title: conv1d and conv2d in tensorflow
body: <p>For conv2d, assuming an input 2D matrix with shape (W,H) and the conv kernel size is (Wk,H), which means the height of the kernel is the same with the height of input matrix. In this case, can we think that conv1 with kernel size Wk carries out the same computation as conv2d?</p>
  
  <p>For example:</p>
  
  <pre><code>tf.layers.conv2d(
      kernel_size=tf.Variable(tf.truncated_normal([Wk, H, 1, out_dim], stddev=0.1),
      input=...
  ) 
  </code></pre>
  
  <p>equals to:</p>
  
  <pre><code>tf.layers.conv1d(kernel_size=Wk, input=...)
  </code></pre>