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 gen_project(G, settings, project_folder, script_commands, overwrite=False, performance=False, quantized=False, test_results=False, save_inputs=False, input_file=None, input_args=None, gen_atproject=False, dump_tensors=False, input_tensors=None, tolerance=0.0): settings = deepcopy(settings) settings['graph_monitor_cycles'] = True settings['graph_produce_node_names'] = True settings['graph_produce_operinfos'] = True code_gen = CodeGenerator(G, DefaultNamingConvension(G), settings) if not os.path.exists(project_folder): os.mkdir(project_folder) qoutputs = None if test_results: np.random.seed(12345) finput_tensors = [] input_tensors = [] for i, node in enumerate(G.input_nodes()): out_q = G.quantization[NodeId(node)].out_qs[0] if input_file: file_per_input = glob_input_files(input_file, G.num_inputs)[0] finput = import_data(file_per_input[i], **input_args) else: min_val = out_q.min if not out_q.is_floating else -1.0 max_val = out_q.max if not out_q.is_floating else 1.0 finput = get_rand(node.out_dims[0].shape, low_high=(min_val, max_val)) finput_tensors.append(finput) executer = GraphExecuter(G, qrecs=G.quantization) qoutput_tensors = executer.execute(finput_tensors.copy(), qmode=QuantizationMode.all()) qoutputs = [] for params in G.outputs(): outp = qoutput_tensors[params.step_idx][0] qoutputs.append(outp) for i, params in enumerate(G.input_nodes()): inp = qoutput_tensors[params.step_idx][0] input_tensors.append(inp) if save_inputs: nodeq = G.quantization[NodeId(params, None)].out_qs[0] np.save(os.path.join(project_folder, f"fake_input_{i}.npy"), nodeq.dequantize(inp)) main = os.path.join(project_folder, f"{code_gen.project_name}") main_c = main + '.c' main_h = main + '.h' common_mk = os.path.join(project_folder, "common.mk") nntool_script = os.path.join(project_folder, "nntool_script") if overwrite or not os.path.exists(main_c): with open(os.path.join(project_folder, f"{code_gen.project_name}.c"), "w") as output_fp: output_fp.write( generate_main_appl_template(G, code_gen, input_tensors, qoutputs, tolerance)) if overwrite or not os.path.exists(main_h): with open(os.path.join(project_folder, f"{code_gen.project_name}.h"), "w") as output_fp: output_fp.write(generate_main_appl_header(G, code_gen)) if overwrite or not os.path.exists(common_mk): open_args = parse_last_open(script_commands) open_args = build_last_open_args(open_args) if open_args else "" with open(os.path.join(project_folder, "common.mk"), "w") as output_fp: if gen_atproject: output_fp.write( generate_main_appl_make_atproject(G, code_gen, quantized, 'Model.c')) else: output_fp.write( generate_main_appl_make(G, code_gen, quantized, open_args=open_args)) if overwrite or not os.path.exists(nntool_script): with open(nntool_script, 'w') as fp: # NOTE - gen_template_project is excluded so that tests work. Normally it will not be in the # history. fp.writelines(process_script(script_commands)) # always add performance since the main template uses it for setting in [ 'set graph_produce_node_names true', 'set graph_produce_operinfos true', 'set graph_monitor_cycles true' ]: fp.write(f'{setting}\n') if dump_tensors: fp.write('set graph_dump_tensor 7\n') if script_commands[-1] != "save_state": fp.write('save_state\n') if gen_atproject: code_gen = CodeGenerator(G, DefaultNamingConvension(G), settings) with open(os.path.join(project_folder, 'Model.c'), "w") as output_fp: output_fp.write(default_template(G, code_generator=code_gen)) if G.has_expressions: with open(os.path.join(project_folder, "Expression_Kernels.c"), "w") as output_fp: output_fp.write( basic_kernel_source_template(G, code_generator=code_gen)) with open(os.path.join(project_folder, "Expression_Kernels.h"), "w") as output_fp: output_fp.write( basic_kernel_header_template(G, code_generator=code_gen)) code_gen.write_constants(tensor_directory=project_folder) ignore_function = None if overwrite else skip_existing_files( project_folder) shutil.copytree(os.path.join(os.environ.get("NNTOOL_PATH"), 'generation/project_template'), project_folder, dirs_exist_ok=True, ignore=ignore_function) if not gen_atproject: try: shutil.copy( G.graph_identity.filename, os.path.join(project_folder, os.path.split(G.graph_identity.filename)[1])) except shutil.SameFileError: pass