def format_model_config(flags):
with open(flags.config) as f:
configs = yaml.load(f)
library_name = configs.get(YAMLKeyword.library_name, "")
mace_check(
len(library_name) > 0, ModuleName.YAML_CONFIG,
"library name should not be empty")
if flags.target_abis:
target_abis = flags.target_abis.split(',')
else:
target_abis = configs.get(YAMLKeyword.target_abis, [])
mace_check((isinstance(target_abis, list) and len(target_abis) > 0),
ModuleName.YAML_CONFIG, "target_abis list is needed")
configs[YAMLKeyword.target_abis] = target_abis
for abi in target_abis:
mace_check(abi in ABITypeStrs, ModuleName.YAML_CONFIG,
"target_abis must be in " + str(ABITypeStrs))
target_socs = configs.get(YAMLKeyword.target_socs, "")
if flags.target_socs and flags.target_socs != TargetSOCTag.random \
and flags.target_socs != TargetSOCTag.all:
configs[YAMLKeyword.target_socs] = \
[soc.lower() for soc in flags.target_socs.split(',')]
elif not target_socs:
configs[YAMLKeyword.target_socs] = []
elif not isinstance(target_socs, list):
configs[YAMLKeyword.target_socs] = [target_socs]
configs[YAMLKeyword.target_socs] = \
[soc.lower() for soc in configs[YAMLKeyword.target_socs]]
if ABIType.armeabi_v7a in target_abis \
or ABIType.arm64_v8a in target_abis:
available_socs = sh_commands.adb_get_all_socs()
target_socs = configs[YAMLKeyword.target_socs]
if TargetSOCTag.all in target_socs:
mace_check(
available_socs, ModuleName.YAML_CONFIG,
"Android abi is listed in config file and "
"build for all SOCs plugged in computer, "
"But no android phone found, "
"you at least plug in one phone")
else:
for soc in target_socs:
mace_check(
soc in available_socs, ModuleName.YAML_CONFIG,
"Build specified SOC library, "
"you must plug in a phone using the SOC")
if flags.model_graph_format:
model_graph_format = flags.model_graph_format
else:
model_graph_format = configs.get(YAMLKeyword.model_graph_format, "")
mace_check(
model_graph_format in ModelFormatStrs, ModuleName.YAML_CONFIG,
'You must set model_graph_format and '
"model_graph_format must be in " + str(ModelFormatStrs))
configs[YAMLKeyword.model_graph_format] = model_graph_format
if flags.model_data_format:
model_data_format = flags.model_data_format
else:
model_data_format = configs.get(YAMLKeyword.model_data_format, "")
configs[YAMLKeyword.model_data_format] = model_data_format
mace_check(
model_data_format in ModelFormatStrs, ModuleName.YAML_CONFIG,
'You must set model_data_format and '
"model_data_format must be in " + str(ModelFormatStrs))
mace_check(
not (model_graph_format == ModelFormat.file
and model_data_format == ModelFormat.code),
ModuleName.YAML_CONFIG, "If model_graph format is 'file',"
" the model_data_format must be 'file' too")
model_names = configs.get(YAMLKeyword.models, [])
mace_check(
len(model_names) > 0, ModuleName.YAML_CONFIG,
"no model found in config file")
model_name_reg = re.compile(r'^[a-zA-Z0-9_]+$')
for model_name in model_names:
# check model_name legality
mace_check(model_name not in CPP_KEYWORDS, ModuleName.YAML_CONFIG,
"model name should not be c++ keyword.")
mace_check((model_name[0] == '_' or model_name[0].isalpha())
and bool(model_name_reg.match(model_name)),
ModuleName.YAML_CONFIG,
"model name should Meet the c++ naming convention"
" which start with '_' or alpha"
" and only contain alpha, number and '_'")
model_config = configs[YAMLKeyword.models][model_name]
platform = model_config.get(YAMLKeyword.platform, "")
mace_check(platform in PlatformTypeStrs, ModuleName.YAML_CONFIG,
"'platform' must be in " + str(PlatformTypeStrs))
for key in [
YAMLKeyword.model_file_path, YAMLKeyword.model_sha256_checksum
]:
value = model_config.get(key, "")
mace_check(value != "", ModuleName.YAML_CONFIG,
"'%s' is necessary" % key)
weight_file_path = model_config.get(YAMLKeyword.weight_file_path, "")
if weight_file_path:
weight_checksum = \
model_config.get(YAMLKeyword.weight_sha256_checksum, "")
mace_check(
weight_checksum != "", ModuleName.YAML_CONFIG,
"'%s' is necessary" % YAMLKeyword.weight_sha256_checksum)
else:
model_config[YAMLKeyword.weight_sha256_checksum] = ""
get_model_files(model_config, BUILD_DOWNLOADS_DIR)
runtime = model_config.get(YAMLKeyword.runtime, "")
mace_check(runtime in RuntimeTypeStrs, ModuleName.YAML_CONFIG,
"'runtime' must be in " + str(RuntimeTypeStrs))
if ABIType.host in target_abis:
mace_check(runtime == RuntimeType.cpu, ModuleName.YAML_CONFIG,
"host only support cpu runtime now.")
data_type = model_config.get(YAMLKeyword.data_type, "")
if runtime == RuntimeType.dsp:
if len(data_type) > 0:
mace_check(
data_type in DSPDataTypeStrs, ModuleName.YAML_CONFIG,
"'data_type' must be in " + str(DSPDataTypeStrs) +
" for dsp runtime")
else:
model_config[YAMLKeyword.data_type] = \
DSPDataType.uint8.value
elif runtime == RuntimeType.apu:
if len(data_type) > 0:
mace_check(
data_type in APUDataTypeStrs, ModuleName.YAML_CONFIG,
"'data_type' must be in " + str(APUDataTypeStrs) +
" for apu runtime")
else:
model_config[YAMLKeyword.data_type] = \
APUDataType.uint8.value
else:
if len(data_type) > 0:
mace_check(
data_type in FPDataTypeStrs, ModuleName.YAML_CONFIG,
"'data_type' must be in " + str(FPDataTypeStrs) +
" for cpu runtime")
else:
if runtime == RuntimeType.cpu:
model_config[YAMLKeyword.data_type] = \
FPDataType.fp32_fp32.value
else:
model_config[YAMLKeyword.data_type] = \
FPDataType.fp16_fp32.value
subgraphs = model_config.get(YAMLKeyword.subgraphs, "")
mace_check(
len(subgraphs) > 0, ModuleName.YAML_CONFIG,
"at least one subgraph is needed")
for subgraph in subgraphs:
for key in [
YAMLKeyword.input_tensors, YAMLKeyword.input_shapes,
YAMLKeyword.output_tensors, YAMLKeyword.output_shapes
]:
value = subgraph.get(key, "")
mace_check(value != "", ModuleName.YAML_CONFIG,
"'%s' is necessary in subgraph" % key)
if not isinstance(value, list):
subgraph[key] = [value]
subgraph[key] = [str(v) for v in subgraph[key]]
# --inputs_shapes will be passed to ELF file `mace_run_static', if input_shapes
# contains spaces, such as: '1, 3, 224, 224', because mace_run.cc use gflags to
# parse command line arguments, --input_shapes 1, 3, 224, 224 will be passed as
# `--input_shapes 1,'. So we strip out spaces here.
if key in [
YAMLKeyword.input_shapes, YAMLKeyword.output_shapes
]:
subgraph[key] = [e.replace(' ', '') for e in subgraph[key]]
input_size = len(subgraph[YAMLKeyword.input_tensors])
output_size = len(subgraph[YAMLKeyword.output_tensors])
mace_check(
len(subgraph[YAMLKeyword.input_shapes]) == input_size,
ModuleName.YAML_CONFIG,
"input shapes' size not equal inputs' size.")
mace_check(
len(subgraph[YAMLKeyword.output_shapes]) == output_size,
ModuleName.YAML_CONFIG,
"output shapes' size not equal outputs' size.")
for key in [YAMLKeyword.check_tensors, YAMLKeyword.check_shapes]:
value = subgraph.get(key, "")
if value != "":
if not isinstance(value, list):
subgraph[key] = [value]
subgraph[key] = [str(v) for v in subgraph[key]]
else:
subgraph[key] = []
for key in [
YAMLKeyword.input_data_types, YAMLKeyword.output_data_types
]:
if key == YAMLKeyword.input_data_types:
count = input_size
else:
count = output_size
data_types = subgraph.get(key, "")
if data_types:
if not isinstance(data_types, list):
subgraph[key] = [data_types] * count
for data_type in subgraph[key]:
mace_check(
data_type in InOutDataTypeStrs,
ModuleName.YAML_CONFIG,
key + " must be in " + str(InOutDataTypeStrs))
else:
subgraph[key] = [InOutDataType.float32] * count
input_data_formats = subgraph.get(YAMLKeyword.input_data_formats,
[])
if input_data_formats:
if not isinstance(input_data_formats, list):
subgraph[YAMLKeyword.input_data_formats] = \
[input_data_formats] * input_size
else:
mace_check(
len(input_data_formats) == input_size,
ModuleName.YAML_CONFIG,
"input_data_formats should match"
" the size of input.")
for input_data_format in \
subgraph[YAMLKeyword.input_data_formats]:
mace_check(
input_data_format in DataFormatStrs,
ModuleName.YAML_CONFIG,
"'input_data_formats' must be in " +
str(DataFormatStrs) + ", but got " + input_data_format)
else:
subgraph[YAMLKeyword.input_data_formats] = \
[DataFormat.NHWC] * input_size
output_data_formats = subgraph.get(YAMLKeyword.output_data_formats,
[])
if output_data_formats:
if not isinstance(output_data_formats, list):
subgraph[YAMLKeyword.output_data_formats] = \
[output_data_formats] * output_size
else:
mace_check(
len(output_data_formats) == output_size,
ModuleName.YAML_CONFIG,
"output_data_formats should match"
" the size of output")
for output_data_format in \
subgraph[YAMLKeyword.output_data_formats]:
mace_check(
output_data_format in DataFormatStrs,
ModuleName.YAML_CONFIG,
"'output_data_formats' must be in " +
str(DataFormatStrs))
else:
subgraph[YAMLKeyword.output_data_formats] = \
[DataFormat.NHWC] * output_size
validation_threshold = subgraph.get(
YAMLKeyword.validation_threshold, {})
if not isinstance(validation_threshold, dict):
raise argparse.ArgumentTypeError(
'similarity threshold must be a dict.')
threshold_dict = {
DeviceType.CPU: ValidationThreshold.cpu_threshold,
DeviceType.GPU: ValidationThreshold.gpu_threshold,
DeviceType.HEXAGON: ValidationThreshold.quantize_threshold,
DeviceType.HTA: ValidationThreshold.quantize_threshold,
DeviceType.APU: ValidationThreshold.quantize_threshold,
DeviceType.QUANTIZE: ValidationThreshold.quantize_threshold,
}
for k, v in six.iteritems(validation_threshold):
if k.upper() == 'DSP':
k = DeviceType.HEXAGON
if k.upper() not in (DeviceType.CPU, DeviceType.GPU,
DeviceType.HEXAGON, DeviceType.HTA,
DeviceType.QUANTIZE):
raise argparse.ArgumentTypeError(
'Unsupported validation threshold runtime: %s' % k)
threshold_dict[k.upper()] = v
subgraph[YAMLKeyword.validation_threshold] = threshold_dict
validation_inputs_data = subgraph.get(
YAMLKeyword.validation_inputs_data, [])
if not isinstance(validation_inputs_data, list):
subgraph[YAMLKeyword.validation_inputs_data] = [
validation_inputs_data
]
else:
subgraph[YAMLKeyword.validation_inputs_data] = \
validation_inputs_data
onnx_backend = subgraph.get(YAMLKeyword.backend, "tensorflow")
subgraph[YAMLKeyword.backend] = onnx_backend
validation_outputs_data = subgraph.get(
YAMLKeyword.validation_outputs_data, [])
if not isinstance(validation_outputs_data, list):
subgraph[YAMLKeyword.validation_outputs_data] = [
validation_outputs_data
]
else:
subgraph[YAMLKeyword.validation_outputs_data] = \
validation_outputs_data
input_ranges = subgraph.get(YAMLKeyword.input_ranges, [])
if not isinstance(input_ranges, list):
subgraph[YAMLKeyword.input_ranges] = [input_ranges]
else:
subgraph[YAMLKeyword.input_ranges] = input_ranges
subgraph[YAMLKeyword.input_ranges] = \
[str(v) for v in subgraph[YAMLKeyword.input_ranges]]
accuracy_validation_script = subgraph.get(
YAMLKeyword.accuracy_validation_script, "")
if isinstance(accuracy_validation_script, list):
mace_check(
len(accuracy_validation_script) == 1,
ModuleName.YAML_CONFIG,
"Only support one accuracy validation script")
accuracy_validation_script = accuracy_validation_script[0]
subgraph[YAMLKeyword.accuracy_validation_script] = \
accuracy_validation_script
for key in [
YAMLKeyword.limit_opencl_kernel_time,
YAMLKeyword.opencl_queue_window_size,
YAMLKeyword.nnlib_graph_mode, YAMLKeyword.obfuscate,
YAMLKeyword.winograd, YAMLKeyword.quantize,
YAMLKeyword.quantize_large_weights,
YAMLKeyword.change_concat_ranges
]:
value = model_config.get(key, "")
if value == "":
model_config[key] = 0
mace_check(
model_config[YAMLKeyword.quantize] == 0
or model_config[YAMLKeyword.quantize_large_weights] == 0,
ModuleName.YAML_CONFIG,
"quantize and quantize_large_weights should not be set to 1"
" at the same time.")
mace_check(
model_config[YAMLKeyword.winograd] in WinogradParameters,
ModuleName.YAML_CONFIG, "'winograd' parameters must be in " +
str(WinogradParameters) + ". 0 for disable winograd convolution")
return configs
def format_model_config(flags):
with open(flags.config) as f:
configs = yaml.load(f)
library_name = configs.get(YAMLKeyword.library_name, "")
mace_check(
len(library_name) > 0, ModuleName.YAML_CONFIG,
"library name should not be empty")
if flags.target_abis:
target_abis = flags.target_abis.split(',')
else:
target_abis = configs.get(YAMLKeyword.target_abis, [])
mace_check((isinstance(target_abis, list) and len(target_abis) > 0),
ModuleName.YAML_CONFIG, "target_abis list is needed")
configs[YAMLKeyword.target_abis] = target_abis
for abi in target_abis:
mace_check(abi in ABITypeStrs, ModuleName.YAML_CONFIG,
"target_abis must be in " + str(ABITypeStrs))
target_socs = configs.get(YAMLKeyword.target_socs, "")
if flags.target_socs:
configs[YAMLKeyword.target_socs] = \
[soc.lower() for soc in flags.target_socs.split(',')]
elif not target_socs:
configs[YAMLKeyword.target_socs] = []
elif not isinstance(target_socs, list):
configs[YAMLKeyword.target_socs] = [target_socs]
configs[YAMLKeyword.target_socs] = \
[soc.lower() for soc in configs[YAMLKeyword.target_socs]]
if ABIType.armeabi_v7a in target_abis \
or ABIType.arm64_v8a in target_abis:
available_socs = sh_commands.adb_get_all_socs()
target_socs = configs[YAMLKeyword.target_socs]
if ALL_SOC_TAG in target_socs:
mace_check(
available_socs, ModuleName.YAML_CONFIG,
"Android abi is listed in config file and "
"build for all SOCs plugged in computer, "
"But no android phone found, "
"you at least plug in one phone")
else:
for soc in target_socs:
mace_check(
soc in available_socs, ModuleName.YAML_CONFIG,
"Build specified SOC library, "
"you must plug in a phone using the SOC")
if flags.model_graph_format:
model_graph_format = flags.model_graph_format
else:
model_graph_format = configs.get(YAMLKeyword.model_graph_format, "")
mace_check(
model_graph_format in ModelFormatStrs, ModuleName.YAML_CONFIG,
'You must set model_graph_format and '
"model_graph_format must be in " + str(ModelFormatStrs))
configs[YAMLKeyword.model_graph_format] = model_graph_format
if flags.model_data_format:
model_data_format = flags.model_data_format
else:
model_data_format = configs.get(YAMLKeyword.model_data_format, "")
configs[YAMLKeyword.model_data_format] = model_data_format
mace_check(
model_data_format in ModelFormatStrs, ModuleName.YAML_CONFIG,
'You must set model_data_format and '
"model_data_format must be in " + str(ModelFormatStrs))
mace_check(
not (model_graph_format == ModelFormat.file
and model_data_format == ModelFormat.code),
ModuleName.YAML_CONFIG, "If model_graph format is 'file',"
" the model_data_format must be 'file' too")
model_names = configs.get(YAMLKeyword.models, [])
mace_check(
len(model_names) > 0, ModuleName.YAML_CONFIG,
"no model found in config file")
model_name_reg = re.compile(r'^[a-zA-Z0-9_]+$')
for model_name in model_names:
# check model_name legality
mace_check(model_name not in CPP_KEYWORDS, ModuleName.YAML_CONFIG,
"model name should not be c++ keyword.")
mace_check((model_name[0] == '_' or model_name[0].isalpha())
and bool(model_name_reg.match(model_name)),
ModuleName.YAML_CONFIG,
"model name should Meet the c++ naming convention"
" which start with '_' or alpha"
" and only contain alpha, number and '_'")
model_config = configs[YAMLKeyword.models][model_name]
platform = model_config.get(YAMLKeyword.platform, "")
mace_check(platform in PlatformTypeStrs, ModuleName.YAML_CONFIG,
"'platform' must be in " + str(PlatformTypeStrs))
for key in [
YAMLKeyword.model_file_path, YAMLKeyword.model_sha256_checksum
]:
value = model_config.get(key, "")
mace_check(value != "", ModuleName.YAML_CONFIG,
"'%s' is necessary" % key)
weight_file_path = model_config.get(YAMLKeyword.weight_file_path, "")
if weight_file_path:
weight_checksum = \
model_config.get(YAMLKeyword.weight_sha256_checksum, "")
mace_check(
weight_checksum != "", ModuleName.YAML_CONFIG,
"'%s' is necessary" % YAMLKeyword.weight_sha256_checksum)
else:
model_config[YAMLKeyword.weight_sha256_checksum] = ""
runtime = model_config.get(YAMLKeyword.runtime, "")
mace_check(runtime in RuntimeTypeStrs, ModuleName.YAML_CONFIG,
"'runtime' must be in " + str(RuntimeTypeStrs))
if ABIType.host in target_abis:
mace_check(runtime == RuntimeType.cpu, ModuleName.YAML_CONFIG,
"host only support cpu runtime now.")
data_type = model_config.get(YAMLKeyword.data_type, "")
if runtime == RuntimeType.dsp:
if len(data_type) > 0:
mace_check(
data_type in DSPDataTypeStrs, ModuleName.YAML_CONFIG,
"'data_type' must be in " + str(DSPDataTypeStrs) +
" for dsp runtime")
else:
model_config[YAMLKeyword.data_type] = \
DSPDataType.uint8.value
else:
if len(data_type) > 0:
mace_check(
data_type in FPDataTypeStrs, ModuleName.YAML_CONFIG,
"'data_type' must be in " + str(FPDataTypeStrs) +
" for cpu runtime")
else:
if runtime == RuntimeType.cpu:
model_config[YAMLKeyword.data_type] = \
FPDataType.fp32_fp32.value
else:
model_config[YAMLKeyword.data_type] = \
FPDataType.fp16_fp32.value
subgraphs = model_config.get(YAMLKeyword.subgraphs, "")
mace_check(
len(subgraphs) > 0, ModuleName.YAML_CONFIG,
"at least one subgraph is needed")
for subgraph in subgraphs:
for key in [
YAMLKeyword.input_tensors, YAMLKeyword.input_shapes,
YAMLKeyword.output_tensors, YAMLKeyword.output_shapes
]:
value = subgraph.get(key, "")
mace_check(value != "", ModuleName.YAML_CONFIG,
"'%s' is necessary in subgraph" % key)
if not isinstance(value, list):
subgraph[key] = [value]
subgraph[key] = [str(v) for v in subgraph[key]]
for key in [YAMLKeyword.check_tensors, YAMLKeyword.check_shapes]:
value = subgraph.get(key, "")
if value != "":
if not isinstance(value, list):
subgraph[key] = [value]
subgraph[key] = [str(v) for v in subgraph[key]]
else:
subgraph[key] = []
input_data_types = subgraph.get(YAMLKeyword.input_data_types, "")
if input_data_types:
if not isinstance(input_data_types, list):
subgraph[YAMLKeyword.input_data_types] = [input_data_types]
for input_data_type in subgraph[YAMLKeyword.input_data_types]:
mace_check(
input_data_type in InputDataTypeStrs,
ModuleName.YAML_CONFIG,
"'input_data_types' must be in " +
str(InputDataTypeStrs))
else:
subgraph[YAMLKeyword.input_data_types] = []
input_data_formats = subgraph.get(YAMLKeyword.input_data_formats,
[])
if input_data_formats:
if not isinstance(input_data_formats, list):
subgraph[YAMLKeyword.input_data_formats] =\
[input_data_formats]
else:
mace_check(
len(input_data_formats) == len(
subgraph[YAMLKeyword.input_tensors]),
ModuleName.YAML_CONFIG,
"input_data_formats should match"
" the size of input")
for input_data_format in\
subgraph[YAMLKeyword.input_data_formats]:
mace_check(
input_data_format in DataFormatStrs,
ModuleName.YAML_CONFIG,
"'input_data_formats' must be in " +
str(DataFormatStrs) + ", but got " + input_data_format)
else:
subgraph[YAMLKeyword.input_data_formats] = [DataFormat.NHWC]
output_data_formats = subgraph.get(YAMLKeyword.output_data_formats,
[])
if output_data_formats:
if not isinstance(output_data_formats, list):
subgraph[YAMLKeyword.output_data_formats] = \
[output_data_formats]
else:
mace_check(
len(output_data_formats) == len(
subgraph[YAMLKeyword.output_tensors]),
ModuleName.YAML_CONFIG,
"output_data_formats should match"
" the size of output")
for output_data_format in\
subgraph[YAMLKeyword.output_data_formats]:
mace_check(
output_data_format in DataFormatStrs,
ModuleName.YAML_CONFIG,
"'output_data_formats' must be in " +
str(DataFormatStrs))
else:
subgraph[YAMLKeyword.output_data_formats] = [DataFormat.NHWC]
validation_threshold = subgraph.get(
YAMLKeyword.validation_threshold, {})
if not isinstance(validation_threshold, dict):
raise argparse.ArgumentTypeError(
'similarity threshold must be a dict.')
threshold_dict = {
DeviceType.CPU:
ValidationThreshold.cpu_threshold,
DeviceType.GPU:
ValidationThreshold.gpu_threshold,
DeviceType.HEXAGON + "_QUANTIZE":
ValidationThreshold.hexagon_threshold,
DeviceType.CPU + "_QUANTIZE":
ValidationThreshold.cpu_quantize_threshold,
}
for k, v in six.iteritems(validation_threshold):
if k.upper() == 'DSP':
k = DeviceType.HEXAGON
if k.upper() not in (DeviceType.CPU, DeviceType.GPU,
DeviceType.HEXAGON,
DeviceType.CPU + "_QUANTIZE"):
raise argparse.ArgumentTypeError(
'Unsupported validation threshold runtime: %s' % k)
threshold_dict[k.upper()] = v
subgraph[YAMLKeyword.validation_threshold] = threshold_dict
validation_inputs_data = subgraph.get(
YAMLKeyword.validation_inputs_data, [])
if not isinstance(validation_inputs_data, list):
subgraph[YAMLKeyword.validation_inputs_data] = [
validation_inputs_data
]
else:
subgraph[YAMLKeyword.validation_inputs_data] = \
validation_inputs_data
onnx_backend = subgraph.get(YAMLKeyword.backend, "tensorflow")
subgraph[YAMLKeyword.backend] = onnx_backend
input_ranges = subgraph.get(YAMLKeyword.input_ranges, [])
if not isinstance(input_ranges, list):
subgraph[YAMLKeyword.input_ranges] = [input_ranges]
else:
subgraph[YAMLKeyword.input_ranges] = input_ranges
subgraph[YAMLKeyword.input_ranges] = \
[str(v) for v in subgraph[YAMLKeyword.input_ranges]]
for key in [
YAMLKeyword.limit_opencl_kernel_time,
YAMLKeyword.nnlib_graph_mode, YAMLKeyword.obfuscate,
YAMLKeyword.winograd, YAMLKeyword.quantize,
YAMLKeyword.change_concat_ranges
]:
value = model_config.get(key, "")
if value == "":
model_config[key] = 0
mace_check(
model_config[YAMLKeyword.winograd] in WinogradParameters,
ModuleName.YAML_CONFIG, "'winograd' parameters must be in " +
str(WinogradParameters) + ". 0 for disable winograd convolution")
weight_file_path = model_config.get(YAMLKeyword.weight_file_path, "")
model_config[YAMLKeyword.weight_file_path] = weight_file_path
return configs
