def run_ngtf_pytests(venv_dir, build_dir):
root_pwd = os.getcwd()
build_dir = os.path.abspath(build_dir)
venv_dir = os.path.abspath(venv_dir)
test_dir = os.path.join(build_dir, "test")
test_dir = os.path.join(test_dir, "python")
if not os.path.isdir(test_dir):
raise Exception("test directory doesn't exist: " + test_dir)
# Change the directory to the test_dir
os.chdir(test_dir)
# Load venv
load_venv(venv_dir)
# Next run the ngraph-tensorflow python tests
command_executor(["pip", "install", "-U", "pytest"])
command_executor(["pip", "install", "-U", "psutil"])
command_executor([
"python", "-m", "pytest",
('--junitxml=%s/xunit_pytest.xml' % build_dir)
])
os.chdir(root_pwd)
def main():
'''
Tests nGraph-TensorFlow Python 3. This script needs to be run after
running build_ngtf.py which builds the ngraph-tensorflow-bridge
and installs it to a virtual environment that would be used by this script.
'''
parser = argparse.ArgumentParser()
parser.add_argument('--test_examples',
help="Builds and tests the examples.\n",
action="store_true")
arguments = parser.parse_args()
#-------------------------------
# Recipe
#-------------------------------
root_pwd = os.getcwd()
# Constants
build_dir = 'build'
venv_dir = 'build/venv-tf-py3'
# Run the bazel based buil
run_bazel_build_test(venv_dir, build_dir)
# First run the C++ gtests
run_ngtf_gtests(build_dir)
# Next run Python unit tests
load_venv(venv_dir)
run_ngtf_pytests(venv_dir, build_dir)
if (arguments.test_examples):
# Run the C++ example build/run test
run_cpp_example_test('build')
# Next run the TensorFlow python tests
run_tensorflow_pytests(venv_dir, build_dir, './', 'build/tensorflow')
# Finally run Resnet50 based training and inferences
run_resnet50(build_dir)
os.chdir(root_pwd)
def run_tensorflow_pytests(venv_dir, build_dir, ngraph_tf_src_dir, tf_src_dir):
root_pwd = os.getcwd()
build_dir = os.path.abspath(build_dir)
venv_dir = os.path.abspath(venv_dir)
ngraph_tf_src_dir = os.path.abspath(ngraph_tf_src_dir)
patch_file = os.path.abspath(
os.path.join(ngraph_tf_src_dir,
"test/python/tensorflow/tf_unittest_ngraph.patch"))
# Load the virtual env
venv_dir_absolute = load_venv(venv_dir)
# Next patch the TensorFlow so that the tests run using ngraph_bridge
pwd = os.getcwd()
# Go to the site-packages
os.chdir(glob.glob(venv_dir_absolute + "/lib/py*/site-packages")[0])
print("CURRENT DIR: " + os.getcwd())
print("Patching TensorFlow using: %s" % patch_file)
result = call(["patch", "-p1", "-N", "-i", patch_file])
print("Patch result: %d" % result)
os.chdir(pwd)
# Now run the TensorFlow python tests
test_src_dir = os.path.join(ngraph_tf_src_dir, "test/python/tensorflow")
test_script = os.path.join(test_src_dir, "tf_unittest_runner.py")
test_manifest_file = os.path.join(test_src_dir, "python_tests_list.txt")
test_xml_report = '%s/junit_tensorflow_tests.xml' % build_dir
import psutil
num_cores = int(psutil.cpu_count(logical=False))
print("OMP_NUM_THREADS: %s " % str(num_cores))
os.environ['OMP_NUM_THREADS'] = str(num_cores)
os.environ['NGRAPH_TF_DISABLE_DEASSIGN_CLUSTERS'] = '1'
command_executor([
"python", test_script, "--tensorflow_path", tf_src_dir,
"--run_tests_from_file", test_manifest_file,
"--xml_report", test_xml_report
])
os.chdir(root_pwd)
def run_bazel_build_test(venv_dir, build_dir):
# Load the virtual env
venv_dir_absolute = load_venv(venv_dir)
# Next patch the TensorFlow so that the tests run using ngraph_bridge
root_pwd = os.getcwd()
# Now run the configure
command_executor(['bash', 'configure_bazel.sh'])
# Build the bridge
command_executor(['bazel', 'build', 'libngraph_bridge.so'])
# Build the backend
command_executor(['bazel', 'build', '@ngraph//:libinterpreter_backend.so'])
# Return to the original directory
os.chdir(root_pwd)
def main():
'''
Tests nGraph-TensorFlow Python 3. This script needs to be run after
running build_ngtf.py which builds the ngraph-tensorflow-bridge
and installs it to a virtual environment that would be used by this script.
'''
parser = argparse.ArgumentParser()
parser.add_argument('--test_examples',
help="Builds and tests the examples.\n",
action="store_true")
parser.add_argument('--gpu_unit_tests_enable',
help="Builds and tests the examples.\n",
action="store_true")
arguments = parser.parse_args()
#-------------------------------
# Recipe
#-------------------------------
root_pwd = os.getcwd()
# Constants
build_dir = 'build'
venv_dir = 'build/venv-tf-py3'
if (platform.system() != 'Darwin'):
# Run the bazel based buil
run_bazel_build_test(venv_dir, build_dir)
# First run the C++ gtests
run_ngtf_gtests(build_dir, None)
# If the GPU tests are requested, then run them as well
if (arguments.gpu_unit_tests_enable):
os.environ['NGRAPH_TF_BACKEND'] = 'GPU'
run_ngtf_gtests(
build_dir,
str("-ArrayOps.Quanti*:ArrayOps.Dequant*:BackendManager.BackendAssignment:"
"MathOps.AnyKeepDims:MathOps.AnyNegativeAxis:MathOps.AnyPositiveAxis:"
"MathOps.AllKeepDims:MathOps.AllNegativeAxis:MathOps.AllPositiveAxis:"
"NNOps.Qu*:NNOps.SoftmaxZeroDimTest*:"
"NNOps.SparseSoftmaxCrossEntropyWithLogits"))
os.environ['NGRAPH_TF_BACKEND'] = 'CPU'
# Next run Python unit tests
load_venv(venv_dir)
run_ngtf_pytests(venv_dir, build_dir)
if (arguments.test_examples):
# Run the C++ example build/run test
run_cpp_example_test('build')
# Next run the TensorFlow python tests
run_tensorflow_pytests(venv_dir, build_dir, './', 'build/tensorflow')
# Finally run Resnet50 based training and inferences
run_resnet50(build_dir)
os.chdir(root_pwd)
