def get(self, id, pk='id', deleted=False):
        try:
            if pk == 'id':
                id = int(id)
            if deleted:
                spec = {pk: id}
            else:
                spec = {pk: id, 'data': {'$exists': 1}}
            fields = {'_id': 0}
            row = self.db.docs.find_one(spec, fields)
        except Exception as e:
            raise DatabaseException(e)
        if row:
            return Document(**row)
        raise NotFoundError('%s %s not found' % (pk, id))
def conv2d_fixed_padding(inputs, filters, kernel_size, strides, data_format,
                         name):
  """Strided 2-D convolution with explicit padding."""
  # The padding is consistent and is based only on `kernel_size`, not on the
  # dimensions of `inputs` (as opposed to using `tf.layers.conv2d` alone).
  if strides > 1:
    inputs = fixed_padding(inputs, kernel_size, data_format)

  return tf.compat.v1.layers.conv2d(
      inputs=inputs,
      filters=filters,
      kernel_size=kernel_size,
      strides=strides,
      padding=('SAME' if strides == 1 else 'VALID'),
      use_bias=False,
      reuse=tf.AUTO_REUSE,
      kernel_initializer=tf.compat.v1.variance_scaling_initializer(),
      data_format=data_format,
      name=name)