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Hi Marc,
I run the caffe2keras function to convert resNext50, but I got the error message as error1, the x is a list instead of a keras tensor, actually it's a structure like [tensor], and if I change the keras backend code to fit this (I change the 492 as shape = x[0].get_shape()), it will get to error2, which still caused by the list type.
Best,
Lele
error1:
(keras_env) lele@istiophorus:~/visualdx_test/keras/keras/caffe$ python caffe2keras.py -load_path /home/lele/visualdx_test/code_resnext -prototxt 'template.prototxt' -caffemodel 'resnext50.caffemodel'
Using TensorFlow backend.
Converting model...
CREATING MODEL
Traceback (most recent call last):
File "caffe2keras.py", line 46, in
main(args)
File "caffe2keras.py", line 34, in main
model = convert.caffe_to_keras(args.load_path+'/'+args.prototxt, args.load_path+'/'+args.caffemodel, debug=args.debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 53, in caffe_to_keras
debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 369, in create_model
net_node[layer_nb] = BatchNormalization(epsilon=epsilon, axis=axis, name=name)(input_layers)
File "/home/lele/visualdx_test/keras/keras/engine/topology.py", line 596, in call
output = self.call(inputs, **kwargs)
File "/home/lele/visualdx_test/keras/keras/layers/normalization.py", line 212, in call
input_shape = K.int_shape(inputs)
File "/home/lele/visualdx_test/keras/keras/backend/tensorflow_backend.py", line 492, in int_shape
shape = x.get_shape()
AttributeError: 'list' object has no attribute 'get_shape'
error2:
(keras_env) lele@istiophorus:~/visualdx_test/keras/keras/caffe$ python caffe2keras.py -load_path /home/lele/visualdx_test/code_resnext -prototxt 'template.prototxt' -caffemodel 'resnext50.caffemodel'
Using TensorFlow backend.
Converting model...
CREATING MODEL
Traceback (most recent call last):
File "caffe2keras.py", line 46, in
main(args)
File "caffe2keras.py", line 34, in main
model = convert.caffe_to_keras(args.load_path+'/'+args.prototxt, args.load_path+'/'+args.caffemodel, debug=args.debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 53, in caffe_to_keras
debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 369, in create_model
net_node[layer_nb] = BatchNormalization(epsilon=epsilon, axis=axis, name=name)(input_layers)
File "/home/lele/visualdx_test/keras/keras/engine/topology.py", line 596, in call
output = self.call(inputs, **kwargs)
File "/home/lele/visualdx_test/keras/keras/layers/normalization.py", line 262, in call
epsilon=self.epsilon)
File "/home/lele/visualdx_test/keras/keras/backend/tensorflow_backend.py", line 1653, in normalize_batch_in_training
shift=None, name=None, keep_dims=False)
File "/home/lele/keras_env/local/lib/python2.7/site-packages/tensorflow/python/ops/nn_impl.py", line 634, in moments
y = math_ops.cast(x, dtypes.float32) if x.dtype == dtypes.float16 else x
AttributeError: 'list' object has no attribute 'dtype'
The text was updated successfully, but these errors were encountered:
Hi Marc,
I run the caffe2keras function to convert resNext50, but I got the error message as error1, the x is a list instead of a keras tensor, actually it's a structure like [tensor], and if I change the keras backend code to fit this (I change the 492 as shape = x[0].get_shape()), it will get to error2, which still caused by the list type.
Best,
Lele
error1:
(keras_env) lele@istiophorus:~/visualdx_test/keras/keras/caffe$ python caffe2keras.py -load_path /home/lele/visualdx_test/code_resnext -prototxt 'template.prototxt' -caffemodel 'resnext50.caffemodel'
Using TensorFlow backend.
Converting model...
CREATING MODEL
Traceback (most recent call last):
File "caffe2keras.py", line 46, in
main(args)
File "caffe2keras.py", line 34, in main
model = convert.caffe_to_keras(args.load_path+'/'+args.prototxt, args.load_path+'/'+args.caffemodel, debug=args.debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 53, in caffe_to_keras
debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 369, in create_model
net_node[layer_nb] = BatchNormalization(epsilon=epsilon, axis=axis, name=name)(input_layers)
File "/home/lele/visualdx_test/keras/keras/engine/topology.py", line 596, in call
output = self.call(inputs, **kwargs)
File "/home/lele/visualdx_test/keras/keras/layers/normalization.py", line 212, in call
input_shape = K.int_shape(inputs)
File "/home/lele/visualdx_test/keras/keras/backend/tensorflow_backend.py", line 492, in int_shape
shape = x.get_shape()
AttributeError: 'list' object has no attribute 'get_shape'
error2:
(keras_env) lele@istiophorus:~/visualdx_test/keras/keras/caffe$ python caffe2keras.py -load_path /home/lele/visualdx_test/code_resnext -prototxt 'template.prototxt' -caffemodel 'resnext50.caffemodel'
Using TensorFlow backend.
Converting model...
CREATING MODEL
Traceback (most recent call last):
File "caffe2keras.py", line 46, in
main(args)
File "caffe2keras.py", line 34, in main
model = convert.caffe_to_keras(args.load_path+'/'+args.prototxt, args.load_path+'/'+args.caffemodel, debug=args.debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 53, in caffe_to_keras
debug)
File "/home/lele/visualdx_test/keras/keras/caffe/convert.py", line 369, in create_model
net_node[layer_nb] = BatchNormalization(epsilon=epsilon, axis=axis, name=name)(input_layers)
File "/home/lele/visualdx_test/keras/keras/engine/topology.py", line 596, in call
output = self.call(inputs, **kwargs)
File "/home/lele/visualdx_test/keras/keras/layers/normalization.py", line 262, in call
epsilon=self.epsilon)
File "/home/lele/visualdx_test/keras/keras/backend/tensorflow_backend.py", line 1653, in normalize_batch_in_training
shift=None, name=None, keep_dims=False)
File "/home/lele/keras_env/local/lib/python2.7/site-packages/tensorflow/python/ops/nn_impl.py", line 634, in moments
y = math_ops.cast(x, dtypes.float32) if x.dtype == dtypes.float16 else x
AttributeError: 'list' object has no attribute 'dtype'
The text was updated successfully, but these errors were encountered: