def _build_model(model_file, data_format): input_shape = ((None, 28, 28, 1) if data_format == 'NHWC' else (None, 1, 28, 28)) model_def = nn.get_model_config(model_file, input_shape=input_shape, n_classes=10) return nn.make_model(model_def)
def _build_model(model_file, data_format): input_shape = ( (None, 28, 28, 1) if data_format == 'NHWC' else (None, 1, 28, 28) ) model_def = nn.get_model_config( model_file, input_shape=input_shape, n_classes=10) return nn.make_model(model_def)
def _build_model(model_file, data_format, batch_size): input_shape = ( [batch_size, 28, 28, 1] if data_format == 'NHWC' else [batch_size, 1, 28, 28] ) model_def = nn.get_model_config(model_file, input_shape=input_shape) return nn.make_model(model_def)
def _build_model(model_file, input_shape): model_def = nn.get_model_config(model_file, input_shape=input_shape) return nn.make_model(model_def)
def _build_models(model_file): _LG.info('Loading model %s', model_file) model_def = nn.get_model_config(model_file) return nn.make_model(model_def)
def _make_model(config_path, input_shape): config = luchador.nn.get_model_config(config_path, input_shape=input_shape) model_def = config['model'] return nn.make_model(model_def)
def _build_model(model_file, data_format, batch_size): input_shape = ([batch_size, 28, 28, 1] if data_format == 'NHWC' else [batch_size, 1, 28, 28]) model_def = nn.get_model_config(model_file, input_shape=input_shape) return nn.make_model(model_def)
def _build_model(model_file, input_shape, batch_size): model_def = nn.get_model_config( model_file, input_shape=input_shape, batch_size=batch_size, n_classes=10) return nn.make_model(model_def)