keras blog上有详细的帖子
但是在编译代码时,我得到的错误如下:
Using TensorFlow backend.
Traceback (most recent call last):
File "visulaize_cifar.py", line 24, in <module>
model.add(MaxPooling2D((2, 2), strides=(2, 2)))
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/models.py", line 332, in add
output_tensor = layer(self.outputs[0])
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/engine/topology.py", line 572, in __call__
self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/engine/topology.py", line 635, in add_inbound_node
Node.create_node(self, inbound_layers, node_indices, tensor_indices)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/engine/topology.py", line 166, in create_node
output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/layers/pooling.py", line 160, in call
dim_ordering=self.dim_ordering)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/layers/pooling.py", line 210, in _pooling_function
pool_mode='max')
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 2866, in pool2d
x = tf.nn.max_pool(x, pool_size, strides, padding=padding)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/ops/nn_ops.py", line 1617, in max_pool
name=name)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 1598, in _max_pool
data_format=data_format, name=name)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
op_def=op_def)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2242, in create_op
set_shapes_for_outputs(ret)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1617, in set_shapes_for_outputs
shapes = shape_func(op)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1568, in call_with_requiring
return call_cpp_shape_fn(op, require_shape_fn=True)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 610, in call_cpp_shape_fn
debug_python_shape_fn, require_shape_fn)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 675, in _call_cpp_shape_fn_impl
raise ValueError(err.message)
ValueError: Negative dimension size caused by subtracting 2 from 1 for 'MaxPool_1' (op: 'MaxPool') with input shapes: [1,1,64,128].
当我设置dim_ordering='th'
时,会发生此错误
但是当我使用tensorflow后端时,维度排序应该是dim_ordering='tf'
即使在将dim_ordering设置为&#39;后,我在loading weights
vgg16_weights.h5
时收到错误,如下所示:
Traceback (most recent call last):
File "visulaize_cifar.py", line 67, in <module>
model.layers[k].set_weights(weights)
File "/home/dude_perf3ct/.local/lib/python2.7/site-packages/keras/engine/topology.py", line 985, in set_weights
'provided weight shape ' + str(w.shape))
ValueError: Layer weight shape (3, 3, 128, 64) not compatible with provided weight shape (64, 3, 3, 3).
详见this post关于&#39;&#39;并且&#39;。上述错误意味着图层权重在&#39; tf&#39; (但我将其设置为“以避免第一次出错”)并在“第三次”中提供了重量形状。排序。
What seems to be the error
?
答案 0 :(得分:0)
回答这个问题非常简单。因为,我使用tensorflow
作为后端。所以,要转换我插入的行
if K.backend()=='tensorflow':
K.set_image_dim_ordering("th")
在from keras import backend as K
之后
这是因为vgg16_weights.h5
具有th
格式,还有cifar10.load_data()
。