我关注 this学习 TensorFlow Slim 的教程，但在运行以下 Inception 代码时:
import numpy as np
import os
import tensorflow as tf
import urllib2
from datasets import imagenet
from nets import inception
from preprocessing import inception_preprocessing
slim = tf.contrib.slim
batch_size = 3
image_size = inception.inception_v1.default_image_size
checkpoints_dir = '/tmp/checkpoints/'
with tf.Graph().as_default():
url = 'https://upload.wikimedia.org/wikipedia/commons/7/70/EnglishCockerSpaniel_simon.jpg'
image_string = urllib2.urlopen(url).read()
image = tf.image.decode_jpeg(image_string, channels=3)
processed_image = inception_preprocessing.preprocess_image(image, image_size, image_size, is_training=False)
processed_images = tf.expand_dims(processed_image, 0)
# Create the model, use the default arg scope to configure the batch norm parameters.
with slim.arg_scope(inception.inception_v1_arg_scope()):
logits, _ = inception.inception_v1(processed_images, num_classes=1001, is_training=False)
probabilities = tf.nn.softmax(logits)
init_fn = slim.assign_from_checkpoint_fn(
os.path.join(checkpoints_dir, 'inception_v1.ckpt'),
slim.get_model_variables('InceptionV1'))
with tf.Session() as sess:
init_fn(sess)
np_image, probabilities = sess.run([image, probabilities])
probabilities = probabilities[0, 0:]
sorted_inds = [i[0] for i in sorted(enumerate(-probabilities), key=lambda x:x[1])]
plt.figure()
plt.imshow(np_image.astype(np.uint8))
plt.axis('off')
plt.show()
names = imagenet.create_readable_names_for_imagenet_labels()
for i in range(5):
index = sorted_inds[i]
print('Probability %0.2f%% => [%s]' % (probabilities[index], names[index]))
我似乎遇到了这组错误:
Traceback (most recent call last):
File "DA_test_pred.py", line 24, in <module>
logits, _ = inception.inception_v1(processed_images, num_classes=1001, is_training=False)
File "/home/deepankar1994/Desktop/MTP/TensorFlowEx/TFSlim/models/slim/nets/inception_v1.py", line 290, in inception_v1
net, end_points = inception_v1_base(inputs, scope=scope)
File "/home/deepankar1994/Desktop/MTP/TensorFlowEx/TFSlim/models/slim/nets/inception_v1.py", line 96, in inception_v1_base
net = tf.concat(3, [branch_0, branch_1, branch_2, branch_3])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 1053, in concat
dtype=dtypes.int32).get_shape(
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 651, in convert_to_tensor
as_ref=False)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 716, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 176, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 165, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 367, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.
这很奇怪，因为所有这些代码都来自他们的官方指南。我是 TF 的新手，如有任何帮助，我们将不胜感激。
最佳答案
我在使用 1.0 版本时遇到了同样的问题，我可以让它工作而不必回滚到以前的版本。
这个问题是由于 api 的变化引起的。那次讨论帮助我找到了解决方案:Google group > Recent API Changes in TensorFlow
你只需要用 tf.concat 更新所有的行
例如
net = tf.concat(3, [branch_0, branch_1, branch_2, branch_3])
应该改为
net = tf.concat([branch_0, branch_1, branch_2, branch_3], 3)
注意:
我能够毫无问题地使用这些模型。但是之后我想加载预训练的重量时仍然出错。 自从他们制作了检查点文件以来，似乎 slim 模块发生了一些变化。代码创建的图形与检查点文件中存在的图形不同。
注2:
通过添加到所有 conv2d 层 biases_initializer=None
关于python - Tensorflow Slim : TypeError: Expected int32, 得到了包含 '_Message' 类型张量的列表，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/41813665/