def test_negative_create_1(self, data):
"""
@test: Create gpg key with valid name and valid gpg key via file import
then try to create new one with same name
@feature: GPG Keys
@assert: gpg key is not created
"""
# Setup data to pass to the factory
data = data.copy()
data['organization-id'] = self.org['label']
try:
new_obj = make_gpg_key(data)
except Exception, e:
self.fail(e)
def test_positive_create_2(self, data):
"""
@test: Create gpg key with valid name and valid gpg key via file import
using the a new organization
@feature: GPG Keys
@assert: gpg key is created
"""
# Setup data to pass to the factory
data = data.copy()
data['key'] = VALID_GPG_KEY_FILE_PATH
data['organization-id'] = self.org['label']
try:
new_obj = make_gpg_key(data)
except Exception, e:
self.fail(e)
def test_negative_create_2(self, data):
"""
@test: Create gpg key with valid name and no gpg key
@feature: GPG Keys
@assert: gpg key is not created
"""
# Setup data to pass to create
data = data.copy()
data['organization-id'] = self.org['label']
# Try to create a new object passing @data to factory method
new_obj = GPGKey().create(data)
self.assertNotEqual(
new_obj.return_code, 0, "Object should not be created")
self.assertGreater(
len(new_obj.stderr), 0, "Should have raised an exception")
def test_positive_create_1(self, data):
"""
@test: Create gpg key with valid name and valid gpg key via file import
using the default created organization
@feature: GPG Keys
@assert: gpg key is created
"""
result = Org.list()
self.assertGreater(len(result.stdout), 0, 'No organization found')
org = result.stdout[0]
# Setup data to pass to the factory
data = data.copy()
data['key'] = VALID_GPG_KEY_FILE_PATH
data['organization-id'] = org['label']
try:
new_obj = make_gpg_key(data)
except Exception, e:
self.fail(e)
def test_negative_create_3(self, data):
"""
@test: Create gpg key with invalid name and valid gpg key via
file import
@feature: GPG Keys
@assert: gpg key is not created
"""
# Setup data to pass to create
data = data.copy()
data['key'] = '/tmp/%s' % generate_name()
data['organization-id'] = self.org['label']
ssh.upload_file(
local_file=VALID_GPG_KEY_FILE_PATH, remote_file=data['key'])
# Try to create a new object passing @data to factory method
new_obj = GPGKey().create(data)
self.assertNotEqual(
new_obj.return_code, 0, "Object should not be created")
self.assertGreater(
len(new_obj.stderr), 0, "Should have raised an exception")
def test(self, data):
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
# load library
dl = ctypes.cdll.LoadLibrary
quant_lib = dl("nnieqat/gpu/lib/libgfpq_gpu.so")
_libcublas = ctypes.cdll.LoadLibrary("libcublas.so")
# struct GFPQ_PARAM_ST in gfpq.hpp
class GFPQ_PARAM_ST(ctypes.Structure):
_fields_ = [("mode", ctypes.c_int), ("buf", ctypes.c_byte * 16)]
class _types:
"""Some alias types."""
handle = ctypes.c_void_p
stream = ctypes.c_void_p
data_origin = data.copy()
print(
"----------------------------------------------------------------------"
)
print("\n\nOriginal data:")
print(data)
data = data.astype(np.float32)
stream = cuda.stream()
_libcublas.cublasCreate_v2.restype = int
_libcublas.cublasCreate_v2.argtypes = [ctypes.c_void_p]
cublas_handle = _types.handle()
_libcublas.cublasCreate_v2(ctypes.byref(cublas_handle))
data_gpu = cuda.to_device(data, stream=stream)
data_p = data_gpu.device_ctypes_pointer
bit_width = 8
param = GFPQ_PARAM_ST()
# init or update param first
param.mode = 0
ret = quant_lib.HI_GFPQ_QuantAndDeQuant_GPU_PY(data_p, data.size,
bit_width,
ctypes.byref(param),
stream.handle,
cublas_handle)
if ret != 0:
print("HI_GFPQ_QuantAndDeQuant failed(%d)\n" % (ret)),
# use apply param
param.mode = 2
ret = quant_lib.HI_GFPQ_QuantAndDeQuant_GPU_PY(data_p, data.size,
bit_width,
ctypes.byref(param),
stream.handle,
cublas_handle)
if ret != 0:
print("HI_GFPQ_QuantAndDeQuant failed(%d)" % (ret)),
data_gpu.copy_to_host(data, stream=stream)
# data may not be available
stream.synchronize()
_libcublas.cublasDestroy_v2(cublas_handle)
import nnieqat
from quant_impl import fake_quantize
import torch
tensor = torch.Tensor(data_origin).cuda()
tensor.data = fake_quantize(tensor.data.detach(), 8)
diff = abs(tensor.cpu().numpy() - data)
# diff_thres = np.max(abs(data)) * 0.001
# print("\nDIFF > 0.1%: ")
# print("idx: ", np.where(diff > diff_thres))
# print("Original data:", data_origin[np.where(diff > diff_thres)])
# print("GFPQ result:", data[np.where(diff > diff_thres)])
# print("Impl result:", tensor.cpu().numpy()[np.where(diff > diff_thres)])
diff_max = np.max(diff)
print("\nDIFF MAX: " + str(diff_max))
print("\nDIFF RATIO: " +
str(diff_max / max(np.max(abs(data)), pow(10, -18))))
def test_do_activity_key_error(self, data):
data_mock = data.copy()
del data_mock['result']
self.verifypublishresponse.logger = MagicMock()
self.assertRaises(KeyError, self.verifypublishresponse.do_activity, data_mock)
def test_do_activity_key_error(self, data):
data_mock = data.copy()
del data_mock['result']
self.verifypublishresponse.logger = MagicMock()
self.assertRaises(KeyError, self.verifypublishresponse.do_activity,
data_mock)
