title: "You must feed a value for placeholder tensor" when data exists and is going into feed dict
body: <p>I swear I'm doing everything correctly, but I'm stuck.</p>
  
  <p>I have my placeholders, but let's just look at one:</p>
  
  <pre><code>y  = tf.placeholder(tf.int32,   [1, 280, 280, 160]) 
  </code></pre>
  
  <p>Notice, they all look fine:</p>
  
  <pre><code>print(y.shape)
  print(y.dtype)
  print(type(y))    
  </code></pre>
  
  <p>gives me  </p>
  
  <pre><code>(1, 280, 280, 160)
  &lt;dtype: 'int32'&gt;
  &lt;class 'tensorflow.python.framework.ops.Tensor'&gt;
  </code></pre>
  
  <p>my data generator is happily supplying these labels, called <code>y_batch</code>:</p>
  
  <pre><code>print(y_batch.shape)
  print(y_batch.dtype)
  print(y_batch))
  </code></pre>
  
  <p>which also seem fine to me:</p>
  
  <pre><code>(1, 280, 280, 160)
  int32
  &lt;class 'numpy.ndarray'&gt;
  </code></pre>
  
  <p>So correct me if I'm wrong but <em>I see no mismatch between the structure of the data and the placeholder!!!!</em></p>
  
  <p>OK, I feel like I should be able to train this.  </p>
  
  <p>So I know this will crash miserably since all I'm feeding to it is the labels, and no actual data. But still, it doesn't crash in the right way. Instead it's crashing and complaining about shape:</p>
  
  <pre><code>ce_loss, step, test_summary = sess.run([loss, global_step, summary_op], {y:y_batch}) 
  </code></pre>
  
  <p>I get: </p>
  
  <p><code>InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_2' with dtype int32 and shape [1,280,280,160]..</code></p>
  
  <p>This problem makes no sense. Clearly the data exists. Clearly the feed dict is sitting right there. There's no dimension mismatch.</p>
  
  <p>NOTE: I know, I'm only feeding labels. But I did that to make this stack overflow question easier to deal with. It gives me the exact same behavior when I feed in the actual data and labels simultaneously.</p>
  
  <p>NOTE 2: This question is not a duplicate! As far as I can tell. I clearly have the data in scope and I am clearly feeding the data to the session via the feed dic</p>