diff --git a/CHANGELOG.md b/CHANGELOG.md index 7d0151ef8..1c291ea0a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -76,6 +76,7 @@ To release a new version, please update the changelog as followed: ### Dependencies Update - nltk>=3.3,<3.4 => nltk>=3.3,<3.5 (PR #892) - pytest>=3.6,<3.11 => pytest>=3.6,<4.1 (PR #889) +- yapf>=0.22,<0.25 => yapf==0.25.0 (PR #896) ### Deprecated diff --git a/requirements/requirements_test.txt b/requirements/requirements_test.txt index cbe0b3de6..7a187e074 100644 --- a/requirements/requirements_test.txt +++ b/requirements/requirements_test.txt @@ -6,4 +6,4 @@ pytest-cache>=1.0,<1.1 pytest-cov>=2.5,<2.7 pytest-xdist>=1.22,<1.25 sphinx>=1.7,<1.9 -yapf>=0.22,<0.25 +yapf==0.25.0 diff --git a/tensorlayer/db.py b/tensorlayer/db.py index 80a8a6b4f..3e8656641 100644 --- a/tensorlayer/db.py +++ b/tensorlayer/db.py @@ -219,9 +219,8 @@ def find_top_model(self, sess, sort=None, model_name='model', **kwargs): pc = self.db.Model.find(kwargs) print( - "[Database] Find one model SUCCESS. kwargs:{} sort:{} save time:{} took: {}s".format( - kwargs, sort, _datetime, round(time.time() - s, 2) - ) + "[Database] Find one model SUCCESS. kwargs:{} sort:{} save time:{} took: {}s". + format(kwargs, sort, _datetime, round(time.time() - s, 2)) ) # put all informations of model into the TL layer @@ -656,10 +655,9 @@ def run_top_task(self, task_name=None, sort=None, **kwargs): }}, return_document=pymongo.ReturnDocument.AFTER ) logging.info( - "[Database] Finished Task: task_name - {} sort: {} push time: {} took: {}s".format( - task_name, sort, _datetime, - time.time() - s - ) + "[Database] Finished Task: task_name - {} sort: {} push time: {} took: {}s". + format(task_name, sort, _datetime, + time.time() - s) ) return True except Exception as e: diff --git a/tensorlayer/files/dataset_loaders/voc_dataset.py b/tensorlayer/files/dataset_loaders/voc_dataset.py index 91ef5ee85..8139e1a32 100644 --- a/tensorlayer/files/dataset_loaders/voc_dataset.py +++ b/tensorlayer/files/dataset_loaders/voc_dataset.py @@ -204,8 +204,9 @@ def _recursive_parse_xml_to_dict(xml): imgs_file_list = load_file_list(path=folder_imgs, regx='\\.jpg', printable=False) logging.info("[VOC] {} images found".format(len(imgs_file_list))) - imgs_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000027.jpg --> 2007000027 + imgs_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000027.jpg --> 2007000027 imgs_file_list = [os.path.join(folder_imgs, s) for s in imgs_file_list] # logging.info('IM',imgs_file_list[0::3333], imgs_file_list[-1]) @@ -215,8 +216,9 @@ def _recursive_parse_xml_to_dict(xml): folder_semseg = os.path.join(path, extracted_filename, "SegmentationClass") imgs_semseg_file_list = load_file_list(path=folder_semseg, regx='\\.png', printable=False) logging.info("[VOC] {} maps for semantic segmentation found".format(len(imgs_semseg_file_list))) - imgs_semseg_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000032.png --> 2007000032 + imgs_semseg_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000032.png --> 2007000032 imgs_semseg_file_list = [os.path.join(folder_semseg, s) for s in imgs_semseg_file_list] # logging.info('Semantic Seg IM',imgs_semseg_file_list[0::333], imgs_semseg_file_list[-1]) ##======== 3. instance segmentation maps path list @@ -224,8 +226,9 @@ def _recursive_parse_xml_to_dict(xml): folder_insseg = os.path.join(path, extracted_filename, "SegmentationObject") imgs_insseg_file_list = load_file_list(path=folder_insseg, regx='\\.png', printable=False) logging.info("[VOC] {} maps for instance segmentation found".format(len(imgs_semseg_file_list))) - imgs_insseg_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000032.png --> 2007000032 + imgs_insseg_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000032.png --> 2007000032 imgs_insseg_file_list = [os.path.join(folder_insseg, s) for s in imgs_insseg_file_list] # logging.info('Instance Seg IM',imgs_insseg_file_list[0::333], imgs_insseg_file_list[-1]) else: @@ -238,8 +241,9 @@ def _recursive_parse_xml_to_dict(xml): logging.info( "[VOC] {} XML annotation files for bounding box and object class found".format(len(imgs_ann_file_list)) ) - imgs_ann_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000027.xml --> 2007000027 + imgs_ann_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000027.xml --> 2007000027 imgs_ann_file_list = [os.path.join(folder_ann, s) for s in imgs_ann_file_list] # logging.info('ANN',imgs_ann_file_list[0::3333], imgs_ann_file_list[-1]) diff --git a/tensorlayer/files/utils.py b/tensorlayer/files/utils.py index 8e6aa213d..5a35bc3cc 100644 --- a/tensorlayer/files/utils.py +++ b/tensorlayer/files/utils.py @@ -1189,8 +1189,9 @@ def _recursive_parse_xml_to_dict(xml): imgs_file_list = load_file_list(path=folder_imgs, regx='\\.jpg', printable=False) logging.info("[VOC] {} images found".format(len(imgs_file_list))) - imgs_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000027.jpg --> 2007000027 + imgs_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000027.jpg --> 2007000027 imgs_file_list = [os.path.join(folder_imgs, s) for s in imgs_file_list] # logging.info('IM',imgs_file_list[0::3333], imgs_file_list[-1]) @@ -1200,8 +1201,9 @@ def _recursive_parse_xml_to_dict(xml): folder_semseg = os.path.join(path, extracted_filename, "SegmentationClass") imgs_semseg_file_list = load_file_list(path=folder_semseg, regx='\\.png', printable=False) logging.info("[VOC] {} maps for semantic segmentation found".format(len(imgs_semseg_file_list))) - imgs_semseg_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000032.png --> 2007000032 + imgs_semseg_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000032.png --> 2007000032 imgs_semseg_file_list = [os.path.join(folder_semseg, s) for s in imgs_semseg_file_list] # logging.info('Semantic Seg IM',imgs_semseg_file_list[0::333], imgs_semseg_file_list[-1]) # ======== 3. instance segmentation maps path list @@ -1209,8 +1211,9 @@ def _recursive_parse_xml_to_dict(xml): folder_insseg = os.path.join(path, extracted_filename, "SegmentationObject") imgs_insseg_file_list = load_file_list(path=folder_insseg, regx='\\.png', printable=False) logging.info("[VOC] {} maps for instance segmentation found".format(len(imgs_semseg_file_list))) - imgs_insseg_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000032.png --> 2007000032 + imgs_insseg_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000032.png --> 2007000032 imgs_insseg_file_list = [os.path.join(folder_insseg, s) for s in imgs_insseg_file_list] # logging.info('Instance Seg IM',imgs_insseg_file_list[0::333], imgs_insseg_file_list[-1]) else: @@ -1223,8 +1226,9 @@ def _recursive_parse_xml_to_dict(xml): logging.info( "[VOC] {} XML annotation files for bounding box and object class found".format(len(imgs_ann_file_list)) ) - imgs_ann_file_list.sort(key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) - ) # 2007_000027.xml --> 2007000027 + imgs_ann_file_list.sort( + key=lambda s: int(s.replace('.', ' ').replace('_', '').split(' ')[-2]) + ) # 2007_000027.xml --> 2007000027 imgs_ann_file_list = [os.path.join(folder_ann, s) for s in imgs_ann_file_list] # logging.info('ANN',imgs_ann_file_list[0::3333], imgs_ann_file_list[-1]) diff --git a/tensorlayer/layers/convolution/deformable_conv.py b/tensorlayer/layers/convolution/deformable_conv.py index 6d414e4c6..70343c83d 100644 --- a/tensorlayer/layers/convolution/deformable_conv.py +++ b/tensorlayer/layers/convolution/deformable_conv.py @@ -107,8 +107,9 @@ def __init__( input_h = int(self.inputs.get_shape()[1]) input_w = int(self.inputs.get_shape()[2]) kernel_n = shape[0] * shape[1] - initial_offsets = tf.stack(tf.meshgrid(tf.range(shape[0]), tf.range(shape[1]), - indexing='ij')) # initial_offsets --> (kh, kw, 2) + initial_offsets = tf.stack( + tf.meshgrid(tf.range(shape[0]), tf.range(shape[1]), indexing='ij') + ) # initial_offsets --> (kh, kw, 2) initial_offsets = tf.reshape(initial_offsets, (-1, 2)) # initial_offsets --> (n, 2) initial_offsets = tf.expand_dims(initial_offsets, 0) # initial_offsets --> (1, n, 2) initial_offsets = tf.expand_dims(initial_offsets, 0) # initial_offsets --> (1, 1, n, 2) diff --git a/tensorlayer/utils.py b/tensorlayer/utils.py index 838de4100..85305a7cc 100644 --- a/tensorlayer/utils.py +++ b/tensorlayer/utils.py @@ -573,8 +573,9 @@ def exit_tensorflow(sess=None, port=6006): elif _platform == "darwin": tl.logging.info('OS X: %s' % text) - subprocess.Popen("lsof -i tcp:" + str(port) + " | grep -v PID | awk '{print $2}' | xargs kill", - shell=True) # kill tensorboard + subprocess.Popen( + "lsof -i tcp:" + str(port) + " | grep -v PID | awk '{print $2}' | xargs kill", shell=True + ) # kill tensorboard elif _platform == "win32": raise NotImplementedError("this function is not supported on the Windows platform") diff --git a/tensorlayer/visualize.py b/tensorlayer/visualize.py index 647b4d537..9fe27c758 100644 --- a/tensorlayer/visualize.py +++ b/tensorlayer/visualize.py @@ -645,8 +645,9 @@ def draw_weights(W=None, second=10, saveable=True, shape=None, name='mnist', fig # feature = np.zeros_like(feature) # if np.mean(feature) < -0.015: # condition threshold # feature = np.zeros_like(feature) - plt.imshow(np.reshape(feature, (shape[0], shape[1])), cmap='gray', - interpolation="nearest") # , vmin=np.min(feature), vmax=np.max(feature)) + plt.imshow( + np.reshape(feature, (shape[0], shape[1])), cmap='gray', interpolation="nearest" + ) # , vmin=np.min(feature), vmax=np.max(feature)) # plt.title(name) # ------------------------------------------------------------ # plt.imshow(np.reshape(W[:,count-1] ,(np.sqrt(size),np.sqrt(size))), cmap='gray', interpolation="nearest") diff --git a/tests/test_tf_layers.py b/tests/test_tf_layers.py index c4d2440bc..dc04a06ff 100644 --- a/tests/test_tf_layers.py +++ b/tests/test_tf_layers.py @@ -162,8 +162,9 @@ def get_network_3d(inputs, reuse=False): with tf.variable_scope("3D_network", reuse=reuse): net = tl.layers.InputLayer(inputs) - net1 = tl.layers.Conv3dLayer(net, shape=(2, 2, 2, 3, 32), strides=(1, 2, 2, 2, 1), - name="Conv3dLayer") # 2 params + net1 = tl.layers.Conv3dLayer( + net, shape=(2, 2, 2, 3, 32), strides=(1, 2, 2, 2, 1), name="Conv3dLayer" + ) # 2 params net2 = tl.layers.DeConv3d(net1, name="DeConv3d") # 2 params net3 = tl.layers.MaxPool3d(net2, (1, 1, 1), name="MaxPool3d") # 0 params net4 = tl.layers.MeanPool3d(net3, (1, 1, 1), name="MeanPool3d") # 0 params