我只是试着用自定义张量的形状（1,18,18,1）对张量进行卷积
kernel_x = K.variable([[-1, -2, -1], [0, 0, 0], [1, 2, 1]])
我用这个：
y_true_boundary_x = K.conv2d(y_true, kernel_x, strides=(1,1), padding="same", data_format="channels_last", dilation_rate=(1, 1))
它引发了错误：
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-43-669f14bb3bdc> in <module>()
----> 1 y_true_boundary_x = K.conv2d(y_true, kernel_x, strides=(1,1), padding="same", data_format="channels_last", dilation_rate=(1, 1))
/anaconda/lib/python3.6/site-packages/keras/backend/theano_backend.py in conv2d(x, kernel, strides, padding, data_format, dilation_rate)
1899 # Will only work if `kernel` is a shared variable.
1900 kernel_shape = kernel.eval().shape
-> 1901 kernel_shape = _preprocess_conv2d_filter_shape(kernel_shape, data_format)
1902
1903 x = _preprocess_conv2d_input(x, data_format)
/anaconda/lib/python3.6/site-packages/keras/backend/theano_backend.py in _preprocess_conv2d_filter_shape(filter_shape, data_format)
1761 return None
1762 if filter_shape:
-> 1763 filter_shape = (filter_shape[3], filter_shape[2],
1764 filter_shape[0], filter_shape[1])
1765 if filter_shape is not None:
IndexError: tuple index out of range