Fix issue with no-init dataclass fields in move_to_device (#9963)

Co-authored-by: ronif <ronif@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>

CHANGELOG.md

@@ -544,6 +544,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed use of `LightningCLI` in computer_vision_fine_tuning.py example ([#9934](https://github.com/PyTorchLightning/pytorch-lightning/pull/9934))
 
 
+- Fixed issue with non-init dataclass fields in `apply_to_collection` ([#9963](https://github.com/PyTorchLightning/pytorch-lightning/issues/9963))
+
+
 ## [1.4.9] - 2021-09-30
 
 - Fixed `lr_find` to generate same results on multiple calls ([#9704](https://github.com/PyTorchLightning/pytorch-lightning/pull/9704))

pytorch_lightning/utilities/apply_func.py

@@ -118,18 +118,19 @@ def apply_to_collection(
 
     if _is_dataclass_instance(data):
         out_dict = {}
-        for field in data.__dataclass_fields__:
-            v = apply_to_collection(
-                getattr(data, field),
-                dtype,
-                function,
-                *args,
-                wrong_dtype=wrong_dtype,
-                include_none=include_none,
-                **kwargs,
-            )
-            if include_none or v is not None:
-                out_dict[field] = v
+        for field in dataclasses.fields(data):
+            if field.init:
+                v = apply_to_collection(
+                    getattr(data, field.name),
+                    dtype,
+                    function,
+                    *args,
+                    wrong_dtype=wrong_dtype,
+                    include_none=include_none,
+                    **kwargs,
+                )
+                if include_none or v is not None:
+                    out_dict[field.name] = v
         return elem_type(**out_dict)
 
     # data is neither of dtype, nor a collection

tests/utilities/test_apply_func.py

@@ -36,6 +36,10 @@ def test_recursive_application_to_collection():
         example_ids: List[str]
         feature: Feature
         label: torch.Tensor
+        some_constant: int = dataclasses.field(init=False)
+
+        def __post_init__(self):
+            self.some_constant = 7
 
     to_reduce = {
         "a": torch.tensor([1.0]),  # Tensor