def test_preprocess_message_type(self):
"""Test preprocessing of the message_type enum.
Verifies JSONPRC implementation of the _preprocess_message_type
function.
"""
generator = SmartFactoryJSONRPC.CodeGenerator()
message_type_elements = collections.OrderedDict()
message_type_elements[u"request"] = Model.EnumElement(name=u"request")
message_type_elements[u"response"] = Model.EnumElement(
name=u"response")
message_type_elements[u"notification"] = Model.EnumElement(
name=u"notification")
message_type = Model.Enum(name=u"messageType",
elements=message_type_elements)
result_enum = generator._preprocess_message_type(message_type)
self.assertIn("error_response", result_enum.elements)
self.assertEqual("error_response",
result_enum.elements["error_response"].primary_name)
message_type_elements = collections.OrderedDict()
message_type_elements[u"request"] = Model.EnumElement(name=u"request")
message_type_elements[u"notification"] = Model.EnumElement(
name=u"notification")
message_type = Model.Enum(name=u"messageType",
elements=message_type_elements)
result_enum = generator._preprocess_message_type(message_type)
self.assertNotIn("error_response", result_enum.elements)
def test_full_generation(self):
"""Test full generation using JSONRPC SmartSchema generator.
Creates output files which is captured by the mock and compare them
with sample files with correct code. This test requires valid
test_expected_jsonrpc.h and test_expected_jsonrpc.cc in the same
directory as this module.
"""
expected_h_file_content = open("test_expected_jsonrpc.h", "r").read()
expected_cc_file_content = open("test_expected_jsonrpc.cc", "r").read()
generator = SmartFactoryJSONRPC.CodeGenerator()
message_type_elements = collections.OrderedDict()
message_type_elements[u"request"] = Model.EnumElement(name=u"request")
message_type_elements[u"response"] = Model.EnumElement(
name=u"response")
message_type_elements[u"notification"] = Model.EnumElement(
name=u"notification")
message_type = Model.Enum(name=u"messageType",
elements=message_type_elements)
elements1 = collections.OrderedDict()
elements1[u"name1"] = Model.EnumElement(
name=u"name1",
design_description=DESIGN_DESCRIPTION,
todos=TODOS,
value=u"1")
elements1[u"name2"] = Model.EnumElement(
name="name2",
description=DESCRIPTION,
issues=ISSUES,
internal_name=u"internal_name2")
enum1 = Model.Enum(name=u"Enum1", todos=TODOS, elements=elements1)
elements2 = collections.OrderedDict()
elements2[u"xxx"] = Model.EnumElement(name=u"xxx",
internal_name=u"val_1")
elements2[u"yyy"] = Model.EnumElement(name=u"yyy",
internal_name=u"val_2",
value=u"100")
elements2[u"zzz"] = Model.EnumElement(name=u"val_3")
enum2 = Model.Enum(name=u"E2", elements=elements2)
elements3 = collections.OrderedDict()
elements3["1"] = Model.EnumElement(name="xxx", internal_name="_1")
elements3["2"] = Model.EnumElement(name="xxx", internal_name="_2")
elements3["3"] = Model.EnumElement(name="xxx", internal_name="_3")
enum3 = Model.Enum(name="Enum_new2", elements=elements3)
elements4 = collections.OrderedDict()
elements4["name1"] = Model.EnumElement(name="xxx", internal_name="_11")
elements4["name2"] = Model.EnumElement(name="xxx", internal_name="_22")
enum4 = Model.Enum(name="Enum_new4", elements=elements4)
enums = collections.OrderedDict()
enums["Enum1"] = enum1
enums["Enum2"] = enum2
enums["Enum3"] = enum3
enums["Enum4"] = enum4
enums["messageType"] = message_type
params1 = collections.OrderedDict()
params1["1"] = Model.FunctionParam(
name="param1",
design_description=DESIGN_DESCRIPTION,
description=DESCRIPTION,
issues=ISSUES,
todos=TODOS,
param_type=enum4,
default_value=elements4["name1"])
params1["2"] = Model.FunctionParam(
name="param2",
param_type=Model.EnumSubset(
name="sub1",
enum=enum1,
allowed_elements={"e1": elements1["name1"]}),
default_value=elements1["name1"])
functions = collections.OrderedDict()
functions["Function1"] = Model.Function(
name="Function1",
function_id=elements1["name1"],
message_type=message_type_elements["request"],
params=params1)
functions["Function2"] = Model.Function(
name="Function2",
function_id=elements2["xxx"],
message_type=message_type_elements["response"])
functions["Function3"] = Model.Function(
name="Function2",
function_id=elements2["yyy"],
message_type=message_type_elements["notification"])
members1 = collections.OrderedDict()
members1["m1"] = Model.Param(name="intParam",
param_type=Model.Integer(max_value=2))
members1["m11"] = Model.Param(name="doubleParam",
param_type=Model.Double(min_value=0.333),
is_mandatory=False)
members1["m222"] = Model.Param(name="boolParam",
param_type=Model.Boolean())
members1["m2"] = Model.Param(name="structParam",
param_type=Model.Struct(name="Struct2"))
members1["aaa"] = Model.Param(name="enumParam", param_type=enum1)
members1["bbb"] = Model.Param(name="enumParam1", param_type=enum1)
members1["xxx"] = Model.Param(
name="enumSubset1",
param_type=Model.EnumSubset(
name="sub",
enum=enum1,
allowed_elements={"e1": elements1["name1"]}),
is_mandatory=False)
members1["1"] = Model.Param(name="arrayOfInt",
param_type=Model.Array(
min_size=0,
max_size=20,
element_type=Model.Boolean()),
is_mandatory=False)
members1["2"] = Model.Param(name="arrayOfEnum1",
param_type=Model.Array(min_size=0,
max_size=20,
element_type=enum1),
is_mandatory=False)
members1["3"] = Model.Param(name="arrayOfEnum3",
param_type=Model.Array(min_size=10,
max_size=40,
element_type=enum3),
is_mandatory=True)
members1["4"] = Model.Param(
name="arrayOfEnum4",
param_type=Model.Array(
min_size=10,
max_size=41,
element_type=Model.EnumSubset(
name="sub1",
enum=enum1,
allowed_elements={"e1": elements1["name1"]})))
members1["5"] = Model.Param(
name="arrayOfEnum5",
param_type=Model.Array(
min_size=10,
max_size=42,
element_type=Model.EnumSubset(
name="sub2",
enum=enum1,
allowed_elements={"e1": elements1["name2"]})))
members1["6"] = Model.Param(
name="arrayOfEnum6",
param_type=Model.Array(
min_size=10,
max_size=43,
element_type=Model.EnumSubset(
name="sub3",
enum=enum4,
allowed_elements={"e1": elements4["name2"]})))
structs = collections.OrderedDict()
structs["Struct1"] = Model.Struct(
name="Struct1",
design_description=DESIGN_DESCRIPTION,
issues=ISSUES,
members=members1)
structs["Struct2"] = Model.Struct(name="Struct2", issues=ISSUES)
interface = Model.Interface(enums=enums,
structs=structs,
functions=functions,
params={
"param1": "value1",
"param2": "value2"
})
os.path.exists = MagicMock(return_value=True)
uuid.uuid1 = MagicMock(
return_value=uuid.UUID("12345678123456781234567812345678"))
codecs.open = MagicMock()
generator.generate(interface=interface,
filename="Test.xml",
namespace="XXX::YYY::ZZZ",
destination_dir="/some/test/dir")
os.path.exists.assert_has_calls([call('/some/test/dir')])
open_result = codecs.open
mock_calls = open_result.mock_calls
self.assertEqual(
mock_calls[0],
call('/some/test/dir/Test.h', mode='w', encoding='utf-8'),
"Invalid header file creation")
self.assertEqual(
mock_calls[4],
call('/some/test/dir/Test.cc', mode='w', encoding='utf-8'),
"Invalid source file creation")
self.assertEqual(
str(mock_calls[2])[27:-2].replace("\\n", "\n"),
expected_h_file_content, "Invalid header file content")
self.assertEqual(
str(mock_calls[6])[27:-2].replace("\\n", "\n"),
expected_cc_file_content, "Invalid source file content")
u""" CSmartSchema error_response_schema(CObjectSchemaItem::create("""
u"""root_members_map));\n"""
u"""\n"""
u""" functions_schemes_.insert(std::make_pair("""
u"""NsSmartDeviceLink::NsJSONHandler::SmartSchemaKey<"""
u"""FunctionID::eType, messageType::eType>("""
u"""FunctionID::request, messageType::error_response)"""
u""", error_response_schema));\n"""
u"""\n""")
DESCRIPTION = [u"Description Line1", u"Description Line2"]
DESIGN_DESCRIPTION = [u"Design Line1"]
ISSUES = [
Model.Issue(value=u"Issue1"),
Model.Issue(value=u"Issue2"),
Model.Issue(value=u"Issue3")
]
TODOS = [u"Do1", u"Do2"]
class Test(unittest.TestCase):
"""Test for JSONRPC SmartFactory generator.
This class holds set of test cases for the JSONRPC SmartFactory generator.
"""
def test_gen_schema_params_fill(self):
"""Test feature that allows to create format specific PARAMS.
def _parse_param_base_item(self, element, prefix):
"""Parse base param items.
Returns params, other subelements and attributes.
"""
params, subelements, attrib = self._parse_base_item(element, "")
is_mandatory = self._extract_attrib(attrib, "mandatory")
if is_mandatory is None:
raise ParseError("'mandatory' is not specified for parameter '" +
params["name"] + "'")
params["is_mandatory"] = self._get_bool_from_string(is_mandatory)
scope = self._extract_attrib(attrib, "scope")
if scope is not None:
params["scope"] = scope
default_value = None
param_type = None
type_name = self._extract_attrib(attrib, "type")
if type_name is None:
raise ParseError("Type is not specified for parameter '" +
params["name"] + "'")
if type_name == "Boolean":
default_value = self._extract_attrib(attrib, "defvalue")
if default_value != None:
default_value = self._get_bool_from_string(default_value)
param_type = Model.Boolean(default_value=default_value)
elif type_name == "Integer" or \
type_name == "Float" or \
type_name == "Double" :
min_value = self._extract_optional_number_attrib(
attrib, "minvalue", int if type_name == "Integer" else float)
max_value = self._extract_optional_number_attrib(
attrib, "maxvalue", int if type_name == "Integer" else float)
default_value = self._extract_optional_number_attrib(
attrib, "defvalue", int if type_name == "Integer" else float)
param_type = \
(Model.Integer if type_name == "Integer" else Model.Double)(
min_value=min_value,
max_value=max_value,
default_value=default_value)
elif type_name == "String":
min_length = self._extract_optional_number_attrib(
attrib, "minlength")
# if minlength is not defined default value is 1
if min_length is None:
min_length = 1
max_length = self._extract_optional_number_attrib(
attrib, "maxlength")
default_value = self._extract_attrib(attrib, "defvalue")
param_type = Model.String(min_length=min_length,
max_length=max_length,
default_value=default_value)
else:
if 1 == type_name.count("."):
custom_type_name = type_name.replace(".", "_")
else:
custom_type_name = prefix + type_name
if custom_type_name in self._types:
param_type = self._types[custom_type_name]
default_value = self._extract_attrib(attrib, "defvalue")
if default_value != None:
if default_value not in param_type.elements:
raise ParseError("Default value '" + default_value +
"' for parameter '" + params["name"] +
"' is not a member of " +
type(param_type).__name__ + "'" +
params["name"] + "'")
default_value = param_type.elements[default_value]
else:
raise ParseError("Unknown type '" + type_name + "'")
if self._extract_optional_bool_attrib(attrib, "array", False):
min_size = self._extract_optional_number_attrib(attrib, "minsize")
max_size = self._extract_optional_number_attrib(attrib, "maxsize")
param_type = Model.Array(element_type=param_type,
min_size=min_size,
max_size=max_size)
base_type = \
param_type.element_type if isinstance(param_type, Model.Array) \
else param_type
other_subelements = []
for subelement in subelements:
if subelement.tag == "element":
if type(base_type) is not Model.Enum and \
type(base_type) is not Model.EnumSubset:
raise ParseError("Elements specified for parameter '" +
params["name"] + "' of type " +
type(base_type).__name__)
if type(base_type) is Model.Enum:
base_type = Model.EnumSubset(
name=params["name"],
enum=base_type,
description=params["description"],
design_description=params["design_description"],
issues=params["issues"],
todos=params["todos"],
allowed_elements={})
if "name" not in subelement.attrib:
raise ParseError(
"Element name is not specified for parameter '" +
params["name"] + "'")
element_name = subelement.attrib["name"]
if len(subelement.attrib) != 1:
raise ParseError("Unexpected attributes for element '" +
element_name + "' of parameter '" +
params["name"])
if len(subelement.getchildren()) != 0:
raise ParseError("Unexpected subelements for element '" +
element_name + "' of parameter '" +
params["name"])
if element_name in base_type.allowed_elements:
raise ParseError("Element '" + element_name +
"' is specified more than once for" +
" parameter '" + params["name"] + "'")
if element_name not in base_type.enum.elements:
raise ParseError("Element '" + element_name +
"' is not a member of enum '" +
base_type.enum.name + "'")
base_type.allowed_elements[element_name] = \
base_type.enum.elements[element_name]
else:
other_subelements.append(subelement)
if isinstance(param_type, Model.Array):
param_type.element_type = base_type
else:
param_type = base_type
params["param_type"] = param_type
if default_value is not None:
params["default_value"] = default_value
return params, other_subelements, attrib
*/
val_2 = 100,
/**
* @brief val_3.
*/
val_3
};
} // E2
"""
DESCRIPTION = [u"Description Line1", u"Description Line2"]
DESIGN_DESCRIPTION = [u"Design Line1"]
ISSUES = [Model.Issue(value=u"Issue1"),
Model.Issue(value=u"Issue2"),
Model.Issue(value=u"Issue3")]
TODOS = [u"Do1", u"Do2"]
class Test(unittest.TestCase):
"""Test for SmartFactory base generator.
This class holds set of test cases for the SmartFactory base generator.
"""
def test_gen_comment(self):
def generate(self, interface, filename, namespace, destination_dir):
""" Generate SmartFactory source files.
Generates source code files at destination directory in
accordance with given model in specified namespace.
Keyword arguments:
interface -- model of the interface to generate source code for.
filename -- name of initial XML file.
namespace -- name of destination namespace.
destination_dir -- directory to create source files.
"""
if interface is None:
raise GenerateError("Given interface is None.")
params_set = set()
for func in interface.functions.values():
for param in func.params:
params_set.add(param)
parameter_enum = Model.Enum('Parameter')
for item in params_set:
parameter_enum.elements[item.upper()] = Model.EnumElement(item)
required_enums_for_policy = [
"HMILevel", "FunctionID", "HybridAppPreference", "AppHMIType",
"RequestType", "ModuleType", "Common_AppPriority", "Parameter"
]
self.required_empty_value = ["RequestType", "ModuleType", "Parameter"]
self.enum_items_naming_conversion_ = {
"HMILevel":
lambda item_name: "HL_" + item_name.replace("HMI_", ""),
"AppHMIType":
lambda item_name: "AHT_" + item_name,
"FunctionID":
lambda item_name: item_name,
"HybridAppPreference":
lambda item_name: item_name,
"RequestType":
lambda item_name: "RT_" + item_name,
"ModuleType":
lambda item_name: "MT_" + item_name,
"Common_AppPriority":
lambda item_name: "P_" + item_name
if not item_name == "VOICE_COMMUNICATION" else "P_VOICECOM",
"Parameter":
lambda item_name: "P_" + to_snake_case(item_name).upper()
}
self.enum_items_string_naming_conversion_ = {
"HMILevel":
lambda item_name: item_name,
"AppHMIType":
lambda item_name: item_name,
"FunctionID":
lambda item_name: item_name[:item_name.rfind("ID")],
"HybridAppPreference":
lambda item_name: item_name,
"RequestType":
lambda item_name: item_name,
"ModuleType":
lambda item_name: item_name,
"Common_AppPriority":
lambda item_name: item_name
if not item_name == "VOICE_COMMUNICATION" else "VOICECOM",
"Parameter":
lambda item_name: item_name
}
self.enum_naming_conversion_ = {
"HMILevel": "HmiLevel",
"AppHMIType": "AppHMIType",
"FunctionID": "FunctionID",
"HybridAppPreference": "HybridAppPreference",
"RequestType": "RequestType",
"ModuleType": "ModuleType",
"Common_AppPriority": "Priority",
"Parameter": "Parameter"
}
get_first_enum_value_name = lambda enum: enum.elements.values()[0].name
enum_required_for_policy = lambda enum: enum.name in required_enums_for_policy and "." not in get_first_enum_value_name(
enum)
# In case if "." is in FunctionID name this is HMI_API function ID and should not be included in Policy enums
required_enum_values = [
val for val in interface.enums.values()
if enum_required_for_policy(val)
]
if filename == "MOBILE_API":
self._write_cc_with_enum_schema_factory(filename, namespace,
destination_dir,
interface.enums.values())
# Params should be generated as enum for MOBILE_API to validate RPCSpec parameters
required_enum_values.append(parameter_enum)
self._write_header_with_enums(filename, namespace, destination_dir,
required_enum_values)
self._write_cc_with_enums(filename, namespace, destination_dir,
required_enum_values)
# dset = simulatedData(opt["dataset_path"], time_points = opt["time_points"])
dset = SCData(opt["dataset_path"])
# denormalizer = dset.denormalize
loader = DataLoader(dset,
batch_size=opt["batch_size"],
shuffle=True,
num_workers=0)
loader_iterator = iter(loader)
data_len = len(loader)
gen_o = opt['models']['generator']
dis_o = opt['models']['discriminator']
gen = Gen(opt["z_slow_dim"], opt["z_fast_dim"], opt["genes_num"],
opt["time_points"], opt["batch_size"])
dis = Dis(opt["genes_num"], opt["time_points"], opt["batch_size"])
if opt['use_cuda']:
start = time.time()
gen.cuda()
end = time.time()
print("Generator moved to GPU in {} seconds".format(end - start))
start = time.time()
dis.cuda()
end = time.time()
print("Discriminator moved to GPU in {} seconds".format(end - start))
start_epoch = 0 #default starting epoch is 0
