Allow selecting precision to make Dreambooth class images (#1832)

* allow selecting precision to make DB class images

addresses #1831

* add prior_generation_precision argument

* correct prior_generation_precision's description
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

examples/dreambooth/train_dreambooth.py

@@ -247,6 +247,16 @@ def parse_args(input_args=None):
             " flag passed with the `accelerate.launch` command. Use this argument to override the accelerate config."
         ),
     )
+    parser.add_argument(
+        "--prior_generation_precision",
+        type=str,
+        default=None,
+        choices=["no", "fp32", "fp16", "bf16"],
+        help=(
+            "Choose prior generation precision between fp32, fp16 and bf16 (bfloat16). Bf16 requires PyTorch >="
+            " 1.10.and an Nvidia Ampere GPU.  Default to  fp16 if a GPU is available else fp32."
+        ),
+    )
     parser.add_argument("--local_rank", type=int, default=-1, help="For distributed training: local_rank")
     parser.add_argument(
         "--enable_xformers_memory_efficient_attention", action="store_true", help="Whether or not to use xformers."
@@ -436,6 +446,12 @@ def main(args):
 
         if cur_class_images < args.num_class_images:
             torch_dtype = torch.float16 if accelerator.device.type == "cuda" else torch.float32
+            if args.prior_generation_precision == "fp32":
+                torch_dtype = torch.float32
+            elif args.prior_generation_precision == "fp16":
+                torch_dtype = torch.float16
+            elif args.prior_generation_precision == "bf16":
+                torch_dtype = torch.bfloat16
             pipeline = DiffusionPipeline.from_pretrained(
                 args.pretrained_model_name_or_path,
                 torch_dtype=torch_dtype,