finding the inner product of two 3D tensor in keras custom layer
$begingroup$
in my keras custom layer, i have to find the inner product of two 3D tensors. For example , x=(?,80,150,12) is the input to the layer and the inner product have to be with all the 4 slices of kernel (80,150,12,4), 4 being the slicing dimension. I am trying to do it with K.dot but i am getting dimension mismatch error.The code snippet is-
kernel1_unpacked = tf.unstack(self.kernel1,axis=3)
all_probs =
for t in kernel1_unpacked:
t=K.permute_dimensions(t,[2,0,1])
B3=K.sum(K.dot(x,t),[1,2,3])
B3=K.expand_dims(B3,1)
print(B3)
all_probs.append(B3)
B4=tf.concat(all_probs[:],axis=1)
print(B4)
the output should have dimension (?,4). please help
python keras tensorflow
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
$endgroup$
add a comment |
$begingroup$
in my keras custom layer, i have to find the inner product of two 3D tensors. For example , x=(?,80,150,12) is the input to the layer and the inner product have to be with all the 4 slices of kernel (80,150,12,4), 4 being the slicing dimension. I am trying to do it with K.dot but i am getting dimension mismatch error.The code snippet is-
kernel1_unpacked = tf.unstack(self.kernel1,axis=3)
all_probs =
for t in kernel1_unpacked:
t=K.permute_dimensions(t,[2,0,1])
B3=K.sum(K.dot(x,t),[1,2,3])
B3=K.expand_dims(B3,1)
print(B3)
all_probs.append(B3)
B4=tf.concat(all_probs[:],axis=1)
print(B4)
the output should have dimension (?,4). please help
python keras tensorflow
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
$endgroup$
add a comment |
$begingroup$
in my keras custom layer, i have to find the inner product of two 3D tensors. For example , x=(?,80,150,12) is the input to the layer and the inner product have to be with all the 4 slices of kernel (80,150,12,4), 4 being the slicing dimension. I am trying to do it with K.dot but i am getting dimension mismatch error.The code snippet is-
kernel1_unpacked = tf.unstack(self.kernel1,axis=3)
all_probs =
for t in kernel1_unpacked:
t=K.permute_dimensions(t,[2,0,1])
B3=K.sum(K.dot(x,t),[1,2,3])
B3=K.expand_dims(B3,1)
print(B3)
all_probs.append(B3)
B4=tf.concat(all_probs[:],axis=1)
print(B4)
the output should have dimension (?,4). please help
python keras tensorflow
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
$endgroup$
in my keras custom layer, i have to find the inner product of two 3D tensors. For example , x=(?,80,150,12) is the input to the layer and the inner product have to be with all the 4 slices of kernel (80,150,12,4), 4 being the slicing dimension. I am trying to do it with K.dot but i am getting dimension mismatch error.The code snippet is-
kernel1_unpacked = tf.unstack(self.kernel1,axis=3)
all_probs =
for t in kernel1_unpacked:
t=K.permute_dimensions(t,[2,0,1])
B3=K.sum(K.dot(x,t),[1,2,3])
B3=K.expand_dims(B3,1)
print(B3)
all_probs.append(B3)
B4=tf.concat(all_probs[:],axis=1)
print(B4)
the output should have dimension (?,4). please help
python keras tensorflow
python keras tensorflow
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
asked 10 mins ago
Sandeep PandeySandeep Pandey
11
11
add a comment |
add a comment |
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