keras-yolo3: problem with mutil GPU in keras

when i try to use model = multi_gpu_model(model,gpus=3) in my data,there is a error occured:

tensorflow.python.framework.errors_impl.InvalidArgumentError: Can’t concatenate scalars (use tf.stack instead) for ‘yolo_loss_1/concat’ (op: ‘ConcatV2’) with input shapes: [], [], [], [].

my enviroment is tensorflow-1.8 gpu, keras 2.20,titan xp please help me fix it！ thx！

About this issue

Original URL
State: open
Created 6 years ago
Comments: 28

Most upvoted comments

Although I don’t think it is the best method, this way it worked. Please rewrite it as follows.

https://github.com/qqwweee/keras-yolo3/blob/da7d756b0e47b979e701f0131ba7074ea138add8/yolo3/model.py#L412

return K.expand_dims(loss, axis=0)

https://github.com/qqwweee/keras-yolo3/blob/da7d756b0e47b979e701f0131ba7074ea138add8/train.py#L53-L55

https://github.com/qqwweee/keras-yolo3/blob/da7d756b0e47b979e701f0131ba7074ea138add8/train.py#L73

'yolo_loss': lambda y_true, y_pred: y_pred[0]

+24

nakasu on Jul 30, 2018

add multi_gpu_model on yolo_body (before yolo_loss) may work

    model_body = tiny_yolo_body(image_input, num_anchors//2, num_classes)
    if gpus > 1:
        model_body = multi_gpu_model(model_body, gpus=gpus)

+17

power630 on Oct 17, 2018

I have pushed the useable code for training multi_gpu_model for YOLOv3 with multiple backbones, please visit https://github.com/anvien/Multi-YOLOv3

zhanganguo on Jul 16, 2019