials provided with the distribution. | ||
# * Neither the name of NVIDIA CORPORATION nor the names of its | ||
# contributors may be used to endorse or promote products derived | ||
# from this software without specific prior written permission. | ||
# | ||
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY | ||
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR | ||
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR | ||
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, | ||
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, | ||
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR | ||
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY | ||
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
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name: "custom_metrics" | ||
backend: "python" | ||
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output [ | ||
{ | ||
name: "OUTPUT0" | ||
data_type: TYPE_FP32 | ||
dims: [ 16 ] | ||
} | ||
] | ||
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instance_group [{ kind: KIND_CPU }] |
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# Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. | ||
# | ||
# Redistribution and use in source and binary forms, with or without | ||
# modification, are permitted provided that the following conditions | ||
# are met: | ||
# * Redistributions of source code must retain the above copyright | ||
# notice, this list of conditions and the following disclaimer. | ||
# * Redistributions in binary form must reproduce the above copyright | ||
# notice, this list of conditions and the following disclaimer in the | ||
# documentation and/or other materials provided with the distribution. | ||
# * Neither the name of NVIDIA CORPORATION nor the names of its | ||
# contributors may be used to endorse or promote products derived | ||
# from this software without specific prior written permission. | ||
# | ||
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY | ||
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR | ||
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR | ||
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, | ||
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, | ||
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR | ||
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY | ||
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
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import numpy as np | ||
import unittest | ||
import triton_python_backend_utils as pb_utils | ||
import requests | ||
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class PBBLSMemoryTest(unittest.TestCase): | ||
def _get_metrics(self): | ||
metrics_url = "http://localhost:8002/metrics" | ||
r = requests.get(metrics_url) | ||
r.raise_for_status() | ||
return r.text | ||
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def _metric_api_helper(self, metric, kind): | ||
# The value should be 0.0 before the test | ||
self.assertEqual(metric.value(), 0.0) | ||
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# Test increment positive value | ||
increment = 2023.0 | ||
metric.increment(increment) | ||
self.assertEqual(metric.value(), increment) | ||
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# Test increment negative value | ||
decrement = -23.5 | ||
if kind == 'counter': | ||
# Counter should not accept negative values | ||
with self.assertRaises(pb_utils.TritonModelException): | ||
metric.increment(decrement) | ||
else: | ||
metric.increment(decrement) | ||
self.assertEqual(metric.value(), increment + decrement) | ||
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# Test set value | ||
value = 999.9 | ||
if kind == 'counter': | ||
# Counter does not support set | ||
with self.assertRaises(pb_utils.TritonModelException): | ||
metric.set(value) | ||
else: | ||
metric.set(value) | ||
self.assertEqual(metric.value(), value) | ||
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def _dup_metric_helper(self, labels={}): | ||
description = "dup metric" | ||
metric_family = pb_utils.MetricFamily(name="test_dup_metric", | ||
description=description, | ||
kind=pb_utils.COUNTER) | ||
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# Verify dupe metrics reference same underlying metric | ||
metric1 = metric_family.Metric(labels=labels) | ||
metric2 = metric_family.Metric(labels=labels) | ||
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# The value should be 0 before the test | ||
self.assertEqual(metric1.value(), 0.0) | ||
self.assertEqual(metric2.value(), 0.0) | ||
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# Increment metric 1, check metric 2 == metric 1 | ||
increment = 7.5 | ||
metric1.increment(increment) | ||
self.assertEqual(metric1.value(), metric2.value()) | ||
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# Assert custom metric/family remains when there's still a reference to it | ||
del metric1 | ||
metrics = self._get_metrics() | ||
self.assertIn(description, metrics) | ||
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def test_counter_e2e(self): | ||
metric_family = pb_utils.MetricFamily( | ||
name="test_counter_e2e", | ||
description="test metric counter kind end to end", | ||
kind=pb_utils.COUNTER) | ||
labels = {"example1": "counter_label1", "example2": "counter_label2"} | ||
metric = metric_family.Metric(labels=labels) | ||
self._metric_api_helper(metric, 'counter') | ||
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pattern = 'test_counter_e2e{example1="counter_label1",example2="counter_label2"}' | ||
metrics = self._get_metrics() | ||
self.assertIn(pattern, metrics) | ||
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def test_gauge_e2e(self): | ||
metric_family = pb_utils.MetricFamily( | ||
name="test_gauge_e2e", | ||
description="test metric gauge kind end to end", | ||
kind=pb_utils.GAUGE) | ||
labels = {"example1": "counter_label1", "example2": "counter_label2"} | ||
metric = metric_family.Metric(labels=labels) | ||
self._metric_api_helper(metric, 'gauge') | ||
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pattern = 'test_gauge_e2e{example1="counter_label1",example2="counter_label2"}' | ||
metrics = self._get_metrics() | ||
self.assertIn(pattern, metrics) | ||
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def test_dup_metric_family_diff_kind(self): | ||
# Test that a duplicate metric family can't be added with a conflicting type/kind | ||
metric_family1 = pb_utils.MetricFamily( | ||
name="test_dup_metric_family_diff_kind", | ||
description="test metric family with same name but different kind", | ||
kind=pb_utils.COUNTER) | ||
with self.assertRaises(pb_utils.TritonModelException): | ||
metric_family2 = pb_utils.MetricFamily( | ||
name="test_dup_metric_family_diff_kind", | ||
description= | ||
"test metric family with same name but different kind", | ||
kind=pb_utils.GAUGE) | ||
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def test_dup_metric_family_diff_description(self): | ||
# Test that a duplicate metric family name will still return the | ||
# original metric family even if the description is changed | ||
metric_family1 = pb_utils.MetricFamily( | ||
name="test_dup_metric_family_diff_description", | ||
description="first description", | ||
kind=pb_utils.COUNTER) | ||
metric_family2 = pb_utils.MetricFamily( | ||
name="test_dup_metric_family_diff_description", | ||
description="second description", | ||
kind=pb_utils.COUNTER) | ||
metric2 = metric_family2.Metric() | ||
# Delete metric_family1 and check if metric_family2 still references it | ||
del metric_family1 | ||
pattern = 'test_dup_metric_family_diff_description first description' | ||
metrics = self._get_metrics() | ||
self.assertIn(pattern, metrics) | ||
# The first description will be kept if adding a duplicate metric | ||
# family name with a different description | ||
pattern = 'test_dup_metric_family_diff_description second description' | ||
self.assertNotIn(pattern, metrics) | ||
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def test_dup_metric_family(self): | ||
# Test that adding a duplicate metric family will reuse the original | ||
# and not add another entry to registry | ||
metric_family1 = pb_utils.MetricFamily(name="test_dup_metric_family", | ||
description="dup description", | ||
kind=pb_utils.COUNTER) | ||
metric_family2 = pb_utils.MetricFamily(name="test_dup_metric_family", | ||
description="dup description", | ||
kind=pb_utils.COUNTER) | ||
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metric_key = "custom_metric_key" | ||
metric1 = metric_family1.Metric(labels={metric_key: "label1"}) | ||
metric2 = metric_family2.Metric(labels={metric_key: "label2"}) | ||
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patterns = [ | ||
'# HELP test_dup_metric_family dup description', | ||
'# TYPE test_dup_metric_family counter', | ||
'test_dup_metric_family{custom_metric_key="label2"} 0', | ||
'test_dup_metric_family{custom_metric_key="label1"} 0' | ||
] | ||
metrics = self._get_metrics() | ||
for pattern in patterns: | ||
self.assertIn(pattern, metrics) | ||
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del metric_family1 | ||
del metric_family2 | ||
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def test_dup_metric_labels(self): | ||
# Test that adding a duplicate metric will refer to the same | ||
# underlying metric, and all instances will be updated | ||
labels = {"example1": "label1", "example2": "label2"} | ||
self._dup_metric_helper(labels) | ||
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def test_dup_metric_empty_labels(self): | ||
# Test that adding a duplicate metric will refer to the same | ||
# underlying metric, and all instances will be updated | ||
self._dup_metric_helper() | ||
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class TritonPythonModel: | ||
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def execute(self, requests): | ||
responses = [] | ||
for _ in requests: | ||
# Run the unittest and store the results in InferenceResponse. | ||
test = unittest.main('model', exit=False) | ||
responses.append( | ||
pb_utils.InferenceResponse([ | ||
pb_utils.Tensor( | ||
'OUTPUT0', | ||
np.array([test.result.wasSuccessful()], | ||
dtype=np.float16)) | ||
])) | ||
return responses |