How to print tensor shape in Lambda layer function?
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0
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I have defined a Lambda
layer that passes tensors to a function attention
. I want to print the shapes of the intermediate tensors in attention
. I have tried print(K.int_shape(ques))
but that doesn't print the shapes. I am fine with both static and dynamic shapes.
layer = Lambda(attention, attention_shape)
def attention(tensors):
img = tensors[0] # (7,7,512)
ques = tensors[1] # (512,)
print('attention: img shape: '+ str( K.int_shape(img) ) )
print('attention: ques shape: '+ str( K.int_shape(ques) ) )
ques = RepeatVector(49)(ques)
ques = Reshape((7, 7, -1))(ques) # (7,7,512)
print('attention: ques shape 2: '+ str( K.int_shape(ques) ) )
return ques
python-3.x tensorflow keras tensor
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up vote
0
down vote
favorite
I have defined a Lambda
layer that passes tensors to a function attention
. I want to print the shapes of the intermediate tensors in attention
. I have tried print(K.int_shape(ques))
but that doesn't print the shapes. I am fine with both static and dynamic shapes.
layer = Lambda(attention, attention_shape)
def attention(tensors):
img = tensors[0] # (7,7,512)
ques = tensors[1] # (512,)
print('attention: img shape: '+ str( K.int_shape(img) ) )
print('attention: ques shape: '+ str( K.int_shape(ques) ) )
ques = RepeatVector(49)(ques)
ques = Reshape((7, 7, -1))(ques) # (7,7,512)
print('attention: ques shape 2: '+ str( K.int_shape(ques) ) )
return ques
python-3.x tensorflow keras tensor
You want the shapes to be printed when you first construct the model or during training? When you first construct the model the shapes would be printed.
– today
Nov 22 at 20:14
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have defined a Lambda
layer that passes tensors to a function attention
. I want to print the shapes of the intermediate tensors in attention
. I have tried print(K.int_shape(ques))
but that doesn't print the shapes. I am fine with both static and dynamic shapes.
layer = Lambda(attention, attention_shape)
def attention(tensors):
img = tensors[0] # (7,7,512)
ques = tensors[1] # (512,)
print('attention: img shape: '+ str( K.int_shape(img) ) )
print('attention: ques shape: '+ str( K.int_shape(ques) ) )
ques = RepeatVector(49)(ques)
ques = Reshape((7, 7, -1))(ques) # (7,7,512)
print('attention: ques shape 2: '+ str( K.int_shape(ques) ) )
return ques
python-3.x tensorflow keras tensor
I have defined a Lambda
layer that passes tensors to a function attention
. I want to print the shapes of the intermediate tensors in attention
. I have tried print(K.int_shape(ques))
but that doesn't print the shapes. I am fine with both static and dynamic shapes.
layer = Lambda(attention, attention_shape)
def attention(tensors):
img = tensors[0] # (7,7,512)
ques = tensors[1] # (512,)
print('attention: img shape: '+ str( K.int_shape(img) ) )
print('attention: ques shape: '+ str( K.int_shape(ques) ) )
ques = RepeatVector(49)(ques)
ques = Reshape((7, 7, -1))(ques) # (7,7,512)
print('attention: ques shape 2: '+ str( K.int_shape(ques) ) )
return ques
python-3.x tensorflow keras tensor
python-3.x tensorflow keras tensor
asked Nov 22 at 16:51
Nirvan Anjirbag
357416
357416
You want the shapes to be printed when you first construct the model or during training? When you first construct the model the shapes would be printed.
– today
Nov 22 at 20:14
add a comment |
You want the shapes to be printed when you first construct the model or during training? When you first construct the model the shapes would be printed.
– today
Nov 22 at 20:14
You want the shapes to be printed when you first construct the model or during training? When you first construct the model the shapes would be printed.
– today
Nov 22 at 20:14
You want the shapes to be printed when you first construct the model or during training? When you first construct the model the shapes would be printed.
– today
Nov 22 at 20:14
add a comment |
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You want the shapes to be printed when you first construct the model or during training? When you first construct the model the shapes would be printed.
– today
Nov 22 at 20:14