def msame_run(self, msame_dir):
"""
Function Description:
run msame project
Parameter:
msame_dir: msame project directory
Return Value:
npu dump data path
Exception Description:
when invalid npu dump data path throw exception
"""
self._compare_shape_vs_bin_file()
npu_data_output_dir = os.path.join(self.arguments.out_path,
NPU_DUMP_DATA_BASE_PATH)
utils.create_directory(npu_data_output_dir)
model_name, extension = utils.get_model_name_and_extension(
self.arguments.offline_model_path)
acl_json_path = os.path.join(msame_dir, ACL_JSON_PATH)
if not os.path.exists(acl_json_path):
os.mknod(acl_json_path, mode=0o600)
self._write_content_to_acl_json(acl_json_path, model_name,
npu_data_output_dir)
msame_cmd = [
"./" + MSAME_COMMAND_PATH, "--model",
self.arguments.offline_model_path, "--input",
self.arguments.input_path, "--device", self.arguments.device,
"--output", npu_data_output_dir
]
self._make_msame_cmd_for_shape_range(msame_cmd)
os.chdir(os.path.join(msame_dir, OUT_PATH))
# do msame command
utils.print_info_log(
"Run command line: cd %s && %s" %
(os.path.join(msame_dir, OUT_PATH), " ".join(msame_cmd)))
utils.execute_command(msame_cmd)
npu_dump_data_path, file_is_exist = utils.get_dump_data_path(
npu_data_output_dir)
if not file_is_exist:
utils.print_error_log("The path {} dump data is not exist.".format(
npu_dump_data_path))
raise AccuracyCompareException(
utils.ACCURACY_COMPARISON_INVALID_PATH_ERROR)
# net output data path
npu_net_output_data_path, file_is_exist = utils.get_dump_data_path(
npu_data_output_dir, True)
if not file_is_exist:
utils.print_error_log(
"The path {} net output data is not exist.".format(
npu_net_output_data_path))
raise AccuracyCompareException(
utils.ACCURACY_COMPARISON_INVALID_PATH_ERROR)
self._convert_net_output_to_numpy(npu_net_output_data_path)
return npu_dump_data_path, npu_net_output_data_path
def save(self, export_path):
create_directory(export_path)
# The number and order of constructor arguments must match.
with open(os.path.join(export_path, 'params.pkl'), 'wb') as f:
pickle.dump([ # the arguments of the class constructor
self.input_dim, self.z_dim,
self.d_conv_filters, self.d_conv_kernel_size, self.d_conv_strides, self.d_batch_norm_momentum, self.d_dropout_rate,
self. g_initial_dense_layer_size, self.g_upsample,
self.g_conv_filters, self.g_conv_kernel_size, self.g_conv_strides, self.g_batch_norm_momentum, self.g_dropout_rate,
], f)
def main(args):
in_stash = biggie.Stash(args.data_file)
utils.create_directory(os.path.dirname(args.output_file))
if os.path.exists(args.output_file):
os.remove(args.output_file)
out_stash = biggie.Stash(args.output_file)
STATUS['total'] = len(in_stash)
for idx, key in enumerate(in_stash.keys()):
new_entity = wrap_cqt_for_key(in_stash.get(key), args.length,
args.stride)
out_stash.add(key, new_entity)
out_stash.close()
def main(args):
in_stash = biggie.Stash(args.data_file)
utils.create_directory(os.path.dirname(args.output_file))
if os.path.exists(args.output_file):
os.remove(args.output_file)
out_stash = biggie.Stash(args.output_file)
STATUS['total'] = len(in_stash)
for idx, key in enumerate(in_stash.keys()):
new_entity = wrap_cqt_for_key(in_stash.get(key), args.length,
args.stride)
out_stash.add(key, new_entity)
out_stash.close()
def _save(self):
create_directory(self.export_path)
# The number and order of constructor arguments must match.
with open(os.path.join(self.export_path, 'params.pkl'), 'wb') as f:
pickle.dump(
[ # the arguments of the class constructor
self.input_dim, self.z_dim, self.encoder_conv_filters,
self.encoder_conv_kernel_size, self.encoder_conv_strides,
self.decoder_conv_t_filters,
self.decoder_conv_t_kernel_size,
self.decoder_conv_t_strides, self.use_batch_norm,
self.use_dropout, self.export_path
],
f)
def _create_dir(self):
# create input directory
utils.create_directory(self.data_dir)
# create dump_data/tf directory
utils.create_directory(self.tf_dump_data_dir)
# create tmp directory
utils.create_directory(self.tmp_dir)
def _create_dir(self):
# create input directory
data_dir = os.path.join(self.args.out_path, "input")
utils.create_directory(data_dir)
# create dump_data/onnx directory
onnx_dump_data_dir = os.path.join(self.args.out_path, "dump_data/onnx")
utils.create_directory(onnx_dump_data_dir)
# create model directory
model_dir = os.path.join(self.args.out_path, "model")
utils.create_directory(model_dir)
return data_dir, onnx_dump_data_dir, model_dir