diff --git a/PaddleCV/gan/cycle_gan/infer.py b/PaddleCV/gan/cycle_gan/infer.py
index 666e6859b64482de12bcd0b13d15a76c63963e2f..51772e3a5879f3b5f316fc086a4e30b9231e214d 100644
--- a/PaddleCV/gan/cycle_gan/infer.py
+++ b/PaddleCV/gan/cycle_gan/infer.py
@@ -2,7 +2,6 @@ import argparse
import functools
import os
from PIL import Image
-from paddle.fluid import core
import paddle.fluid as fluid
import paddle
import numpy as np
@@ -51,7 +50,7 @@ def infer(args):
if len(image.shape) != 3:
continue
data = image.transpose([2, 0, 1])[np.newaxis, :].astype("float32")
- tensor = core.LoDTensor()
+ tensor = fluid.LoDTensor()
tensor.set(data, place)
fake_temp = exe.run(fetch_list=[fake.name], feed={"input": tensor})
diff --git a/PaddleCV/gan/cycle_gan/train.py b/PaddleCV/gan/cycle_gan/train.py
index 561b1effc48477efb0454f63859e1664128e2a3a..29bd7b054cc0198930977ebafab635adc6b807b3 100644
--- a/PaddleCV/gan/cycle_gan/train.py
+++ b/PaddleCV/gan/cycle_gan/train.py
@@ -12,7 +12,6 @@ import numpy as np
from scipy.misc import imsave
import paddle.fluid as fluid
import paddle.fluid.profiler as profiler
-from paddle.fluid import core
import data_reader
from utility import add_arguments, print_arguments, ImagePool
from trainer import *
@@ -82,8 +81,8 @@ def train(args):
for data_A, data_B in zip(A_test_reader(), B_test_reader()):
A_name = data_A[1]
B_name = data_B[1]
- tensor_A = core.LoDTensor()
- tensor_B = core.LoDTensor()
+ tensor_A = fluid.LoDTensor()
+ tensor_B = fluid.LoDTensor()
tensor_A.set(data_A[0], place)
tensor_B.set(data_B[0], place)
fake_A_temp, fake_B_temp, cyc_A_temp, cyc_B_temp = exe.run(
@@ -168,8 +167,8 @@ def train(args):
for i in range(max_images_num):
data_A = next(A_reader)
data_B = next(B_reader)
- tensor_A = core.LoDTensor()
- tensor_B = core.LoDTensor()
+ tensor_A = fluid.LoDTensor()
+ tensor_B = fluid.LoDTensor()
tensor_A.set(data_A, place)
tensor_B.set(data_B, place)
s_time = time.time()
diff --git a/PaddleCV/icnet/infer.py b/PaddleCV/icnet/infer.py
index fddc375af223962add58cb6ddf7c0d319b318c99..1686adcc45b40b6306fbe8b5d0fc80aa757c74ab 100644
--- a/PaddleCV/icnet/infer.py
+++ b/PaddleCV/icnet/infer.py
@@ -115,7 +115,7 @@ def infer(args):
image_file, is_color=True).astype("float32")
image -= IMG_MEAN
img = paddle.dataset.image.to_chw(image)[np.newaxis, :]
- image_t = fluid.core.LoDTensor()
+ image_t = fluid.LoDTensor()
image_t.set(img, place)
result = exe.run(inference_program,
feed={"image": image_t},
diff --git a/PaddleCV/icnet/utils.py b/PaddleCV/icnet/utils.py
index 7d58060eb96fd95a04f377f8c852eda02e59b5f6..2796b95d3aa5c36d31b49901c8b5f5a8f91866aa 100644
--- a/PaddleCV/icnet/utils.py
+++ b/PaddleCV/icnet/utils.py
@@ -18,7 +18,6 @@ from __future__ import division
from __future__ import print_function
import distutils.util
import numpy as np
-from paddle.fluid import core
import six
@@ -72,7 +71,7 @@ def to_lodtensor(data, place):
lod.append(cur_len)
flattened_data = np.concatenate(data, axis=0).astype("int32")
flattened_data = flattened_data.reshape([len(flattened_data), 1])
- res = core.LoDTensor()
+ res = fluid.LoDTensor()
res.set(flattened_data, place)
res.set_lod([lod])
return res
@@ -80,17 +79,17 @@ def to_lodtensor(data, place):
def get_feeder_data(data, place, for_test=False):
feed_dict = {}
- image_t = core.LoDTensor()
+ image_t = fluid.LoDTensor()
image_t.set(data[0], place)
feed_dict["image"] = image_t
if not for_test:
- labels_sub1_t = core.LoDTensor()
- labels_sub2_t = core.LoDTensor()
- labels_sub4_t = core.LoDTensor()
- mask_sub1_t = core.LoDTensor()
- mask_sub2_t = core.LoDTensor()
- mask_sub4_t = core.LoDTensor()
+ labels_sub1_t = fluid.LoDTensor()
+ labels_sub2_t = fluid.LoDTensor()
+ labels_sub4_t = fluid.LoDTensor()
+ mask_sub1_t = fluid.LoDTensor()
+ mask_sub2_t = fluid.LoDTensor()
+ mask_sub4_t = fluid.LoDTensor()
labels_sub1_t.set(data[1], place)
labels_sub2_t.set(data[3], place)
@@ -105,8 +104,8 @@ def get_feeder_data(data, place, for_test=False):
feed_dict["label_sub4"] = labels_sub4_t
feed_dict["mask_sub4"] = mask_sub4_t
else:
- label_t = core.LoDTensor()
- mask_t = core.LoDTensor()
+ label_t = fluid.LoDTensor()
+ mask_t = fluid.LoDTensor()
label_t.set(data[1], place)
mask_t.set(data[2], place)
feed_dict["label"] = label_t
diff --git a/PaddleCV/ocr_recognition/utility.py b/PaddleCV/ocr_recognition/utility.py
index 3d0adb7781631e410302d9b1b25aa8353470d867..a22a744128e01f97026d1535278566ec8c8f7a66 100755
--- a/PaddleCV/ocr_recognition/utility.py
+++ b/PaddleCV/ocr_recognition/utility.py
@@ -18,7 +18,6 @@ from __future__ import division
from __future__ import print_function
import distutils.util
import numpy as np
-from paddle.fluid import core
import paddle.fluid as fluid
import six
@@ -73,14 +72,14 @@ def to_lodtensor(data, place):
lod.append(cur_len)
flattened_data = np.concatenate(data, axis=0).astype("int32")
flattened_data = flattened_data.reshape([len(flattened_data), 1])
- res = core.LoDTensor()
+ res = fluid.LoDTensor()
res.set(flattened_data, place)
res.set_lod([lod])
return res
def get_ctc_feeder_data(data, place, need_label=True):
- pixel_tensor = core.LoDTensor()
+ pixel_tensor = fluid.LoDTensor()
pixel_data = None
pixel_data = np.concatenate(
list(map(lambda x: x[0][np.newaxis, :], data)),
@@ -98,7 +97,7 @@ def get_ctc_feeder_for_infer(data, place):
def get_attention_feeder_data(data, place, need_label=True):
- pixel_tensor = core.LoDTensor()
+ pixel_tensor = fluid.LoDTensor()
pixel_data = None
pixel_data = np.concatenate(
list(map(lambda x: x[0][np.newaxis, :], data)),
@@ -130,7 +129,7 @@ def get_attention_feeder_for_infer(data, place):
init_scores = fluid.create_lod_tensor(init_scores_data,
init_recursive_seq_lens, place)
- pixel_tensor = core.LoDTensor()
+ pixel_tensor = fluid.LoDTensor()
pixel_data = None
pixel_data = np.concatenate(
list(map(lambda x: x[0][np.newaxis, :], data)),