我正在按照这个教程学习TensorFlow Slim，但在运行以下用于Inception的代码时：

import numpy as npimport osimport tensorflow as tfimport urllib2from datasets import imagenetfrom nets import inceptionfrom preprocessing import inception_preprocessingslim = tf.contrib.slimbatch_size = 3image_size = inception.inception_v1.default_image_sizecheckpoints_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]))

我似乎遇到了以下错误：

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新手，任何帮助都会被感激的。

回答：

我在使用1.0版本时也遇到了相同的问题，我设法在不需要回退到之前版本的情况下解决了这个问题。

问题是由API的变化引起的。那个讨论帮助我找到了解决方案：Google群组 > TensorFlow最近的API变化

你只需要更新所有使用tf.concat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：

我能够无问题地使用模型。但在之后想要加载预训练权重时仍然遇到了错误。看起来自从他们制作检查点文件以来，slim模块有了一些变化。代码创建的图和检查点文件中的图是不同的。

注意2：

通过在所有conv2d层中添加biases_initializer=None，我能够使用inception_resnet_v2的预训练权重。