Merge 4916544c8d into bbe2c13a70

Move count increment before isinstance(item, dict) check so that
non-dict output items (like text strings from PreviewAny node)
are included in outputs_count.

This aligns OSS Python with Cloud's Go implementation which uses
len(itemsArray) to count ALL items regardless of type.

Amp-Thread-ID: https://ampcode.com/threads/T-019c0bb5-14e0-744f-8808-1e57653f3ae3

Co-authored-by: Amp <amp@ampcode.com>

comfy_execution/jobs.py

@@ -171,9 +171,10 @@ def get_outputs_summary(outputs: dict) -> tuple[int, Optional[dict]]:
                 continue
 
             for item in items:
+                count += 1
+
                 if not isinstance(item, dict):
                     continue
-                count += 1
 
                 if preview_output is None and is_previewable(media_type, item):
                     enriched = {

comfy_extras/nodes_hunyuan.py

@@ -56,7 +56,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
     @classmethod
     def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
         latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        return io.NodeOutput({"samples":latent})
+        return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 8})
 
     generate = execute  # TODO: remove
 
@@ -73,7 +73,7 @@ class EmptyHunyuanVideo15Latent(EmptyHunyuanLatentVideo):
     def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
         # Using scale factor of 16 instead of 8
         latent = torch.zeros([batch_size, 32, ((length - 1) // 4) + 1, height // 16, width // 16], device=comfy.model_management.intermediate_device())
-        return io.NodeOutput({"samples": latent})
+        return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 16})
 
 
 class HunyuanVideo15ImageToVideo(io.ComfyNode):

comfy_extras/nodes_primitive.py

@@ -66,7 +66,7 @@ class Float(io.ComfyNode):
             display_name="Float",
             category="utils/primitive",
             inputs=[
-                io.Float.Input("value", min=-sys.maxsize, max=sys.maxsize, step=0.1),
+                io.Float.Input("value", min=float(-sys.maxsize), max=float(sys.maxsize), step=0.1),
             ],
             outputs=[io.Float.Output()],
         )