message: Fix ValueError in tf.nn.nce_loss when weights and biases are float64
  This fix tries to fix the issue raised in 24547 where ValueError
  was thrown when weights and biases are float64
  This fix fixes 24547
diff: @@ -1380,6 +1380,7 @@ def _compute_sampled_logits(weights,
  # weights shape is [num_classes, dim]
  all_w = embedding_ops.embedding_lookup(
  weights, all_ids, partition_strategy=partition_strategy)
  + all_w = all_w if all_w.dtype == inputs.dtype else math_ops.cast(all_w, inputs.dtype)
  # true_w shape is [batch_size * num_true, dim]
  true_w = array_ops.slice(all_w, [0, 0],
  @@ -1397,6 +1398,7 @@ def _compute_sampled_logits(weights,
  # add the biases to the true and sampled logits.
  all_b = embedding_ops.embedding_lookup(
  biases, all_ids, partition_strategy=partition_strategy)
  + all_b = all_b if all_b.dtype == inputs.dtype else math_ops.cast(all_b, inputs.dtype)
  # true_b is a [batch_size * num_true] tensor
  # sampled_b is a [num_sampled] float tensor
  true_b = array_ops.slice(all_b, [0], array_ops.shape(labels_flat))
  