def create_network(name, *args, **kwargs):
if name == "textrcnn":
return textrcnn(*args, **kwargs)
raise NotImplementedError(f"{name} is not implemented in the repo")
set_seed(1)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='textrcnn')
parser.add_argument('--ckpt_path', type=str)
args = parser.parse_args()
context.set_context(mode=context.GRAPH_MODE,
save_graphs=False,
device_target="Ascend")
device_id = int(os.getenv('DEVICE_ID'))
context.set_context(device_id=device_id)
embedding_table = np.loadtxt(
os.path.join(cfg.preprocess_path, "weight.txt")).astype(np.float32)
network = textrcnn(weight=Tensor(embedding_table),
vocab_size=embedding_table.shape[0],
cell=cfg.cell,
batch_size=cfg.batch_size)
loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True)
loss_cb = LossMonitor()
print("============== Starting Testing ==============")
ds_eval = create_dataset(cfg.preprocess_path, cfg.batch_size, False)
param_dict = load_checkpoint(args.ckpt_path)
load_param_into_net(network, param_dict)
network.set_train(False)
model = Model(network, loss, metrics={'acc': Accuracy()}, amp_level='O3')
acc = model.eval(ds_eval, dataset_sink_mode=False)
print("============== Accuracy:{} ==============".format(acc))
def textrcnn_net(*args, **kwargs):
return textrcnn(*args, **kwargs)