Closed ankitsharma285 closed 7 years ago
Have you checked your keras version?
Consider upgrading as the API call has been changed.
sudo pip install --upgrade keras
@ramanb25: I did the same few hours back. The issue got resolved. Thank you for your suggestion.
I have the same problem as you, could you tell me how to solve this issue? Thanks
@ramanb25 Where do I type that command? I'm using a Jupyter notebook on AWS. In my shell, I shut down the notebook in order to access my ubuntu command line (while ssh'ed into the AWS server) and typed that line, but it said "sudo: pip: command not found". Thanks.
x1 = Conv2D(16, (4, 4), strides=(2, 2), activation='relu')(input_1) TypeError: init() takes at least 4 arguments (4 given) This is the error I'm getting, I tried upgrading keras and tensorflow versions but nothing seems to be effective. Please give me some solution
@SabariRaaj Me too!Could you tell me how to solve this issue?
@SabariRaaj Me too!Could you tell me how to solve this issue?
@brotheryun Bro just use the following versions, keras 2.1.5 and tensorflow 1.5.0. only these versions matched perfectly and solved my issue. These versions are for python 3.
I am learning to use Keras's Functional API . I tried running one of code snippet (ex: inception module ) from the documentation (https://keras.io/getting-started/functional-api-guide/). I get the above mentioned error. I tried running other code snippets as well from the documentation. I get same error for each one.
Inception Module code snippet from the docs:
from keras.layers import Conv2D, MaxPooling2D, Input
input_img = Input(shape=(256, 256,3))
tower_1 = Conv2D(64, (1, 1), padding='same', activation='relu')(input_img) tower_1 = Conv2D(64, (3, 3), padding='same', activation='relu')(tower_1)
tower_2 = Conv2D(64, (1, 1), padding='same', activation='relu')(input_img) tower_2 = Conv2D(64, (5, 5), padding='same', activation='relu')(tower_2)
tower_3 = MaxPooling2D((3, 3), strides=(1, 1), padding='same')(input_img) tower_3 = Conv2D(64, (1, 1), padding='same', activation='relu')(tower_3)
output = keras.layers.concatenate([tower_1, tower_2, tower_3], axis=1)
I am trying to use Conv2D as the first layer in functional API setting. Can anyone please provide me some suggestion on how to resolve this issue?
Thank you.
Ankit Sharma.