title: Tensorflow ConcatOp Error with Object Detection API
body: <p>I'm following tensorflow object detection api instructions and trying to train <strong><em>existing object-detection model("faster_rcnn_resnet101_coco")</em></strong> with <strong>my own dataset having 50 classes</strong>.</p>
  
  <p>So according to my own dataset, I created </p>
  
  <ol>
  <li>TFRecord (FOR training,evaluation and testing separately)</li>
  <li>labelmap.pbtxt</li>
  </ol>
  
  <p>Next, I edited <strong><em>model.config</em></strong> only for <strong>model-faster_rcnn-num_classes</strong>(90 -> 50(the number of classes of my own dataset), train_config-batch_size(1 -> 10), train_config-num_steps(200000 -> 100), train_input_reader-tf_record_input_reader-input_path(to the path where TFRecord resides) and train_input_reader-label_map_path(to the path where labelmap.pbtxt resides).</p>
  
  <p>Finally, I run the command</p>
  
  <pre><code>python train.py \
  --logtostderr \
  --pipeline_config_path="PATH WHERE CONFIG FILE RESIDES" \
  --train_dir="PATH WHERE MODEL DIRECTORY RESIDES"
  </code></pre>
  
  <p>And I met the error below:</p>
  
  <blockquote>
    <p>InvalidArgumentError (see above for traceback): ConcatOp : Dimensions
    of inputs should match: shape[0] = [1,890,600,3] vs. shape[1] =
    [1,766,600,3]      [[Node: concat_1 = ConcatV2[N=10, T=DT_FLOAT,
    Tidx=DT_INT32,
    _device="/job:localhost/replica:0/task:0/cpu:0"](Preprocessor/sub, Preprocessor_1/sub, Preprocessor_2/sub, Preprocessor_3/sub,
    Preprocessor_4/sub, Preprocessor_5/sub, Preprocessor_6/sub,
    Preprocessor_7/sub, Preprocessor_8/sub, Preprocessor_9/sub,
    concat_1/axis)]]</p>
  </blockquote>
  
  <p>It seems like the dimension of input images so it may be caused by not resizing the raw image data.</p>
  
  <p>But As I know, model automatically resizes the input image to train (isn't it?)</p>
  
  <p>Then I'm stuck with this issue.</p>
  
  <p>If there is solution, I'll appreciate it for your answer.
  Thanks.</p>
  
  <p><strong><em>UPDATE</em></strong></p>
  
  <p>When I <code>updated my batch_size field from 10 to one(original one)</code>, it seems to <code>train without any problem</code>... <strong>but I don't understand why...</strong></p>