Add plotting 19/n (#1662)

* fixes * typing --------- Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com> Co-authored-by: Jirka <jirka.borovec@seznam.cz>
Lightning-AI · Mar 31, 2023 · c553325 · c553325
1 parent b5ac44e
commit c553325
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Showing 83 changed files with 285 additions and 75 deletions.
diff --git a/src/torchmetrics/audio/pesq.py b/src/torchmetrics/audio/pesq.py
@@ -85,8 +85,8 @@ class PerceptualEvaluationSpeechQuality(Metric):
  full_state_update: bool = False
  is_differentiable: bool = False
  higher_is_better: bool = True
- plot_lower_bound = 1.0
- plot_upper_bound = 4.5
+ plot_lower_bound: float = 1.0
+ plot_upper_bound: float = 4.5
 
  def __init__(
  self,

diff --git a/src/torchmetrics/audio/pit.py b/src/torchmetrics/audio/pit.py
@@ -69,8 +69,8 @@ class PermutationInvariantTraining(Metric):
  is_differentiable: bool = True
  sum_pit_metric: Tensor
  total: Tensor
- plot_lower_bound = -10.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = -10.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,

diff --git a/src/torchmetrics/audio/sdr.py b/src/torchmetrics/audio/sdr.py
@@ -85,8 +85,8 @@ class SignalDistortionRatio(Metric):
  full_state_update: bool = False
  is_differentiable: bool = True
  higher_is_better: bool = True
- plot_lower_bound = -20.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = -20.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -195,8 +195,8 @@ class ScaleInvariantSignalDistortionRatio(Metric):
  higher_is_better = True
  sum_si_sdr: Tensor
  total: Tensor
- plot_lower_bound = -40.0
- plot_upper_bound = 20.0
+ plot_lower_bound: float = -40.0
+ plot_upper_bound: float = 20.0
 
  def __init__(
  self,

diff --git a/src/torchmetrics/audio/snr.py b/src/torchmetrics/audio/snr.py
@@ -64,8 +64,8 @@ class SignalNoiseRatio(Metric):
  higher_is_better: bool = True
  sum_snr: Tensor
  total: Tensor
- plot_lower_bound = -20.0
- plot_upper_bound = 5.0
+ plot_lower_bound: float = -20.0
+ plot_upper_bound: float = 5.0
 
  def __init__(
  self,
@@ -164,8 +164,8 @@ class ScaleInvariantSignalNoiseRatio(Metric):
  sum_si_snr: Tensor
  total: Tensor
  higher_is_better = True
- plot_lower_bound = -20.0
- plot_upper_bound = 10.0
+ plot_lower_bound: float = -20.0
+ plot_upper_bound: float = 10.0
 
  def __init__(
  self,

diff --git a/src/torchmetrics/audio/stoi.py b/src/torchmetrics/audio/stoi.py
@@ -77,8 +77,8 @@ class ShortTimeObjectiveIntelligibility(Metric):
  full_state_update: bool = False
  is_differentiable: bool = False
  higher_is_better: bool = True
- plot_lower_bound = -20.0
- plot_upper_bound = 5.0
+ plot_lower_bound: float = -20.0
+ plot_upper_bound: float = 5.0
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/accuracy.py b/src/torchmetrics/classification/accuracy.py
@@ -91,8 +91,8 @@ class BinaryAccuracy(BinaryStatScores):
  is_differentiable = False
  higher_is_better = True
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def compute(self) -> Tensor:
  """Compute accuracy based on inputs passed in to ``update`` previously."""
@@ -237,9 +237,9 @@ class MulticlassAccuracy(MulticlassStatScores):
  is_differentiable = False
  higher_is_better = True
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
- plot_legend_name = "Class"
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def compute(self) -> Tensor:
  """Compute accuracy based on inputs passed in to ``update`` previously."""
@@ -384,9 +384,9 @@ class MultilabelAccuracy(MultilabelStatScores):
  is_differentiable = False
  higher_is_better = True
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
- plot_legend_name = "Label"
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def compute(self) -> Tensor:
  """Compute accuracy based on inputs passed in to ``update`` previously."""

diff --git a/src/torchmetrics/classification/auroc.py b/src/torchmetrics/classification/auroc.py
@@ -99,8 +99,8 @@ class BinaryAUROC(BinaryPrecisionRecallCurve):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = None
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -239,9 +239,9 @@ class MulticlassAUROC(MulticlassPrecisionRecallCurve):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = None
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
- plot_legend_name = "Class"
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,
@@ -386,9 +386,9 @@ class MultilabelAUROC(MultilabelPrecisionRecallCurve):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = None
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
- plot_legend_name = "Label"
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/average_precision.py b/src/torchmetrics/classification/average_precision.py
@@ -106,8 +106,8 @@ class BinaryAveragePrecision(BinaryPrecisionRecallCurve):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = None
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def compute(self) -> Tensor:
  """Compute metric."""
@@ -238,9 +238,9 @@ class MulticlassAveragePrecision(MulticlassPrecisionRecallCurve):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = None
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
- plot_legend_name = "Class"
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,
@@ -390,9 +390,9 @@ class MultilabelAveragePrecision(MultilabelPrecisionRecallCurve):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = None
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
- plot_legend_name = "Label"
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/calibration_error.py b/src/torchmetrics/classification/calibration_error.py
@@ -99,8 +99,8 @@ class BinaryCalibrationError(Metric):
  is_differentiable: bool = False
  higher_is_better: bool = False
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -245,8 +245,9 @@ class MulticlassCalibrationError(Metric):
  is_differentiable: bool = False
  higher_is_better: bool = False
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/cohen_kappa.py b/src/torchmetrics/classification/cohen_kappa.py
@@ -90,8 +90,8 @@ class labels.
  is_differentiable: bool = False
  higher_is_better: bool = True
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -215,8 +215,9 @@ class labels.
  is_differentiable: bool = False
  higher_is_better: bool = True
  full_state_update: bool = False
- plot_lower_bound = 0.0
- plot_upper_bound = 1.0
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/dice.py b/src/torchmetrics/classification/dice.py
@@ -136,6 +136,9 @@ class Dice(Metric):
  is_differentiable: bool = False
  higher_is_better: bool = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  @no_type_check
  def __init__(

diff --git a/src/torchmetrics/classification/exact_match.py b/src/torchmetrics/classification/exact_match.py
@@ -95,6 +95,9 @@ class MulticlassExactMatch(Metric):
  is_differentiable = False
  higher_is_better = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,
@@ -253,6 +256,9 @@ class MultilabelExactMatch(Metric):
  is_differentiable = False
  higher_is_better = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/f_beta.py b/src/torchmetrics/classification/f_beta.py
@@ -109,6 +109,8 @@ class BinaryFBetaScore(BinaryStatScores):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -280,6 +282,9 @@ class MulticlassFBetaScore(MulticlassStatScores):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,
@@ -451,6 +456,9 @@ class MultilabelFBetaScore(MultilabelStatScores):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def __init__(
  self,
@@ -592,6 +600,8 @@ class BinaryF1Score(BinaryFBetaScore):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -752,6 +762,9 @@ class MulticlassF1Score(MulticlassFBetaScore):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,
@@ -912,6 +925,9 @@ class MultilabelF1Score(MultilabelFBetaScore):
  is_differentiable: bool = False
  higher_is_better: Optional[bool] = True
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/group_fairness.py b/src/torchmetrics/classification/group_fairness.py
@@ -98,6 +98,8 @@ class BinaryGroupStatRates(_AbstractGroupStatScores):
  is_differentiable = False
  higher_is_better = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -200,6 +202,8 @@ class BinaryFairness(_AbstractGroupStatScores):
  is_differentiable = False
  higher_is_better = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,

diff --git a/src/torchmetrics/classification/hamming.py b/src/torchmetrics/classification/hamming.py
@@ -101,6 +101,8 @@ class BinaryHammingDistance(BinaryStatScores):
  is_differentiable: bool = False
  higher_is_better: bool = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def compute(self) -> Tensor:
  """Compute metric."""
@@ -248,6 +250,9 @@ class MulticlassHammingDistance(MulticlassStatScores):
  is_differentiable: bool = False
  higher_is_better: bool = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def compute(self) -> Tensor:
  """Compute metric."""
@@ -393,6 +398,9 @@ class MultilabelHammingDistance(MultilabelStatScores):
  is_differentiable: bool = False
  higher_is_better: bool = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Label"
 
  def compute(self) -> Tensor:
  """Compute metric."""

diff --git a/src/torchmetrics/classification/hinge.py b/src/torchmetrics/classification/hinge.py
@@ -84,6 +84,8 @@ class BinaryHingeLoss(Metric):
  is_differentiable: bool = True
  higher_is_better: bool = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
 
  def __init__(
  self,
@@ -219,6 +221,9 @@ class MulticlassHingeLoss(Metric):
  is_differentiable: bool = True
  higher_is_better: bool = False
  full_state_update: bool = False
+ plot_lower_bound: float = 0.0
+ plot_upper_bound: float = 1.0
+ plot_legend_name: str = "Class"
 
  def __init__(
  self,