code: def test_same_padding_conv(self):
      for ishape in [[10], [11]]:
          inputs = np.zeros(ishape, dtype=np.float32)
          inputs[len(inputs) // 2] = 1
          for kshape in [[4], [5]]:
              kernel = np.zeros(kshape, dtype=np.float32)
              kernel[len(kernel) // 2] = 1
              outputs = tf.nn.conv2d_transpose(
                  tf.reshape(inputs, (1, 1, -1, 1)),
                  tf.reshape(kernel, (1, -1, 1, 1)),
                  (1, 1, ishape[0] + kshape[0] - 1, 1),
                  strides=(1, 1, 1, 1),
                  padding="VALID",
                  data_format="NHWC",
              )
              outputs = outputs[
                  :, :, (kshape[0] - 1) : -(kshape[0] - 1), :
              ]
              outputs = np.squeeze(outputs.numpy())
              pos_inp = np.squeeze(np.nonzero(inputs > 0.5))
              pos_out = np.squeeze(np.nonzero(outputs > 0.5))
              padding = padding_ops.same_padding_for_kernel(
                  kshape, False
              )
              self.assertEqual(padding[0][0], pos_inp - pos_out)
  
imports: import numpy
  import tensorflow
  from tensorflow_compression.python.ops import padding_ops
label_desc: Use image node_id 2 for calling the PaddingOpsTest obj's underlying member method code with example usage: obj.test_same_padding_conv() without return types