def test_load_existing_but_not_a_library(self):
tmp = tempfile.NamedTemporaryFile(delete=False)
for _ in range(10):
tmp.write(b"0xdeadbeef\n")
tmp.close()
with self.assertRaises(RuntimeError):
plugin_manager.load_library(tmp.name)
os.remove(tmp.name)
def main():
plugin_manager.load_library('./cmake-build-debug/libCustomOp.so')
pipe = TestPipeline(batch_size=8, num_threads=4, device_id=0)
pipe.build()
pipe_out = pipe.run()
gimage, gmask = pipe_out
print(gmask.as_tensor())
print(gmask.layout())
def test_pipeline_including_custom_plugin(self):
plugin_manager.load_library(test_bin_dir + "/libcustomdummyplugin.so")
pipe = CustomPipeline(batch_size, 1, 0)
pipe.build()
pipe_out = pipe.run()
print(pipe_out)
images, output = pipe_out
output_cpu = output.asCPU()
assert len(images) == batch_size
assert len(output_cpu) == batch_size
for i in range(len(images)):
img = images.at(i)
out = output_cpu.at(i)
assert img.shape == out.shape
np.testing.assert_array_equal(img, out)
def test_load_custom_operator_plugin(self):
with self.assertRaises(AttributeError):
print(ops.CustomDummy)
plugin_manager.load_library(test_bin_dir + "/libcustomdummyplugin.so")
print(ops.CustomDummy)
def test_load_existing_but_not_a_library(self):
with self.assertRaises(RuntimeError):
plugin_manager.load_library(test_bin_dir + "/dali_test.bin")
def test_load_unexisting_library(self):
with self.assertRaises(RuntimeError):
plugin_manager.load_library("not_a_dali_plugin.so")
def test_python_operator_and_custom_plugin(self):
plugin_manager.load_library(test_bin_dir + "/libcustomdummyplugin.so")
ops.readers.TFRecord(path="dummy", index_path="dummy", features={})
# subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
# FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
# COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
# IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
import nvidia.dali as dali
import nvidia.dali.plugin_manager as plugin_manager
plugin_manager.load_library('./model_repository/libcustomcopy.so')
def parse_args():
import argparse
parser = argparse.ArgumentParser(
description="Serialize the pipeline and save it to a file")
parser.add_argument('file_path',
type=str,
help='The path where to save the serialized pipeline')
return parser.parse_args()
@dali.pipeline_def(batch_size=3, num_threads=1, device_id=0)
def pipe():
data = dali.fn.external_source(device="cpu", name="DALI_INPUT_0")
types.int64)
@cfunc(c_sig, nopython=True)
def hello_cfunc(in_ptr, out_ptr, size):
in_arr = carray(in_ptr, size)
out_arr = carray(out_ptr, size)
out_arr[:] = 255
#print(hello_cfunc.address)
#print(hello_cfunc.inspect_llvm())
import nvidia.dali.plugin_manager as plugin_manager
plugin_manager.load_library(
'/home/agartner/dali-numba-plugin/libcustomdummy.so')
image_dir = "/home/agartner/DALI/docs/examples/data/images"
batch_size = 8
import nvidia.dali.ops as ops
import nvidia.dali.types as types
from nvidia.dali.pipeline import Pipeline
class SimplePipeline(Pipeline):
def __init__(self, batch_size, num_threads, device_id):
super(SimplePipeline, self).__init__(batch_size,
num_threads,
device_id,
seed=12)
self.input = ops.FileReader(file_root=image_dir)
