def test_imagenet_model(model_name, val_data, gpus, batch_size): """test model on imagenet """ logging.info('test %s', model_name) meta_info = get_model_meta_info(model_name) [model_name, mean] = convert_caffe_model(model_name, meta_info) sym, arg_params, aux_params = mx.model.load_checkpoint(model_name, 0) acc = [mx.metric.create('acc'), mx.metric.create('top_k_accuracy', top_k=5)] if isinstance(mean, str): mean_args = {'mean_img':mean} else: mean_args = {'rgb_mean':','.join([str(i) for i in mean])} print(val_data) (speed,) = score(model=(sym, arg_params, aux_params), data_val=val_data, label_name='prob_label', metrics=acc, gpus=gpus, batch_size=batch_size, max_num_examples=500, **mean_args) logging.info('speed : %f image/sec', speed) for a in acc: logging.info(a.get()) assert acc[0].get()[1] > meta_info['top-1-acc'] - 0.3 assert acc[1].get()[1] > meta_info['top-5-acc'] - 0.3
def test_model_weights_and_outputs(model_name, image_url, gpu): """ Run the layer comparison on one of the known caffe models. :param model_name: available models are listed in convert_caffe_modelzoo.py :param image_url: image file or url to run inference on :param gpu: gpu to use, -1 for cpu """ logging.info('test weights and outputs of model: %s', model_name) meta_info = get_model_meta_info(model_name) (prototxt, caffemodel, mean) = download_caffe_model(model_name, meta_info, dst_dir='./model') convert_and_compare_caffe_to_mxnet(image_url, gpu, prototxt, caffemodel, mean, mean_diff_allowed=1e-03, max_diff_allowed=1e-01)
def test_model_weights_and_outputs(model_name, image_url, gpu): """ Run the layer comparison on one of the known caffe models. :param model_name: available models are listed in convert_caffe_modelzoo.py :param image_url: image file or url to run inference on :param gpu: gpu to use, -1 for cpu """ logging.info('test weights and outputs of model: %s', model_name) meta_info = get_model_meta_info(model_name) (prototxt, caffemodel, mean) = download_caffe_model(model_name, meta_info, dst_dir='./model') convert_and_compare_caffe_to_mxnet(image_url, gpu, prototxt, caffemodel, mean, mean_diff_allowed=1e-03, max_diff_allowed=1e-01)