AttributeError: 'tuple' object has no attribute 'log_softmax'
while trying to finetune inception_V3 for my own dataset by changing the last fc layer like
last_layer =nn.Linear(n_inputs, len(classes))
inception_v3.fc = last_layer
after that when I train it got this error on this position
# on training loop
output = inception_v3(data)
# calculate the batch loss
loss = criterion(output, target)
Error is
AttributeError: 'tuple' object has no attribute 'log_softmax'
python deep-learning pytorch
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
add a comment |
while trying to finetune inception_V3 for my own dataset by changing the last fc layer like
last_layer =nn.Linear(n_inputs, len(classes))
inception_v3.fc = last_layer
after that when I train it got this error on this position
# on training loop
output = inception_v3(data)
# calculate the batch loss
loss = criterion(output, target)
Error is
AttributeError: 'tuple' object has no attribute 'log_softmax'
python deep-learning pytorch
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
add a comment |
while trying to finetune inception_V3 for my own dataset by changing the last fc layer like
last_layer =nn.Linear(n_inputs, len(classes))
inception_v3.fc = last_layer
after that when I train it got this error on this position
# on training loop
output = inception_v3(data)
# calculate the batch loss
loss = criterion(output, target)
Error is
AttributeError: 'tuple' object has no attribute 'log_softmax'
python deep-learning pytorch
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
while trying to finetune inception_V3 for my own dataset by changing the last fc layer like
last_layer =nn.Linear(n_inputs, len(classes))
inception_v3.fc = last_layer
after that when I train it got this error on this position
# on training loop
output = inception_v3(data)
# calculate the batch loss
loss = criterion(output, target)
Error is
AttributeError: 'tuple' object has no attribute 'log_softmax'
python deep-learning pytorch
python deep-learning pytorch
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
asked Nov 26 '18 at 7:18
Israel AbebeIsrael Abebe
16412
16412
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
This is a well known problem.
Try one the following solutions:
disable aux_logits when the model is created here by also passing
aux_logits=Falseto the inception_v3 function.edit your train function to accept and unpack the returned tuple to be something like:
output, aux = model(input_var)
Check the following link for more info.
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
3
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
This is a well known problem.
Try one the following solutions:
disable aux_logits when the model is created here by also passing
aux_logits=Falseto the inception_v3 function.edit your train function to accept and unpack the returned tuple to be something like:
output, aux = model(input_var)
Check the following link for more info.
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
3
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
add a comment |
This is a well known problem.
Try one the following solutions:
disable aux_logits when the model is created here by also passing
aux_logits=Falseto the inception_v3 function.edit your train function to accept and unpack the returned tuple to be something like:
output, aux = model(input_var)
Check the following link for more info.
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
3
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
add a comment |
This is a well known problem.
Try one the following solutions:
disable aux_logits when the model is created here by also passing
aux_logits=Falseto the inception_v3 function.edit your train function to accept and unpack the returned tuple to be something like:
output, aux = model(input_var)
Check the following link for more info.
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
This is a well known problem.
Try one the following solutions:
disable aux_logits when the model is created here by also passing
aux_logits=Falseto the inception_v3 function.edit your train function to accept and unpack the returned tuple to be something like:
output, aux = model(input_var)
Check the following link for more info.
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
answered Nov 26 '18 at 7:48
kHarshitkHarshit
79211017
79211017
3
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
add a comment |
3
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
3
3
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
solved by doing inception_v3 = models.inception_v3(pretrained=True) inception_v3.aux_logits=False
– Israel Abebe
Nov 26 '18 at 7:50
add a comment |
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