Keras: IndexError: tuple index out of range - Conv2D
I'm new in Keras and Tensorflow. I'm trying to run some specific code based on Keras and Tensorflow. In that code, I prepared dataset from tfrecordes files and reshape it with tf.reshape(image, [32, 32, 3]), in my model, I need to apply a Conv2D layer on this image output, I using Keras, in my code below:
# Image
x = k.layers.Input(shape=input_shape,tensor=img)
# ReLU Conv1
conv1 = k.layers.Conv2D(filters = 256, kernel_size = 9, strides=1,padding='valid', activation='relu', name='conv1')(x)
the problem is that, when I run the code, I got this error:
self.kernel_size[i],
IndexError: tuple index out of range
so, after many searches, I found that this error may be fixed by change Keras ver from 2.2 to 1.2.
I do that but actually, I must change all of my code, do anybody how can fix this error just in Keras 2.2, without using Karas 1.2?
python tensorflow keras
asked Nov 20 at 10:53
Vahid
15
add a comment |
I'm new in Keras and Tensorflow. I'm trying to run some specific code based on Keras and Tensorflow. In that code, I prepared dataset from tfrecordes files and reshape it with tf.reshape(image, [32, 32, 3]), in my model, I need to apply a Conv2D layer on this image output, I using Keras, in my code below:
# Image
x = k.layers.Input(shape=input_shape,tensor=img)
# ReLU Conv1
conv1 = k.layers.Conv2D(filters = 256, kernel_size = 9, strides=1,padding='valid', activation='relu', name='conv1')(x)
the problem is that, when I run the code, I got this error:
self.kernel_size[i],
IndexError: tuple index out of range
so, after many searches, I found that this error may be fixed by change Keras ver from 2.2 to 1.2.
I do that but actually, I must change all of my code, do anybody how can fix this error just in Keras 2.2, without using Karas 1.2?
python tensorflow keras
asked Nov 20 at 10:53
Vahid
15
add a comment |
I'm new in Keras and Tensorflow. I'm trying to run some specific code based on Keras and Tensorflow. In that code, I prepared dataset from tfrecordes files and reshape it with tf.reshape(image, [32, 32, 3]), in my model, I need to apply a Conv2D layer on this image output, I using Keras, in my code below:
# Image
x = k.layers.Input(shape=input_shape,tensor=img)
# ReLU Conv1
conv1 = k.layers.Conv2D(filters = 256, kernel_size = 9, strides=1,padding='valid', activation='relu', name='conv1')(x)
the problem is that, when I run the code, I got this error:
self.kernel_size[i],
IndexError: tuple index out of range
so, after many searches, I found that this error may be fixed by change Keras ver from 2.2 to 1.2.
I do that but actually, I must change all of my code, do anybody how can fix this error just in Keras 2.2, without using Karas 1.2?
python tensorflow keras
asked Nov 20 at 10:53
Vahid
15
I'm new in Keras and Tensorflow. I'm trying to run some specific code based on Keras and Tensorflow. In that code, I prepared dataset from tfrecordes files and reshape it with tf.reshape(image, [32, 32, 3]), in my model, I need to apply a Conv2D layer on this image output, I using Keras, in my code below:
# Image
x = k.layers.Input(shape=input_shape,tensor=img)
# ReLU Conv1
conv1 = k.layers.Conv2D(filters = 256, kernel_size = 9, strides=1,padding='valid', activation='relu', name='conv1')(x)
the problem is that, when I run the code, I got this error:
self.kernel_size[i],
IndexError: tuple index out of range
so, after many searches, I found that this error may be fixed by change Keras ver from 2.2 to 1.2.
I do that but actually, I must change all of my code, do anybody how can fix this error just in Keras 2.2, without using Karas 1.2?
python tensorflow keras
python tensorflow keras
asked Nov 20 at 10:53
Vahid
15
asked Nov 20 at 10:53
Vahid
15
asked Nov 20 at 10:53
Vahid
15
asked Nov 20 at 10:53
Vahid
15
asked Nov 20 at 10:53
Vahid
15
15
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
I think you need a 9 * 9 kernel. Change kernel_size=9 to kernel_size=( 9 , 9 )
Edited code line :
conv1 = k.layers.Conv2D(filters = 256, kernel_size = ( 9 , 9 ), strides=1,padding='valid', activation='relu', name='conv1')(x)
answered Nov 20 at 11:06
Shubham Panchal
38419
this change has not any effect!
– Vahid
Nov 20 at 12:00
add a comment |
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1 Answer
1
active
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
I think you need a 9 * 9 kernel. Change kernel_size=9 to kernel_size=( 9 , 9 )
Edited code line :
conv1 = k.layers.Conv2D(filters = 256, kernel_size = ( 9 , 9 ), strides=1,padding='valid', activation='relu', name='conv1')(x)
answered Nov 20 at 11:06
Shubham Panchal
38419
this change has not any effect!
– Vahid
Nov 20 at 12:00
add a comment |
I think you need a 9 * 9 kernel. Change kernel_size=9 to kernel_size=( 9 , 9 )
Edited code line :
conv1 = k.layers.Conv2D(filters = 256, kernel_size = ( 9 , 9 ), strides=1,padding='valid', activation='relu', name='conv1')(x)
answered Nov 20 at 11:06
Shubham Panchal
38419
this change has not any effect!
– Vahid
Nov 20 at 12:00
add a comment |
I think you need a 9 * 9 kernel. Change kernel_size=9 to kernel_size=( 9 , 9 )
Edited code line :
conv1 = k.layers.Conv2D(filters = 256, kernel_size = ( 9 , 9 ), strides=1,padding='valid', activation='relu', name='conv1')(x)
answered Nov 20 at 11:06
Shubham Panchal
38419
I think you need a 9 * 9 kernel. Change kernel_size=9 to kernel_size=( 9 , 9 )
Edited code line :
conv1 = k.layers.Conv2D(filters = 256, kernel_size = ( 9 , 9 ), strides=1,padding='valid', activation='relu', name='conv1')(x)
answered Nov 20 at 11:06
Shubham Panchal
38419
answered Nov 20 at 11:06
Shubham Panchal
38419
answered Nov 20 at 11:06
Shubham Panchal
38419
answered Nov 20 at 11:06
Shubham Panchal
38419
38419
this change has not any effect!
– Vahid
Nov 20 at 12:00
add a comment |
this change has not any effect!
– Vahid
Nov 20 at 12:00
this change has not any effect!
– Vahid
Nov 20 at 12:00
this change has not any effect!
– Vahid
Nov 20 at 12:00
add a comment |
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