Traceback (most recent call last):


 "<string>", line 1, in <module>
TypeError: 'exceptions.ValueError' object is not callable

Traceback (most recent call last):

 "finetune_mnist.py", line 34, in <module>
net = MyNet({'data': images})

 "/home/username/Documents/caffe-tensorflow/examples/mnist/kaffe/tensorflow/network.py", line 43, in **init**
self.setup()

 "/home/username/Documents/caffe-tensorflow/examples/mnist/mynet.py", line 10, in setup
.conv(5, 5, 256, 1, 1, group=2, name='conv2')

 "/home/username/Documents/caffe-tensorflow/examples/mnist/kaffe/tensorflow/network.py", line 21, in layer_decorated
layer_output = op(self, layer_input, _args, *_kwargs)

 "/home/username/Documents/caffe-tensorflow/examples/mnist/kaffe/tensorflow/network.py", line 131, in conv
output_groups = [convolve(i, k) for i, k in zip(input_groups, kernel_groups)]

 "/home/username/Documents/caffe-tensorflow/examples/mnist/kaffe/tensorflow/network.py", line 121, in <lambda>
convolve = lambda i, k: tf.nn.conv2d(i, k, [1, s_h, s_w, 1], padding=padding)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 394, in conv2d
data_format=data_format, name=name)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 704, in apply_op
op_def=op_def)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2262, in create_op
set_shapes_for_outputs(ret)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1702, in set_shapes_for_outputs
shapes = shape_func(op)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/common_shapes.py", line 246, in conv2d_shape
padding)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/common_shapes.py", line 184, in get2d_conv_output_size
(row_stride, col_stride), padding_type)

 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/common_shapes.py", line 149, in get_conv_output_size
"Filter: %r Input: %r" % (filter_size, input_size))ValueError: Filter must not be larger than the input: Filter: (5, 5) Input: (2, 2)