def generate_code(args):
LOG.propagate = False
nntool_shell = NNToolShell(args, allow_cli_args=False)
# handler = GeneratorShellLogHandler()
# formatter = logging.Formatter('%(module)s - %(message)s')
# handler.setFormatter(formatter)
# LOG.addHandler(handler)
# if args.log_level:
# LOG.setLevel(args.log_level.upper())
# else:
# LOG.setLevel('WARN')
LOG.info("Loading %s", args.graph_file)
nntool_shell.load_state_file(args.graph_file)
G = nntool_shell.G
opts = nntool_shell.settings
if args.model_file:
opts['model_file'] = args.model_file
if args.model_directory:
opts['model_directory'] = args.model_directory
if args.tensor_directory:
opts['tensor_directory'] = args.tensor_directory
opts['basic_kernel_header_file'] = args.model_file
opts['basic_kernel_source_file'] = args.model_file
os.makedirs(os.path.abspath(opts['model_directory']),
mode=0o750,
exist_ok=True)
os.makedirs(os.path.abspath(opts['tensor_directory']),
mode=0o750,
exist_ok=True)
code_gen = CodeGenerator(G, DefaultNamingConvension(G), opts)
if args.template_file:
code_template = dynamic_template(args.template_file)
else:
code_template = default_template
write_template(G, code_gen, opts['model_directory'], opts['model_file'],
code_template, "model")
if G.has_expressions:
write_template(G, code_gen, opts['model_directory'],
opts['basic_kernel_header_file'],
basic_kernel_header_template, "kernel headers")
write_template(G, code_gen, opts['model_directory'],
opts['basic_kernel_source_file'],
basic_kernel_source_template, "kernel source")
if args.header_file:
with open(os.path.join(opts['model_directory'], args.header_file),
"w") as output_fp:
output_fp.write(header_template(G, code_generator=code_gen))
if not args.dont_dump_tensors:
LOG.info("Writing constants to %s", opts['model_directory'])
code_gen.write_constants()
def do_gen(self, args):
"""
Generate AutoTiler model C code and optionally dump tensors. If no destination file is
given the generated code will be outputed to the screen. Check the 'set' command for
settings related to code generation."""
self._check_graph()
self._check_quantized()
self._check_adjusted()
if args.checksums:
input_args = self._get_input_args(None)
LOG.info("input file %s", args.checksums)
data = import_data(args.checksums, **input_args)
executer = GraphExecuter(self.G, qrecs=self.G.quantization)
executer.execute([data], qmode=QuantizationMode.all())
self.settings['checksum_file'] = args.checksums
self.settings['generate_checksums'] = True
if args.tensor_directory:
self.settings['tensor_directory'] = args.tensor_directory
if args.model_directory:
self.settings['model_directory'] = args.model_directory
self.settings['basic_kernel_source_file'] = args.basic_kernel_source_file
self.settings['basic_kernel_header_file'] = args.basic_kernel_header_file
code_gen = CodeGenerator(self.G, DefaultNamingConvension(self.G), self.settings)
if self.settings['template_file']:
code_template = dynamic_template(self.settings['template_file'])
else:
code_template = default_template
if args.model_file:
with open(os.path.join(self.settings['model_directory'],
args.model_file), "w") as output_fp:
output_fp.write(code_template(self.G, code_generator=code_gen))
if self.G.has_expressions:
with open(os.path.join(self.settings['model_directory'],
args.basic_kernel_source_file), "w") as output_fp:
output_fp.write(basic_kernel_source_template(self.G, code_generator=code_gen))
with open(os.path.join(self.settings['model_directory'],
args.basic_kernel_header_file), "w") as output_fp:
output_fp.write(basic_kernel_header_template(self.G, code_generator=code_gen))
else:
self.ppaged(code_template(self.G, code_generator=code_gen))
if self.G.has_expressions:
self.ppaged(basic_kernel_source_template(self.G, code_generator=code_gen))
self.ppaged(basic_kernel_header_template(self.G, code_generator=code_gen))
if args.output_tensors:
code_gen.write_constants()
if args.header_file:
with open(os.path.join(self.settings['model_directory'], args.header_file), "w") as output_fp:
output_fp.write(header_template(self.G, code_generator=code_gen))
def generate_code(args):
LOG.propagate = False
handler = GeneratorShellLogHandler()
formatter = logging.Formatter('%(module)s - %(message)s')
handler.setFormatter(formatter)
LOG.addHandler(handler)
if args.log_level:
LOG.setLevel(args.log_level.upper())
else:
LOG.setLevel('WARN')
LOG.info("Loading %s", args.graph_file)
G, opts = load_state(args.graph_file, return_extra=True)
if args.model_file:
opts['model_file'] = args.model_file
if args.model_directory:
opts['model_directory'] = args.model_directory
if args.tensor_directory:
opts['tensor_directory'] = args.tensor_directory
os.makedirs(os.path.abspath(opts['model_directory']),
mode=0o750,
exist_ok=True)
os.makedirs(os.path.abspath(opts['tensor_directory']),
mode=0o750,
exist_ok=True)
model_path = os.path.join(opts['model_directory'], opts['model_file'])
LOG.info("Saving model to %s", model_path)
code_gen = CodeGenerator(G, DefaultNamingConvension(G), opts)
if args.template_file:
code_template = dynamic_template(args.template_file)
else:
code_template = default_template
model = code_template(G, code_generator=code_gen)
if not model:
LOG.error("error generating model code")
sys.exit(1)
with open(model_path, "w") as output_fp:
output_fp.write(model)
if args.header_file:
with open(os.path.join(opts['model_directory'], args.header_file),
"w") as output_fp:
output_fp.write(header_template(G, code_generator=code_gen))
if not args.dont_dump_tensors:
LOG.info("Writing constants to %s", opts['model_directory'])
code_gen.write_constants()