running on tensorflow 1.3.0 GPU.
I have trained a model in TF and saved just a single varialbe tensor using:

```
embeddings = tf.Variable(tf.random_uniform([4**kmer_len, embedding_size], -0.04, 0.04), name='Embeddings')
more code, variables...
saver = tf.train.Saver({"Embeddings": embeddings})  # saving only embeddings variable
some more code, training model...
saver.save(ses, './embeddings/embedding_mat')       # saving the variable 

```

Now, I have a different model in a different file and I would like to resotre just the single saved **embeddings** variable to it. the problem is that this new model has some more variables.
Now, when I try to restore the variable by doing:

```
embeddings = tf.Variable(tf.random_uniform([4**kmer_len_emb, embedding_size], -0.04, 0.04), name='Embeddings')
dense1 = tf.layers.dense(inputs=kmer_flattened, units=200, activation=tf.nn.relu, use_bias=True)  
ses = tf.Session()
init = tf.global_variables_initializer()
ses.run(init)
saver = tf.train.Saver()
saver.restore(ses, './embeddings/embedding_mat')

```

I'm getting a not found in checkpoint error.
Any thoughts on how to deal with this?
Thanks