def main(): """Read the configuration and run the network""" args = parse_args() # Heaps are sized for the j11_v2 network. Changing the network will # require updating network_heap_size and param_heap_size config_file = '../test/testvecs/config/infer/tidl_config_j11_v2.txt' configuration = Configuration() configuration.read_from_file(config_file) configuration.enable_api_trace = False configuration.num_frames = args.num_frames # Heap sizes for this network determined using Configuration.showHeapStats configuration.param_heap_size = (3 << 20) configuration.network_heap_size = (20 << 20) num_dsp = Executor.get_num_devices(DeviceType.DSP) num_eve = Executor.get_num_devices(DeviceType.EVE) if num_dsp == 0 or num_eve == 0: print('This example requires EVEs and DSPs.') return enable_time_stamps("2eo_opt_timestamp.log", 16) run(num_eve, num_dsp, configuration)
def main(): """Read the configuration and run the network""" args = parse_args() config_file = '../test/testvecs/config/infer/tidl_config_mnist_lenet.txt' labels_file = '../test/testvecs/input/digits10_labels_10x1.y' configuration = Configuration() configuration.read_from_file(config_file) num_eve = Executor.get_num_devices(DeviceType.EVE) num_dsp = 0 if num_eve == 0: print('MNIST network currently supported only on EVE') return run(num_eve, num_dsp, configuration, labels_file) return
def main(): """Read the configuration and run the network""" args = parse_args() # Heaps are sized for the j11_v2 network. Changing the network will # require updating network_heap_size and param_heap_size config_file = '../test/testvecs/config/infer/tidl_config_j11_v2.txt' configuration = Configuration() configuration.read_from_file(config_file) configuration.enable_api_trace = False configuration.num_frames = args.num_frames num_dsp = Executor.get_num_devices(DeviceType.DSP) num_eve = Executor.get_num_devices(DeviceType.EVE) if num_dsp == 0 and num_eve == 0: print('No TIDL API capable devices available') return enable_time_stamps("1eo_timestamp.log", 16) run(num_eve, num_dsp, configuration) return
def main(): """Read the configuration and run the network""" #logging.basicConfig(level=logging.INFO) args = parse_args() config_file = '../test/testvecs/config/infer/tidl_config_j11_v2.txt' labels_file = '../imagenet/imagenet_objects.json' configuration = Configuration() configuration.read_from_file(config_file) if os.path.isfile(args.input_file): configuration.in_data = args.input_file else: print('Input image {} does not exist'.format(args.input_file)) return print('Input: {}'.format(args.input_file)) num_eve = Executor.get_num_devices(DeviceType.EVE) num_dsp = Executor.get_num_devices(DeviceType.DSP) if num_eve == 0 and num_dsp == 0: print('No TIDL API capable devices available') return # use 1 EVE or DSP since input is a single image # If input is a stream of images, feel free to use all EVEs and/or DSPs if num_eve > 0: num_eve = 1 num_dsp = 0 else: num_dsp = 1 run(num_eve, num_dsp, configuration, labels_file) return
def main(): """ Parse arguments, read configuration and run network""" parser = argparse.ArgumentParser( description='Dump output of each network layer to file.') parser.add_argument( '-c', '--config_file', default='../test/testvecs/config/infer/tidl_config_j11_v2.txt', help='Path to TIDL config file') args = parser.parse_args() # Run network for 1 frame since we interested in intermediate layer outputs num_frames = 1 # Read configuration from file configuration = Configuration() configuration.read_from_file(args.config_file) configuration.enable_layer_dump = True configuration.num_frames = num_frames num_dsp = Executor.get_num_devices(DeviceType.DSP) num_eve = Executor.get_num_devices(DeviceType.EVE) if num_dsp == 0 and num_eve == 0: print('No TIDL API capable devices available') return if num_eve > 0: device_type = DeviceType.EVE else: device_type = DeviceType.DSP # Since we are dumping layer outputs, just run on one device run(device_type, 1, configuration)