parameters: (self, batch_size, images, labels)
return_statement: return images, labels
docstring: Statically set the batch_size dimension.
docstring_summary: Statically set the batch_size dimension.
docstring_tokens: Statically set the batch_size dimension .
function: def set_shapes(self, batch_size, images, labels):
      """Statically set the batch_size dimension."""
      if self.transpose_input:
        images.set_shape(images.get_shape().merge_with(
            tf.TensorShape([None, None, None, batch_size])))
        labels.set_shape(labels.get_shape().merge_with(
            tf.TensorShape([batch_size])))
      else:
        images.set_shape(images.get_shape().merge_with(
            tf.TensorShape([batch_size, None, None, None])))
        labels.set_shape(labels.get_shape().merge_with(
            tf.TensorShape([batch_size])))
  
      return images, labels
function_tokens: def set_shapes ( self , batch_size , images , labels ) : if self . transpose_input : images . set_shape ( images . get_shape ( ) . merge_with ( tf . TensorShape ( [ None , None , None , batch_size ] ) ) ) labels . set_shape ( labels . get_shape ( ) . merge_with ( tf . TensorShape ( [ batch_size ] ) ) ) else : images . set_shape ( images . get_shape ( ) . merge_with ( tf . TensorShape ( [ batch_size , None , None , None ] ) ) ) labels . set_shape ( labels . get_shape ( ) . merge_with ( tf . TensorShape ( [ batch_size ] ) ) ) return images , labels