TensorFlow random_shuffle_queue is closed and has insufficient elements

Question

I\'m reading batch of images by getting idea here from tfrecords(converted by this)

My images are cifar images, [32, 32, 3] and as you can see while reading and pas

Answer 1

You're likely processing the parsed TFRecord example wrong. E.g. trying to reshape a tensor to an incompatible size. You can debug using a tf_record_iterator to confirm the data you're reading is stored the way you think it is:

import tensorflow as tf
import numpy as np

tfrecords_filename = '/path/to/some.tfrecord'
record_iterator = tf.python_io.tf_record_iterator(path=tfrecords_filename)

for string_record in record_iterator:
    # Parse the next example
    example = tf.train.Example()
    example.ParseFromString(string_record)

    # Get the features you stored (change to match your tfrecord writing code)
    height = int(example.features.feature['height']
                                 .int64_list
                                 .value[0])

    width = int(example.features.feature['width']
                                .int64_list
                                .value[0])

    img_string = (example.features.feature['image_raw']
                                  .bytes_list
                                  .value[0])
    # Convert to a numpy array (change dtype to the datatype you stored)
    img_1d = np.fromstring(img_string, dtype=np.float32)
    # Print the image shape; does it match your expectations?
    print(img_1d.shape)