Review fixes

Signed-off-by: Marek Dabek <mdabek@nvidia.com>

Author: mdabek-nvidia

dali/python/nvidia/dali/experimental/torchvision/v2/color.py

@@ -99,7 +99,7 @@ def verify(cls, data_input) -> None:
             layout = data_input.property("layout")[1]
 
         # CHW
-        if layout.cpu() == np.frombuffer(bytes("C", "utf-8"), dtype=np.uint8)[0]:
+        if layout == np.frombuffer(bytes("C", "utf-8"), dtype=np.uint8)[0]:
             raise NotImplementedError(
                 "NCHW and CHW layout are not supported for Grayscale, expecting HWC or NHWC"
             )

dali/python/nvidia/dali/experimental/torchvision/v2/functional/color.py

@@ -44,8 +44,6 @@ def _grayscale(
         return ndd.cat(inpt, inpt, inpt, axis_name="C")
     else:
         return ndd.hsv(inpt, saturation=0, device=device)
-    else:
-        return ndd.hsv(inpt, saturation=0, device=device)
 
 
 @adjust_input

dali/python/nvidia/dali/experimental/torchvision/v2/functional/normalize.py

@@ -18,7 +18,7 @@
 import torch
 import nvidia.dali.experimental.dynamic as ndd
 
-from ..operator import adjust_input, VerificationIsTensor  # noqa: E402
+from ..operator import adjust_input, _ValidateIsTensor  # noqa: E402
 from ..normalize import Normalize  # noqa: E402
 
 
@@ -54,7 +54,7 @@ def normalize(
     std = np.asarray(std)[:, None, None]
 
     Normalize.verify_args(std=std, mean=mean)
-    VerificationIsTensor.verify(input_data)
+    _ValidateIsTensor.verify(input_data)
 
     if inplace:
         raise NotImplementedError("inplace is not implemented, yet")

dali/python/nvidia/dali/experimental/torchvision/v2/normalize.py

@@ -17,10 +17,10 @@
 from typing import Sequence, Literal
 import nvidia.dali.fn as fn
 
-from .operator import Operator, ArgumentVerificationRule
+from .operator import Operator, _ArgumentValidateRule
 
 
-class VerifyStd(ArgumentVerificationRule):
+class _ValidateStd(_ArgumentValidateRule):
     """
     Verify the standard deviation argument for the Normalize operator.
 
@@ -32,17 +32,15 @@ class VerifyStd(ArgumentVerificationRule):
 
     @classmethod
     def verify(cls, *, std, **_) -> None:
-        if (
-            not isinstance(std, (int, float, Sequence, torch.Tensor, np.ndarray))
-            or isinstance(std, Sequence)
-            and isinstance(std, str)
+        if not isinstance(std, (int, float, Sequence, torch.Tensor, np.ndarray)) or (
+            isinstance(std, Sequence) and isinstance(std, str)
         ):
             raise TypeError(f"Std must be an int, a float or a Sequence, got {type(std)}")
         if np.any(np.array(std) == 0):
             raise ValueError("Std must not be 0")
 
 
-class VerifyMean(ArgumentVerificationRule):
+class _ValidateMean(_ArgumentValidateRule):
     """
     Verify the mean argument for the Normalize operator.
 
@@ -77,7 +75,7 @@ class Normalize(Operator):
         Bool to make this operation in-place. Not supported.
     """
 
-    arg_rules = [VerifyStd, VerifyMean]
+    arg_rules = [_ValidateStd, _ValidateMean]
     # TODO: currently not supported
     # input_rules = [VerificationIsTensor]