Add sanity tests for inference engine:
- test inference engine c/cpp shared library
- test inference engine python api
- test inference engine cpu, gpu, myriad plugin
Add sanity tests for model optimizer
- test model optmizer can generate ir
Licenses:
- classification_sample.py
license: Apache 2.0
source: <install_root>/deployment_tools/inference_engine/samples/*
Signed-off-by: Yeoh Ee Peng <[email protected]>
---
lib/oeqa/runtime/cases/dldt_inference_engine.py | 101 +++++++++++++++
lib/oeqa/runtime/cases/dldt_model_optimizer.py | 38 ++++++
.../dldt-inference-engine/classification_sample.py | 135 +++++++++++++++++++++
lib/oeqa/runtime/miutils/dldtutils.py | 3 +
lib/oeqa/runtime/miutils/targets/oeqatarget.py | 11 ++
.../miutils/tests/dldt_inference_engine_test.py | 48 ++++++++
.../miutils/tests/dldt_model_optimizer_test.py | 23 ++++
.../tests/squeezenet_model_download_test.py | 25 ++++
8 files changed, 384 insertions(+)
create mode 100644 lib/oeqa/runtime/cases/dldt_inference_engine.py
create mode 100644 lib/oeqa/runtime/cases/dldt_model_optimizer.py
create mode 100644
lib/oeqa/runtime/files/dldt-inference-engine/classification_sample.py
create mode 100644 lib/oeqa/runtime/miutils/dldtutils.py
create mode 100644 lib/oeqa/runtime/miutils/targets/oeqatarget.py
create mode 100644 lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py
create mode 100644 lib/oeqa/runtime/miutils/tests/dldt_model_optimizer_test.py
create mode 100644
lib/oeqa/runtime/miutils/tests/squeezenet_model_download_test.py
diff --git a/lib/oeqa/runtime/cases/dldt_inference_engine.py
b/lib/oeqa/runtime/cases/dldt_inference_engine.py
new file mode 100644
index 0000000..7680ed2
--- /dev/null
+++ b/lib/oeqa/runtime/cases/dldt_inference_engine.py
@@ -0,0 +1,101 @@
+from oeqa.runtime.case import OERuntimeTestCase
+from oeqa.runtime.decorator.package import OEHasPackage
+from oeqa.core.decorator.depends import OETestDepends
+from oeqa.runtime.miutils.targets.oeqatarget import OEQATarget
+from oeqa.runtime.miutils.tests.squeezenet_model_download_test import
SqueezenetModelDownloadTest
+from oeqa.runtime.miutils.tests.dldt_model_optimizer_test import
DldtModelOptimizerTest
+from oeqa.runtime.miutils.tests.dldt_inference_engine_test import
DldtInferenceEngineTest
+from oeqa.runtime.miutils.dldtutils import get_testdata_config
+
+class DldtInferenceEngine(OERuntimeTestCase):
+
+ @classmethod
+ def setUpClass(cls):
+ cls.sqn_download =
SqueezenetModelDownloadTest(OEQATarget(cls.tc.target), '/tmp/ie/md')
+ cls.sqn_download.setup()
+ cls.dldt_mo = DldtModelOptimizerTest(OEQATarget(cls.tc.target),
'/tmp/ie/ir')
+ cls.dldt_mo.setup()
+ cls.dldt_ie = DldtInferenceEngineTest(OEQATarget(cls.tc.target),
'/tmp/ie/inputs')
+ cls.dldt_ie.setup()
+ cls.ir_files_dir = cls.dldt_mo.work_dir
+
+ @classmethod
+ def tearDownClass(cls):
+ cls.dldt_ie.tear_down()
+ cls.dldt_mo.tear_down()
+ cls.sqn_download.tear_down()
+
+ @OEHasPackage(['dldt-model-optimizer'])
+ @OEHasPackage(['wget'])
+ def test_dldt_ie_can_create_ir_and_download_input(self):
+ proxy_port = get_testdata_config(self.tc.td, 'DLDT_PIP_PROXY')
+ if not proxy_port:
+ self.skipTest('Need to configure bitbake configuration
(DLDT_PIP_PROXY="proxy.server:port").')
+ (status, output) =
self.sqn_download.test_can_download_squeezenet_model(proxy_port)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+ (status, output) =
self.sqn_download.test_can_download_squeezenet_prototxt(proxy_port)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+ mo_exe_dir = get_testdata_config(self.tc.td, 'DLDT_MO_EXE_DIR')
+ if not mo_exe_dir:
+ self.skipTest('Need to configure bitbake configuration
(DLDT_MO_EXE_DIR="directory_to_mo.py").')
+ mo_files_dir = self.sqn_download.work_dir
+ (status, output) = self.dldt_mo.test_dldt_mo_can_create_ir(mo_exe_dir,
mo_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+ (status, output) =
self.dldt_ie.test_can_download_input_file(proxy_port)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+
@OETestDepends(['dldt_inference_engine.DldtInferenceEngine.test_dldt_ie_can_create_ir_and_download_input'])
+ @OEHasPackage(['dldt-inference-engine'])
+ @OEHasPackage(['dldt-inference-engine-samples'])
+ def test_dldt_ie_classification_with_cpu(self):
+ (status, output) =
self.dldt_ie.test_dldt_ie_classification_with_device('CPU', self.ir_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+
@OETestDepends(['dldt_inference_engine.DldtInferenceEngine.test_dldt_ie_can_create_ir_and_download_input'])
+ @OEHasPackage(['dldt-inference-engine'])
+ @OEHasPackage(['dldt-inference-engine-samples'])
+ @OEHasPackage(['intel-compute-runtime'])
+ @OEHasPackage(['opencl-icd-loader'])
+ def test_dldt_ie_classification_with_gpu(self):
+ (status, output) =
self.dldt_ie.test_dldt_ie_classification_with_device('GPU', self.ir_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+
@OETestDepends(['dldt_inference_engine.DldtInferenceEngine.test_dldt_ie_can_create_ir_and_download_input'])
+ @OEHasPackage(['dldt-inference-engine'])
+ @OEHasPackage(['dldt-inference-engine-samples'])
+ @OEHasPackage(['dldt-inference-engine-vpu-firmware'])
+ def test_dldt_ie_classification_with_myriad(self):
+ (status, output) =
self.dldt_ie.test_dldt_ie_classification_with_device('MYRIAD',
self.ir_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+
@OETestDepends(['dldt_inference_engine.DldtInferenceEngine.test_dldt_ie_can_create_ir_and_download_input'])
+ @OEHasPackage(['dldt-inference-engine'])
+ @OEHasPackage(['dldt-inference-engine-python3'])
+ @OEHasPackage(['python3-opencv'])
+ @OEHasPackage(['python3-numpy'])
+ def test_dldt_ie_classification_python_api_with_cpu(self):
+ (status, output) =
self.dldt_ie.test_dldt_ie_classification_python_api_with_device('CPU',
self.ir_files_dir, 'libcpu_extension.so')
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+
@OETestDepends(['dldt_inference_engine.DldtInferenceEngine.test_dldt_ie_can_create_ir_and_download_input'])
+ @OEHasPackage(['dldt-inference-engine'])
+ @OEHasPackage(['dldt-inference-engine-python3'])
+ @OEHasPackage(['intel-compute-runtime'])
+ @OEHasPackage(['opencl-icd-loader'])
+ @OEHasPackage(['python3-opencv'])
+ @OEHasPackage(['python3-numpy'])
+ def test_dldt_ie_classification_python_api_with_gpu(self):
+ (status, output) =
self.dldt_ie.test_dldt_ie_classification_python_api_with_device('GPU',
self.ir_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+
@OETestDepends(['dldt_inference_engine.DldtInferenceEngine.test_dldt_ie_can_create_ir_and_download_input'])
+ @OEHasPackage(['dldt-inference-engine'])
+ @OEHasPackage(['dldt-inference-engine-python3'])
+ @OEHasPackage(['dldt-inference-engine-vpu-firmware'])
+ @OEHasPackage(['python3-opencv'])
+ @OEHasPackage(['python3-numpy'])
+ def test_dldt_ie_classification_python_api_with_myriad(self):
+ (status, output) =
self.dldt_ie.test_dldt_ie_classification_python_api_with_device('MYRIAD',
self.ir_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
diff --git a/lib/oeqa/runtime/cases/dldt_model_optimizer.py
b/lib/oeqa/runtime/cases/dldt_model_optimizer.py
new file mode 100644
index 0000000..286c462
--- /dev/null
+++ b/lib/oeqa/runtime/cases/dldt_model_optimizer.py
@@ -0,0 +1,38 @@
+from oeqa.runtime.case import OERuntimeTestCase
+from oeqa.runtime.decorator.package import OEHasPackage
+from oeqa.runtime.miutils.targets.oeqatarget import OEQATarget
+from oeqa.runtime.miutils.tests.squeezenet_model_download_test import
SqueezenetModelDownloadTest
+from oeqa.runtime.miutils.tests.dldt_model_optimizer_test import
DldtModelOptimizerTest
+from oeqa.runtime.miutils.dldtutils import get_testdata_config
+
+class DldtModelOptimizer(OERuntimeTestCase):
+
+ @classmethod
+ def setUpClass(cls):
+ cls.sqn_download =
SqueezenetModelDownloadTest(OEQATarget(cls.tc.target), '/tmp/mo/md')
+ cls.sqn_download.setup()
+ cls.dldt_mo = DldtModelOptimizerTest(OEQATarget(cls.tc.target),
'/tmp/mo/ir')
+ cls.dldt_mo.setup()
+
+ @classmethod
+ def tearDownClass(cls):
+ cls.dldt_mo.tear_down()
+ cls.sqn_download.tear_down()
+
+ @OEHasPackage(['dldt-model-optimizer'])
+ @OEHasPackage(['wget'])
+ def test_dldt_mo_can_create_ir(self):
+ proxy_port = get_testdata_config(self.tc.td, 'DLDT_PIP_PROXY')
+ if not proxy_port:
+ self.skipTest('Need to configure bitbake configuration
(DLDT_PIP_PROXY="proxy.server:port").')
+ (status, output) =
self.sqn_download.test_can_download_squeezenet_model(proxy_port)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+ (status, output) =
self.sqn_download.test_can_download_squeezenet_prototxt(proxy_port)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
+
+ mo_exe_dir = get_testdata_config(self.tc.td, 'DLDT_MO_EXE_DIR')
+ if not mo_exe_dir:
+ self.skipTest('Need to configure bitbake configuration
(DLDT_MO_EXE_DIR="directory_to_mo.py").')
+ mo_files_dir = self.sqn_download.work_dir
+ (status, output) = self.dldt_mo.test_dldt_mo_can_create_ir(mo_exe_dir,
mo_files_dir)
+ self.assertEqual(status, 0, msg='status and output: %s and %s' %
(status, output))
diff --git
a/lib/oeqa/runtime/files/dldt-inference-engine/classification_sample.py
b/lib/oeqa/runtime/files/dldt-inference-engine/classification_sample.py
new file mode 100644
index 0000000..9336e39
--- /dev/null
+++ b/lib/oeqa/runtime/files/dldt-inference-engine/classification_sample.py
@@ -0,0 +1,135 @@
+#!/usr/bin/env python
+"""
+ Copyright (C) 2018-2019 Intel Corporation
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+"""
+from __future__ import print_function
+import sys
+import os
+from argparse import ArgumentParser, SUPPRESS
+import cv2
+import numpy as np
+import logging as log
+from time import time
+from openvino.inference_engine import IENetwork, IECore
+
+
+def build_argparser():
+ parser = ArgumentParser(add_help=False)
+ args = parser.add_argument_group('Options')
+ args.add_argument('-h', '--help', action='help', default=SUPPRESS,
help='Show this help message and exit.')
+ args.add_argument("-m", "--model", help="Required. Path to an .xml file
with a trained model.", required=True,
+ type=str)
+ args.add_argument("-i", "--input", help="Required. Path to a folder with
images or path to an image files",
+ required=True,
+ type=str, nargs="+")
+ args.add_argument("-l", "--cpu_extension",
+ help="Optional. Required for CPU custom layers. "
+ "MKLDNN (CPU)-targeted custom layers. Absolute path
to a shared library with the"
+ " kernels implementations.", type=str, default=None)
+ args.add_argument("-d", "--device",
+ help="Optional. Specify the target device to infer on;
CPU, GPU, FPGA, HDDL, MYRIAD or HETERO: is "
+ "acceptable. The sample will look for a suitable
plugin for device specified. Default "
+ "value is CPU",
+ default="CPU", type=str)
+ args.add_argument("--labels", help="Optional. Path to a labels mapping
file", default=None, type=str)
+ args.add_argument("-nt", "--number_top", help="Optional. Number of top
results", default=10, type=int)
+
+ return parser
+
+
+def main():
+ log.basicConfig(format="[ %(levelname)s ] %(message)s", level=log.INFO,
stream=sys.stdout)
+ args = build_argparser().parse_args()
+ model_xml = args.model
+ model_bin = os.path.splitext(model_xml)[0] + ".bin"
+
+ # Plugin initialization for specified device and load extensions library
if specified
+ log.info("Creating Inference Engine")
+ ie = IECore()
+ if args.cpu_extension and 'CPU' in args.device:
+ ie.add_extension(args.cpu_extension, "CPU")
+ # Read IR
+ log.info("Loading network files:\n\t{}\n\t{}".format(model_xml, model_bin))
+ net = IENetwork(model=model_xml, weights=model_bin)
+
+ if "CPU" in args.device:
+ supported_layers = ie.query_network(net, "CPU")
+ not_supported_layers = [l for l in net.layers.keys() if l not in
supported_layers]
+ if len(not_supported_layers) != 0:
+ log.error("Following layers are not supported by the plugin for
specified device {}:\n {}".
+ format(args.device, ', '.join(not_supported_layers)))
+ log.error("Please try to specify cpu extensions library path in
sample's command line parameters using -l "
+ "or --cpu_extension command line argument")
+ sys.exit(1)
+
+ assert len(net.inputs.keys()) == 1, "Sample supports only single input
topologies"
+ assert len(net.outputs) == 1, "Sample supports only single output
topologies"
+
+ log.info("Preparing input blobs")
+ input_blob = next(iter(net.inputs))
+ out_blob = next(iter(net.outputs))
+ net.batch_size = len(args.input)
+
+ # Read and pre-process input images
+ n, c, h, w = net.inputs[input_blob].shape
+ images = np.ndarray(shape=(n, c, h, w))
+ for i in range(n):
+ image = cv2.imread(args.input[i])
+ if image.shape[:-1] != (h, w):
+ log.warning("Image {} is resized from {} to
{}".format(args.input[i], image.shape[:-1], (h, w)))
+ image = cv2.resize(image, (w, h))
+ image = image.transpose((2, 0, 1)) # Change data layout from HWC to
CHW
+ images[i] = image
+ log.info("Batch size is {}".format(n))
+
+ # Loading model to the plugin
+ log.info("Loading model to the plugin")
+ exec_net = ie.load_network(network=net, device_name=args.device)
+
+ # Start sync inference
+ log.info("Starting inference in synchronous mode")
+ res = exec_net.infer(inputs={input_blob: images})
+
+ # Processing output blob
+ log.info("Processing output blob")
+ res = res[out_blob]
+ log.info("Top {} results: ".format(args.number_top))
+ if args.labels:
+ with open(args.labels, 'r') as f:
+ labels_map = [x.split(sep=' ', maxsplit=1)[-1].strip() for x in f]
+ else:
+ labels_map = None
+ classid_str = "classid"
+ probability_str = "probability"
+ for i, probs in enumerate(res):
+ probs = np.squeeze(probs)
+ top_ind = np.argsort(probs)[-args.number_top:][::-1]
+ print("Image {}\n".format(args.input[i]))
+ print(classid_str, probability_str)
+ print("{} {}".format('-' * len(classid_str), '-' *
len(probability_str)))
+ for id in top_ind:
+ det_label = labels_map[id] if labels_map else "{}".format(id)
+ label_length = len(det_label)
+ space_num_before = (len(classid_str) - label_length) // 2
+ space_num_after = len(classid_str) - (space_num_before +
label_length) + 2
+ space_num_before_prob = (len(probability_str) -
len(str(probs[id]))) // 2
+ print("{}{}{}{}{:.7f}".format(' ' * space_num_before, det_label,
+ ' ' * space_num_after, ' ' *
space_num_before_prob,
+ probs[id]))
+ print("\n")
+ log.info("This sample is an API example, for any performance measurements
please use the dedicated benchmark_app tool\n")
+
+if __name__ == '__main__':
+ sys.exit(main() or 0)
diff --git a/lib/oeqa/runtime/miutils/dldtutils.py
b/lib/oeqa/runtime/miutils/dldtutils.py
new file mode 100644
index 0000000..f2fceb9
--- /dev/null
+++ b/lib/oeqa/runtime/miutils/dldtutils.py
@@ -0,0 +1,3 @@
+
+def get_testdata_config(testdata, config):
+ return testdata.get(config)
diff --git a/lib/oeqa/runtime/miutils/targets/oeqatarget.py
b/lib/oeqa/runtime/miutils/targets/oeqatarget.py
new file mode 100644
index 0000000..6d0c802
--- /dev/null
+++ b/lib/oeqa/runtime/miutils/targets/oeqatarget.py
@@ -0,0 +1,11 @@
+
+class OEQATarget(object):
+
+ def __init__(self, target):
+ self.target = target
+
+ def run(self, cmd):
+ return self.target.run(cmd)
+
+ def copy_to(self, source, destination_dir):
+ self.target.copyTo(source, destination_dir)
diff --git a/lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py
b/lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py
new file mode 100644
index 0000000..3aff096
--- /dev/null
+++ b/lib/oeqa/runtime/miutils/tests/dldt_inference_engine_test.py
@@ -0,0 +1,48 @@
+import os
+script_path = os.path.dirname(os.path.realpath(__file__))
+files_path = os.path.join(script_path, '../../files/')
+
+class DldtInferenceEngineTest(object):
+ ie_input_files = {'ie_python_sample': 'classification_sample.py',
+ 'input': 'chicky_512.png',
+ 'input_download':
'https://raw.githubusercontent.com/opencv/opencv/master/samples/data/chicky_512.png',
+ 'model': 'squeezenet_v1.1.xml'}
+
+ def __init__(self, target, work_dir):
+ self.target = target
+ self.work_dir = work_dir
+
+ def setup(self):
+ self.target.run('mkdir -p %s' % self.work_dir)
+ self.target.copy_to(os.path.join(files_path, 'dldt-inference-engine',
self.ie_input_files['ie_python_sample']),
+ self.work_dir)
+
+ def tear_down(self):
+ self.target.run('rm -rf %s' % self.work_dir)
+
+ def test_can_download_input_file(self, proxy_port):
+ return self.target.run('cd %s; wget %s -e https_proxy=%s' %
+ (self.work_dir,
+ self.ie_input_files['input_download'],
+ proxy_port))
+
+ def test_dldt_ie_classification_with_device(self, device, ir_files_dir):
+ return self.target.run('classification_sample_async -d %s -i %s -m %s'
%
+ (device,
+ os.path.join(self.work_dir,
self.ie_input_files['input']),
+ os.path.join(ir_files_dir,
self.ie_input_files['model'])))
+
+ def test_dldt_ie_classification_python_api_with_device(self, device,
ir_files_dir, extension=''):
+ if extension:
+ return self.target.run('python3 %s -d %s -i %s -m %s -l %s' %
+ (os.path.join(self.work_dir,
self.ie_input_files['ie_python_sample']),
+ device,
+ os.path.join(self.work_dir,
self.ie_input_files['input']),
+ os.path.join(ir_files_dir,
self.ie_input_files['model']),
+ extension))
+ else:
+ return self.target.run('python3 %s -d %s -i %s -m %s' %
+ (os.path.join(self.work_dir,
self.ie_input_files['ie_python_sample']),
+ device,
+ os.path.join(self.work_dir,
self.ie_input_files['input']),
+ os.path.join(ir_files_dir,
self.ie_input_files['model'])))
diff --git a/lib/oeqa/runtime/miutils/tests/dldt_model_optimizer_test.py
b/lib/oeqa/runtime/miutils/tests/dldt_model_optimizer_test.py
new file mode 100644
index 0000000..a37a45d
--- /dev/null
+++ b/lib/oeqa/runtime/miutils/tests/dldt_model_optimizer_test.py
@@ -0,0 +1,23 @@
+import os
+
+class DldtModelOptimizerTest(object):
+ mo_input_files = {'model': 'squeezenet_v1.1.caffemodel',
+ 'prototxt': 'deploy.prototxt'}
+ mo_exe = 'mo.py'
+
+ def __init__(self, target, work_dir):
+ self.target = target
+ self.work_dir = work_dir
+
+ def setup(self):
+ self.target.run('mkdir -p %s' % self.work_dir)
+
+ def tear_down(self):
+ self.target.run('rm -rf %s' % self.work_dir)
+
+ def test_dldt_mo_can_create_ir(self, mo_exe_dir, mo_files_dir):
+ return self.target.run('python3 %s --input_model %s --input_proto %s
--output_dir %s --data_type FP16' %
+ (os.path.join(mo_exe_dir, self.mo_exe),
+ os.path.join(mo_files_dir,
self.mo_input_files['model']),
+ os.path.join(mo_files_dir,
self.mo_input_files['prototxt']),
+ self.work_dir))
diff --git a/lib/oeqa/runtime/miutils/tests/squeezenet_model_download_test.py
b/lib/oeqa/runtime/miutils/tests/squeezenet_model_download_test.py
new file mode 100644
index 0000000..2486a58
--- /dev/null
+++ b/lib/oeqa/runtime/miutils/tests/squeezenet_model_download_test.py
@@ -0,0 +1,25 @@
+class SqueezenetModelDownloadTest(object):
+ download_files = {'squeezenet1.1.prototxt':
'https://raw.githubusercontent.com/DeepScale/SqueezeNet/a47b6f13d30985279789d08053d37013d67d131b/SqueezeNet_v1.1/deploy.prototxt',
+ 'squeezenet1.1.caffemodel':
'https://github.com/DeepScale/SqueezeNet/raw/a47b6f13d30985279789d08053d37013d67d131b/SqueezeNet_v1.1/squeezenet_v1.1.caffemodel'}
+
+ def __init__(self, target, work_dir):
+ self.target = target
+ self.work_dir = work_dir
+
+ def setup(self):
+ self.target.run('mkdir -p %s' % self.work_dir)
+
+ def tear_down(self):
+ self.target.run('rm -rf %s' % self.work_dir)
+
+ def test_can_download_squeezenet_model(self, proxy_port):
+ return self.target.run('cd %s; wget %s -e https_proxy=%s' %
+ (self.work_dir,
+
self.download_files['squeezenet1.1.caffemodel'],
+ proxy_port))
+
+ def test_can_download_squeezenet_prototxt(self, proxy_port):
+ return self.target.run('cd %s; wget %s -e https_proxy=%s' %
+ (self.work_dir,
+ self.download_files['squeezenet1.1.prototxt'],
+ proxy_port))
--
2.7.4
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