diff --git a/python/paddle/v2/dataset/flowers.py b/python/paddle/v2/dataset/flowers.py index d9a39b11df3298c16a3b8af7dd455112536b19e1..07c13cf719ae0c864c23fef51f0bd7d47f265759 100644 --- a/python/paddle/v2/dataset/flowers.py +++ b/python/paddle/v2/dataset/flowers.py @@ -105,7 +105,8 @@ def reader_creator(data_file, for sample, label in itertools.izip(data, batch['label']): yield sample, int(label) - return paddle.reader.xmap(mapper, reader, cpu_count(), buffered_size) + return paddle.reader.xmap_readers(mapper, reader, + cpu_count(), buffered_size) def train(mapper=default_mapper, buffered_size=1024): diff --git a/python/paddle/v2/image.py b/python/paddle/v2/image.py index 56031e8734b96d6e5903fca75953230b6852e629..0d648e9ae697ff0373c6cdc166608d395a8d8086 100644 --- a/python/paddle/v2/image.py +++ b/python/paddle/v2/image.py @@ -3,8 +3,6 @@ try: import cv2 except ImportError: cv2 = None - -from cv2 import resize import os import tarfile import cPickle @@ -164,7 +162,7 @@ def resize_short(im, size): h_new = size * h / w else: w_new = size * w / h - im = resize(im, (h_new, w_new), interpolation=cv2.INTER_CUBIC) + im = cv2.resize(im, (h_new, w_new), interpolation=cv2.INTER_CUBIC) return im diff --git a/python/paddle/v2/reader/decorator.py b/python/paddle/v2/reader/decorator.py index 1b5df21b3de4fa71c2960b38ad0ae64ae2978585..c76faa596c9fb9079cab3456b721c18ef9768e95 100644 --- a/python/paddle/v2/reader/decorator.py +++ b/python/paddle/v2/reader/decorator.py @@ -14,7 +14,7 @@ __all__ = [ 'map_readers', 'buffered', 'compose', 'chain', 'shuffle', - 'ComposeNotAligned', 'firstn', 'xmap' + 'ComposeNotAligned', 'firstn', 'xmap_readers' ] import itertools @@ -230,7 +230,7 @@ class XmapEndSignal(): pass -def xmap(mapper, reader, process_num, buffer_size): +def xmap_readers(mapper, reader, process_num, buffer_size): """ Use multiprocess to map samples from reader by a mapper defined by user. And this function contains a buffered decorator.