add --device for fast_neural_style

@@ -28,6 +28,7 @@ python neural_style/neural_style.py eval --content-image </path/to/content/image
 - `--content-scale`: factor for scaling down the content image if memory is an issue (eg: value of 2 will halve the height and width of content-image)
 - `--cuda`: set it to 1 for running on GPU, 0 for CPU.
 - `--mps`: set it to 1 for running on macOS GPU
+- `--device DEVICE`: backend device to run on, 'cpu' by default.
 
 Train model
 
@@ -42,6 +43,7 @@ There are several command line arguments, the important ones are listed below
 - `--save-model-dir`: path to folder where trained model will be saved.
 - `--cuda`: set it to 1 for running on GPU, 0 for CPU.
 - `--mps`: set it to 1 for running on macOS GPU
+- `--device DEVICE`: backend device to run on, 'cpu' by default.
 
 Refer to `neural_style/neural_style.py` for other command line arguments. For training new models you might have to tune the values of `--content-weight` and `--style-weight`. The mosaic style model shown above was trained with `--content-weight 1e5` and `--style-weight 1e10`. The remaining 3 models were also trained with similar order of weight parameters with slight variation in the `--style-weight` (`5e10` or `1e11`).