Hi, I am sorry to trouble you for my problems.
I downloaded the whole project and try to test your KEGG pre-trained weight with only mouse bulk dataset but there was a error about the shape of the weight matrix.
I added "model.load_weights(model_path,by_name=True)" and found the following information:ValueError: Layer #19 (named "dense_1"), weight <tf.Variable 'dense_1/kernel:0' shape=(512, 512) dtype=float32, numpy=
array( ………………） > has shape (512, 512), but the saved weight has shape (1536, 512).
I wonder if the using of single-cell dataset the key to this problem or maybe your weight is not fit for the code here?
I have tried to trained one with only bulk dataset and it was ok to predict. Well...
It would be greatly appreciated if you could tell me more, thanks.
Hi, I am sorry to trouble you for my problems. I downloaded the whole project and try to test your KEGG pre-trained weight with only mouse bulk dataset but there was a error about the shape of the weight matrix. I added "model.load_weights(model_path,by_name=True)" and found the following information:ValueError: Layer #19 (named "dense_1"), weight <tf.Variable 'dense_1/kernel:0' shape=(512, 512) dtype=float32, numpy= array( ………………） > has shape (512, 512), but the saved weight has shape (1536, 512). I wonder if the using of single-cell dataset the key to this problem or maybe your weight is not fit for the code here? I have tried to trained one with only bulk dataset and it was ok to predict. Well... It would be greatly appreciated if you could tell me more, thanks.