parameters: (depth, padding, x)
return_statement: return K.conv2d(x, kernel, strides=(3, 3), padding=padding)
docstring: Perform a conv2d on x with a given padding
docstring_summary: Perform a conv2d on x with a given padding
docstring_tokens: Perform a conv2d on x with a given padding
function: def offset_conv2d_eval(depth, padding, x):
      """Perform a conv2d on x with a given padding"""
      kernel = K.variable(value=np.array([[[[1]] + [[0]] * (depth - 1)]]),
                          dtype='float32')
      return K.conv2d(x, kernel, strides=(3, 3), padding=padding)
function_tokens: def offset_conv2d_eval ( depth , padding , x ) : kernel = K . variable ( value = np . array ( [ [ [ [ 1 ] ] + [ [ 0 ] ] * ( depth - 1 ) ] ] ) , dtype = 'float32' ) return K . conv2d ( x , kernel , strides = ( 3 , 3 ) , padding = padding )