def package_simple_addition_model(self, test_dir, custom_ops, do_fail=False):
neuropod_path = os.path.join(test_dir, "test_neuropod")
model_code_dir = os.path.join(test_dir, "model_code")
os.makedirs(model_code_dir)
with open(os.path.join(model_code_dir, "addition_model.py"), "w") as f:
f.write(ADDITION_MODEL_SOURCE)
# `create_pytorch_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_pytorch_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
data_paths=[],
code_path_spec=[
{
"python_root": model_code_dir,
"dirs_to_package": [""], # Package everything in the python_root
}
],
entrypoint_package="addition_model",
entrypoint="get_model",
custom_ops=custom_ops,
requirements="""
torch==1.4.0
""",
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail)
)
return neuropod_path
def package_simple_addition_model(self, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
model_code_dir = os.path.join(test_dir, "model_code")
os.makedirs(model_code_dir)
model_ops_dir = os.path.join(test_dir, "model_ops")
os.makedirs(model_ops_dir)
with open(os.path.join(model_code_dir, "model.prototxt"),
"w") as f:
f.write(ADDITION_MODEL_SOURCE)
with open(os.path.join(model_ops_dir, "CustomLayer.py"), "w") as f:
f.write(CUSTOM_OPS)
create_caffe_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
prototxt=os.path.join(model_code_dir, "model.prototxt"),
node_name_mapping={
'x': 'data1',
'y': 'data2',
'out': 'out',
},
code_path_spec=[{
"python_root": test_dir,
"dirs_to_package": ["model_ops"],
}],
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
model_code_dir = os.path.join(test_dir, "model_code")
os.makedirs(model_code_dir)
with open(os.path.join(model_code_dir, "addition_model.py"),
"w") as f:
f.write(ADDITION_MODEL_SOURCE)
# `create_python_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_python_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
data_paths=[],
code_path_spec=[{
"python_root":
model_code_dir,
"dirs_to_package": [
"" # Package everything in the python_root
],
}],
entrypoint_package="addition_model",
entrypoint="get_model",
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False):
for model in [CustomOpModel]:
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
# `create_torchscript_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_torchscript_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
module=model(),
custom_ops=[self.custom_op_path, self.second_custom_op],
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
def package_simple_addition_model(self, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
create_onnx_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
onnx_model=create_onnx_addition_model(),
node_name_mapping={
"x": "X",
"y": "Y",
"out": "Z",
},
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False, **kwargs):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
# Get the input/output spec along with test data
kwargs.update(get_addition_model_spec(do_fail=do_fail))
# `create_tensorflow_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_tensorflow_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
trackable_obj=create_tf_addition_model(),
**kwargs)
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
# `create_tensorflow_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_tensorflow_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
graph_def=create_tf_addition_model(self.custom_op_path),
node_name_mapping={
"x": "some_namespace/in_x:0",
"y": "some_namespace/in_y:0",
"out": "some_namespace/out:0",
},
custom_ops=[self.custom_op_path, self.second_custom_op],
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
def package_simple_addition_model(self, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
net = AdditionModel()
net.initialize()
net.hybridize()
net.forward(mx.nd.array([1, 2, 3]), mx.nd.array([1, 2, 3]))
create_mxnet_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
module=net,
input_names=['data0', 'data1'],
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False):
for model in [
AdditionModel, AdditionModelDictInput,
AdditionModelTensorOutput
]:
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
# `create_torchscript_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_torchscript_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
module=model(),
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, alias_names=False, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
if alias_names:
node_name_mapping = {"x": "x_", "y": "y_", "out": "out_"}
else:
node_name_mapping = None
# `create_keras_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_keras_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
sess=tf.keras.backend.get_session(),
model=create_keras_addition_model(node_name_mapping),
node_name_mapping=node_name_mapping,
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False, **kwargs):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
# Get the input/output spec along with test data
kwargs.update(get_addition_model_spec(do_fail=do_fail))
# `create_tensorflow_neuropod` runs inference with the test data immediately
# after creating the neuropod. Raises a ValueError if the model output
# does not match the expected output.
create_tensorflow_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
graph_def=create_tf_addition_model(),
node_name_mapping={
"x": "some_namespace/in_x:0",
"y": "some_namespace/in_y:0",
# The `:0` is optional
"out": "some_namespace/out",
},
**kwargs)
# Run some additional checks
check_addition_model(neuropod_path)
def package_simple_addition_model(self, do_fail=False):
with TemporaryDirectory() as test_dir:
neuropod_path = os.path.join(test_dir, "test_neuropod")
INIT_NET = os.path.join(test_dir, "init_net.pb")
PREDICT_NET = os.path.join(test_dir, "predict_net.pb")
SaveNet(INIT_NET, PREDICT_NET, workspace,
create_caffe2_addition_model())
create_caffe2_neuropod(
neuropod_path=neuropod_path,
model_name="addition_model",
node_name_mapping={
"x": "X",
"y": "Y",
"out": "Z",
},
predict_net=PREDICT_NET,
init_net=INIT_NET,
# Get the input/output spec along with test data
**get_addition_model_spec(do_fail=do_fail))
# Run some additional checks
check_addition_model(neuropod_path)
def test_output_spec_inference(self):
# Test whether addition model's output spec is inferred correctly
inferred_spec = infer_keras_output_spec(create_keras_addition_model())
self.assertEquals(get_addition_model_spec()["output_spec"],
inferred_spec)
