refactor usage of manual seed (Lightning-AI#2007)

* refactor usage of manual seed

* fix outputs

examples/plotting.py

@@ -246,8 +246,9 @@ def error_relative_global_dimensionless_synthesis() -> tuple:
     """Plot error relative global dimensionless synthesis example."""
     from torchmetrics.image.ergas import ErrorRelativeGlobalDimensionlessSynthesis
 
-    p = lambda: torch.rand([16, 1, 16, 16], generator=torch.manual_seed(42))
-    t = lambda: torch.rand([16, 1, 16, 16], generator=torch.manual_seed(42))
+    gen = torch.manual_seed(42)
+    p = lambda: torch.rand([16, 1, 16, 16], generator=gen)
+    t = lambda: torch.rand([16, 1, 16, 16], generator=gen)
 
     # plot single value
     metric = ErrorRelativeGlobalDimensionlessSynthesis()
@@ -286,8 +287,9 @@ def spectral_angle_mapper() -> tuple:
     """Plot spectral angle mapper example."""
     from torchmetrics.image.sam import SpectralAngleMapper
 
-    p = lambda: torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-    t = lambda: torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+    gen = torch.manual_seed(42)
+    p = lambda: torch.rand([16, 3, 16, 16], generator=gen)
+    t = lambda: torch.rand([16, 3, 16, 16], generator=gen)
 
     # plot single value
     metric = SpectralAngleMapper()
@@ -306,7 +308,8 @@ def structural_similarity_index_measure() -> tuple:
     """Plot structural similarity index measure example."""
     from torchmetrics.image.ssim import StructuralSimilarityIndexMeasure
 
-    p = lambda: torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
+    gen = torch.manual_seed(42)
+    p = lambda: torch.rand([3, 3, 256, 256], generator=gen)
     t = lambda: p() * 0.75
 
     # plot single value
@@ -326,7 +329,8 @@ def multiscale_structural_similarity_index_measure() -> tuple:
     """Plot multiscale structural similarity index measure example."""
     from torchmetrics.image.ssim import MultiScaleStructuralSimilarityIndexMeasure
 
-    p = lambda: torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
+    gen = torch.manual_seed(42)
+    p = lambda: torch.rand([3, 3, 256, 256], generator=gen)
     t = lambda: p() * 0.75
 
     # plot single value

src/torchmetrics/functional/image/_deprecated.py

@@ -48,7 +48,8 @@ def _error_relative_global_dimensionless_synthesis(
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> preds = torch.rand([16, 1, 16, 16], generator=torch.manual_seed(42))
+    >>> gen = torch.manual_seed(42)
+    >>> preds = torch.rand([16, 1, 16, 16], generator=gen)
     >>> target = preds * 0.75
     >>> ergds = _error_relative_global_dimensionless_synthesis(preds, target)
     >>> torch.round(ergds)
@@ -105,9 +106,9 @@ def _relative_average_spectral_error(preds: Tensor, target: Tensor, window_size:
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> g = torch.manual_seed(22)
-    >>> preds = torch.rand(4, 3, 16, 16)
-    >>> target = torch.rand(4, 3, 16, 16)
+    >>> gen = torch.manual_seed(22)
+    >>> preds = torch.rand(4, 3, 16, 16, generator=gen)
+    >>> target = torch.rand(4, 3, 16, 16, generator=gen)
     >>> _relative_average_spectral_error(preds, target)
     tensor(5114.6641)
 
@@ -122,9 +123,9 @@ def _root_mean_squared_error_using_sliding_window(
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> g = torch.manual_seed(22)
-    >>> preds = torch.rand(4, 3, 16, 16)
-    >>> target = torch.rand(4, 3, 16, 16)
+    >>> gen = torch.manual_seed(22)
+    >>> preds = torch.rand(4, 3, 16, 16, generator=gen)
+    >>> target = torch.rand(4, 3, 16, 16, generator=gen)
     >>> _root_mean_squared_error_using_sliding_window(preds, target)
     tensor(0.3999)
 
@@ -143,10 +144,11 @@ def _spectral_angle_mapper(
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-    >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+    >>> gen = torch.manual_seed(42)
+    >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+    >>> target = torch.rand([16, 3, 16, 16], generator=gen)
     >>> _spectral_angle_mapper(preds, target)
-    tensor(0.5943)
+    tensor(0.5914)
 
     """
     _deprecated_root_import_func("spectral_angle_mapper", "image")
@@ -169,7 +171,8 @@ def _multiscale_structural_similarity_index_measure(
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> preds = torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
+    >>> gen = torch.manual_seed(42)
+    >>> preds = torch.rand([3, 3, 256, 256], generator=gen)
     >>> target = preds * 0.75
     >>> _multiscale_structural_similarity_index_measure(preds, target, data_range=1.0)
     tensor(0.9627)

src/torchmetrics/functional/image/ergas.py

@@ -62,7 +62,8 @@ def _ergas_compute(
             - ``'none'`` or ``None``: no reduction will be applied
 
     Example:
-        >>> preds = torch.rand([16, 1, 16, 16], generator=torch.manual_seed(42))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand([16, 1, 16, 16], generator=gen)
         >>> target = preds * 0.75
         >>> preds, target = _ergas_update(preds, target)
         >>> torch.round(_ergas_compute(preds, target))
@@ -111,7 +112,8 @@ def error_relative_global_dimensionless_synthesis(
 
     Example:
         >>> from torchmetrics.functional.image import error_relative_global_dimensionless_synthesis
-        >>> preds = torch.rand([16, 1, 16, 16], generator=torch.manual_seed(42))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand([16, 1, 16, 16], generator=gen)
         >>> target = preds * 0.75
         >>> ergds = error_relative_global_dimensionless_synthesis(preds, target)
         >>> torch.round(ergds)

src/torchmetrics/functional/image/sam.py

@@ -65,11 +65,12 @@ def _sam_compute(
             - ``'none'`` or ``None``: no reduction will be applied
 
     Example:
-        >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-        >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+        >>> target = torch.rand([16, 3, 16, 16], generator=gen)
         >>> preds, target = _sam_update(preds, target)
         >>> _sam_compute(preds, target)
-        tensor(0.5943)
+        tensor(0.5914)
 
     """
     dot_product = (preds * target).sum(dim=1)
@@ -106,10 +107,11 @@ def spectral_angle_mapper(
 
     Example:
         >>> from torchmetrics.functional.image import spectral_angle_mapper
-        >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-        >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+        >>> target = torch.rand([16, 3, 16, 16], generator=gen)
         >>> spectral_angle_mapper(preds, target)
-        tensor(0.5943)
+        tensor(0.5914)
 
     References:
         [1] Roberta H. Yuhas, Alexander F. H. Goetz and Joe W. Boardman, "Discrimination among semi-arid

src/torchmetrics/functional/image/ssim.py

@@ -502,7 +502,8 @@ def multiscale_structural_similarity_index_measure(
 
     Example:
         >>> from torchmetrics.functional.image import multiscale_structural_similarity_index_measure
-        >>> preds = torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand([3, 3, 256, 256], generator=gen)
         >>> target = preds * 0.75
         >>> multiscale_structural_similarity_index_measure(preds, target, data_range=1.0)
         tensor(0.9627)

src/torchmetrics/functional/multimodal/clip_score.py

@@ -151,7 +151,7 @@ def clip_score(
         >>> _ = torch.manual_seed(42)
         >>> from torchmetrics.functional.multimodal import clip_score
         >>> score = clip_score(torch.randint(255, (3, 224, 224)), "a photo of a cat", "openai/clip-vit-base-patch16")
-        >>> print(score.detach())
+        >>> score.detach()
         tensor(24.4255)
 
     """

src/torchmetrics/functional/text/_deprecated.py

@@ -246,11 +246,12 @@ def _perplexity(preds: Tensor, target: Tensor, ignore_index: Optional[int] = Non
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> preds = torch.rand(2, 8, 5, generator=torch.manual_seed(22))
-    >>> target = torch.randint(5, (2, 8), generator=torch.manual_seed(22))
+    >>> gen = torch.manual_seed(42)
+    >>> preds = torch.rand(2, 8, 5, generator=gen)
+    >>> target = torch.randint(5, (2, 8), generator=gen)
     >>> target[0, 6:] = -100
     >>> _perplexity(preds, target, ignore_index=-100)
-    tensor(5.2545)
+    tensor(5.8540)
 
     """
     _deprecated_root_import_func("perplexity", "text")

src/torchmetrics/functional/text/perplexity.py

@@ -136,11 +136,12 @@ def perplexity(preds: Tensor, target: Tensor, ignore_index: Optional[int] = None
 
     Examples:
         >>> import torch
-        >>> preds = torch.rand(2, 8, 5, generator=torch.manual_seed(22))
-        >>> target = torch.randint(5, (2, 8), generator=torch.manual_seed(22))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand(2, 8, 5, generator=gen)
+        >>> target = torch.randint(5, (2, 8), generator=gen)
         >>> target[0, 6:] = -100
         >>> perplexity(preds, target, ignore_index=-100)
-        tensor(5.2545)
+        tensor(5.8540)
 
     """
     total, count = _perplexity_update(preds, target, ignore_index)

src/torchmetrics/image/_deprecated.py

@@ -148,11 +148,12 @@ class _SpectralAngleMapper(SpectralAngleMapper):
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-    >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+    >>> gen = torch.manual_seed(42)
+    >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+    >>> target = torch.rand([16, 3, 16, 16], generator=gen)
     >>> sam = _SpectralAngleMapper()
     >>> sam(preds, target)
-    tensor(0.5943)
+    tensor(0.5914)
 
     """
 

src/torchmetrics/image/kid.py

@@ -151,8 +151,7 @@ class KernelInceptionDistance(Metric):
         >>> imgs_dist2 = torch.randint(100, 255, (100, 3, 299, 299), dtype=torch.uint8)
         >>> kid.update(imgs_dist1, real=True)
         >>> kid.update(imgs_dist2, real=False)
-        >>> kid_mean, kid_std = kid.compute()
-        >>> print((kid_mean, kid_std))
+        >>> kid.compute()
         (tensor(0.0337), tensor(0.0023))
 
     """

src/torchmetrics/image/sam.py

@@ -58,11 +58,12 @@ class SpectralAngleMapper(Metric):
     Example:
         >>> import torch
         >>> from torchmetrics.image import SpectralAngleMapper
-        >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-        >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+        >>> target = torch.rand([16, 3, 16, 16], generator=gen)
         >>> sam = SpectralAngleMapper()
         >>> sam(preds, target)
-        tensor(0.5943)
+        tensor(0.5914)
 
     """
 
@@ -125,8 +126,9 @@ def plot(
             >>> # Example plotting single value
             >>> import torch
             >>> from torchmetrics.image import SpectralAngleMapper
-            >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-            >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+            >>> gen = torch.manual_seed(42)
+            >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+            >>> target = torch.rand([16, 3, 16, 16], generator=gen)
             >>> metric = SpectralAngleMapper()
             >>> metric.update(preds, target)
             >>> fig_, ax_ = metric.plot()
@@ -137,8 +139,9 @@ def plot(
             >>> # Example plotting multiple values
             >>> import torch
             >>> from torchmetrics.image import SpectralAngleMapper
-            >>> preds = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(42))
-            >>> target = torch.rand([16, 3, 16, 16], generator=torch.manual_seed(123))
+            >>> gen = torch.manual_seed(42)
+            >>> preds = torch.rand([16, 3, 16, 16], generator=gen)
+            >>> target = torch.rand([16, 3, 16, 16], generator=gen)
             >>> metric = SpectralAngleMapper()
             >>> values = [ ]
             >>> for _ in range(10):

src/torchmetrics/image/ssim.py

@@ -270,6 +270,7 @@ class MultiScaleStructuralSimilarityIndexMeasure(Metric):
     Example:
         >>> from torchmetrics.image import MultiScaleStructuralSimilarityIndexMeasure
         >>> import torch
+        >>> gen = torch.manual_seed(42)
         >>> preds = torch.rand([3, 3, 256, 256], generator=torch.manual_seed(42))
         >>> target = preds * 0.75
         >>> ms_ssim = MultiScaleStructuralSimilarityIndexMeasure(data_range=1.0)

src/torchmetrics/multimodal/clip_score.py

@@ -83,12 +83,11 @@ class CLIPScore(Metric):
 
     Example:
         >>> import torch
-        >>> _ = torch.manual_seed(42)
         >>> from torchmetrics.multimodal.clip_score import CLIPScore
         >>> metric = CLIPScore(model_name_or_path="openai/clip-vit-base-patch16")
-        >>> score = metric(torch.randint(255, (3, 224, 224)), "a photo of a cat")
-        >>> print(score.detach())
-        tensor(24.7691)
+        >>> score = metric(torch.randint(255, (3, 224, 224), generator=torch.manual_seed(42)), "a photo of a cat")
+        >>> score.detach()
+        tensor(24.4255)
 
     """
 

src/torchmetrics/text/_deprecated.py

@@ -145,12 +145,13 @@ class _Perplexity(Perplexity):
     """Wrapper for deprecated import.
 
     >>> import torch
-    >>> preds = torch.rand(2, 8, 5, generator=torch.manual_seed(22))
-    >>> target = torch.randint(5, (2, 8), generator=torch.manual_seed(22))
+    >>> gen = torch.manual_seed(42)
+    >>> preds = torch.rand(2, 8, 5, generator=gen)
+    >>> target = torch.randint(5, (2, 8), generator=gen)
     >>> target[0, 6:] = -100
     >>> perp = _Perplexity(ignore_index=-100)
     >>> perp(preds, target)
-    tensor(5.2545)
+    tensor(5.8540)
 
     """
 

src/torchmetrics/text/perplexity.py

@@ -50,12 +50,13 @@ class Perplexity(Metric):
     Examples:
         >>> from torchmetrics.text import Perplexity
         >>> import torch
-        >>> preds = torch.rand(2, 8, 5, generator=torch.manual_seed(22))
-        >>> target = torch.randint(5, (2, 8), generator=torch.manual_seed(22))
+        >>> gen = torch.manual_seed(42)
+        >>> preds = torch.rand(2, 8, 5, generator=gen)
+        >>> target = torch.randint(5, (2, 8), generator=gen)
         >>> target[0, 6:] = -100
         >>> perp = Perplexity(ignore_index=-100)
         >>> perp(preds, target)
-        tensor(5.2545)
+        tensor(5.8540)
 
     """
     is_differentiable = True