Question

我只是运行一个简单的代码，希望在培训后获得准确性。我加载了我保存的模型，但是当我想要获得准确性时，我得到了一些错误。为什么呢？

# coding=utf-8
from  color_1 import read_and_decode, get_batch, get_test_batch
import AlexNet
import cv2
import os
import time
import numpy as np
import tensorflow as tf
import AlexNet_train
import math

batch_size=128
num_examples = 1000
crop_size=56

def evaluate(test_x, test_y):
    image_holder = tf.placeholder(tf.float32, [batch_size, 56, 56, 3], name='x-input')
    label_holder = tf.placeholder(tf.int32, [batch_size], name='y-input')

    y = AlexNet.inference(image_holder,evaluate,None)

    correct_prediction=tf.equal(tf.argmax(y,1),tf.argmax(label_holder,1))
    accuracy=tf.reduce_mean(tf.cast(correct_prediction,tf.float32))
    saver = tf.train.Saver()
    with tf.Session() as sess:
        init_op = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer())
        coord = tf.train.Coordinator()
        sess.run(init_op)
        threads = tf.train.start_queue_runners(sess=sess, coord=coord)
        ckpt=tf.train.get_checkpoint_state(AlexNet_train.MODEL_SAVE_PATH)
        if ckpt and ckpt.model_checkpoint_path:
            ckpt_name = os.path.basename(ckpt.model_checkpoint_path)
            global_step = ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1]
            saver.restore(sess, os.path.join(AlexNet_train.MODEL_SAVE_PATH, ckpt_name))
            print('Loading success, global_step is %s' % global_step)
            step=0

            image_batch, label_batch = sess.run([test_x, test_y])
            accuracy_score=sess.run(accuracy,feed_dict={image_holder: image_batch,
                                                              label_holder: label_batch})
            print("After %s training step(s),validation "
                  "precision=%g" % (global_step, accuracy_score))
        coord.request_stop()  
        coord.join(threads)

def main(argv=None):
    test_image, test_label = read_and_decode('val.tfrecords')

    test_images, test_labels = get_test_batch(test_image, test_label, batch_size, crop_size)

    evaluate(test_images, test_labels)


if __name__=='__main__':
    tf.app.run()

这是错误，它说我的代码中的这一行是错的：＆＃34; correct_prediction = tf.equal（tf.argmax（Y，1），tf.argmax（label_holder，1））＆＃34;

Traceback (most recent call last):
  File "/home/vrview/tensorflow/example/char/tfrecords/AlexNet/Alex_save/AlexNet_test.py", line 80, in <module>
    tf.app.run()
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "/home/vrview/tensorflow/example/char/tfrecords/AlexNet/Alex_save/AlexNet_test.py", line 76, in main
    evaluate(test_images, test_labels)
  File "/home/vrview/tensorflow/example/char/tfrecords/AlexNet/Alex_save/AlexNet_test.py", line 45, in evaluate
    label_holder: label_batch})
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 767, in run
    run_metadata_ptr)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 965, in _run
    feed_dict_string, options, run_metadata)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1015, in _do_run
    target_list, options, run_metadata)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1035, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected dimension in the range [-1, 1), but got 1
     [[Node: ArgMax_1 = ArgMax[T=DT_INT32, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_y-input_0, ArgMax_1/dimension)]]

Caused by op u'ArgMax_1', defined at:
  File "/home/vrview/tensorflow/example/char/tfrecords/AlexNet/Alex_save/AlexNet_test.py", line 80, in <module>
    tf.app.run()
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "/home/vrview/tensorflow/example/char/tfrecords/AlexNet/Alex_save/AlexNet_test.py", line 76, in main
    evaluate(test_images, test_labels)
  File "/home/vrview/tensorflow/example/char/tfrecords/AlexNet/Alex_save/AlexNet_test.py", line 22, in evaluate
    correct_prediction=tf.equal(tf.argmax(y,1),tf.argmax(label_holder,1))
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 263, in argmax
    return gen_math_ops.arg_max(input, axis, name)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 168, in arg_max
    name=name)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
    op_def=op_def)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2395, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/vrview/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1264, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): Expected dimension in the range [-1, 1), but got 1
     [[Node: ArgMax_1 = ArgMax[T=DT_INT32, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_y-input_0, ArgMax_1/dimension)]]

如何解决？

Answer 1

在这里考虑this answer与问题相关的部分：

tf.argmax's definition州：

轴：张量。必须是以下类型之一：int32，int64。 int32， 0＆lt; = axis＆lt;秩（输入）即可。描述输入的哪个轴张量减少跨越。

然后，似乎在张量的最后一个轴上运行argmax的唯一方法是给它axis=-1，因为“严格小于”符号的定义是功能

Tensorflow：我的准确性有问题

1 个答案: