Merge branch 'master' into doc/gov

.pre-commit-config.yaml

@@ -27,10 +27,11 @@ repos:
  hooks:
  - id: end-of-file-fixer
  - id: trailing-whitespace
+ # - id: check-json
  - id: check-yaml
+ - id: check-toml
  - id: check-docstring-first
  - id: check-executables-have-shebangs
- - id: check-toml
  - id: check-case-conflict
  - id: check-added-large-files
  args: ['--maxkb=250', '--enforce-all']

torchmetrics/aggregation.py

@@ -35,13 +35,12 @@ class BaseAggregator(Metric):
 
  compute_on_step:
  Forward only calls ``update()`` and returns None if this is
- set to False. default: True
+ set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
  Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state.
  When `None`, DDP will be used to perform the allgather.
@@ -122,13 +121,12 @@ class MaxMetric(BaseAggregator):
 
  compute_on_step:
  Forward only calls ``update()`` and returns None if this is
- set to False. default: True
+ set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
  Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state.
  When `None`, DDP will be used to perform the allgather.
@@ -188,13 +186,12 @@ class MinMetric(BaseAggregator):
 
  compute_on_step:
  Forward only calls ``update()`` and returns None if this is
- set to False. default: True
+ set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
  Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state.
  When `None`, DDP will be used to perform the allgather.
@@ -254,13 +251,12 @@ class SumMetric(BaseAggregator):
 
  compute_on_step:
  Forward only calls ``update()`` and returns None if this is
- set to False. default: True
+ set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
  Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state.
  When `None`, DDP will be used to perform the allgather.
@@ -313,13 +309,12 @@ class CatMetric(BaseAggregator):
 
  compute_on_step:
  Forward only calls ``update()`` and returns None if this is
- set to False. default: True
+ set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
  Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state.
  When `None`, DDP will be used to perform the allgather.
@@ -377,13 +372,12 @@ class MeanMetric(BaseAggregator):
 
  compute_on_step:
  Forward only calls ``update()`` and returns None if this is
- set to False. default: True
+ set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
  Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state.
  When `None`, DDP will be used to perform the allgather.

torchmetrics/audio/pit.py

@@ -37,12 +37,12 @@ class PIT(Metric):
  the function to find the best permutation, can be 'min' or 'max', i.e. the smaller the better
  or the larger the better.
  compute_on_step:
- Forward only calls ``update()`` and returns None if this is set to False. default: True
+ Forward only calls ``update()`` and returns None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When `None`, DDP
  will be used to perform the allgather.

torchmetrics/audio/sdr.py

@@ -45,12 +45,12 @@ class SDR(Metric):
  This can help stabilize the metric in the case where some of the reference
  signals may sometimes be zero
  compute_on_step:
- Forward only calls ``update()`` and returns None if this is set to False. default: True
+ Forward only calls ``update()`` and returns None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When `None`, DDP
  will be used to perform the allgather.

torchmetrics/audio/si_sdr.py

@@ -32,12 +32,12 @@ class SI_SDR(Metric):
  zero_mean:
  if to zero mean target and preds or not
  compute_on_step:
- Forward only calls ``update()`` and returns None if this is set to False. default: True
+ Forward only calls ``update()`` and returns None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When `None`, DDP
  will be used to perform the allgather.

torchmetrics/audio/si_snr.py

@@ -29,12 +29,12 @@ class SI_SNR(Metric):
 
  Args:
  compute_on_step:
- Forward only calls ``update()`` and returns None if this is set to False. default: True
+ Forward only calls ``update()`` and returns None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When `None`, DDP
  will be used to perform the allgather.

torchmetrics/audio/snr.py

@@ -38,12 +38,12 @@ class SNR(Metric):
  zero_mean:
  if to zero mean target and preds or not
  compute_on_step:
- Forward only calls ``update()`` and returns None if this is set to False. default: True
+ Forward only calls ``update()`` and returns None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When `None`, DDP
  will be used to perform the allgather.

torchmetrics/audio/stoi.py

@@ -45,12 +45,12 @@ class STOI(Metric):
  extended:
  whether to use the extended STOI described in [4]
  compute_on_step:
- Forward only calls ``update()`` and returns None if this is set to False. default: True
+ Forward only calls ``update()`` and returns None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When `None`, DDP
  will be used to perform the allgather.

torchmetrics/classification/auc.py

@@ -38,7 +38,7 @@ class AUC(Metric):
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the ``allgather`` operation on the metric state. When ``None``, DDP
  will be used to perform the ``allgather``.

torchmetrics/classification/auroc.py

@@ -63,12 +63,13 @@ class AUROC(Metric):
  If not ``None``, calculates standardized partial AUC over the
  range [0, max_fpr]. Should be a float between 0 and 1.
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
+
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When ``None``, DDP
  will be used to perform the allgather

torchmetrics/classification/avg_precision.py

@@ -58,12 +58,12 @@ class AveragePrecision(Metric):
  the metric for every class.
 
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Example (binary case):
  >>> from torchmetrics import AveragePrecision

torchmetrics/classification/binned_precision_recall.py

@@ -62,12 +62,12 @@ class BinnedPrecisionRecallCurve(Metric):
  It is used for computation will lead to more detailed curve and accurate estimates,
  but will be slower and consume more memory.
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Raises:
  ValueError:
@@ -210,9 +210,9 @@ class BinnedAveragePrecision(BinnedPrecisionRecallCurve):
  It is used for computation will lead to more detailed curve and accurate estimates,
  but will be slower and consume more memory
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Raises:
  ValueError:
@@ -262,9 +262,9 @@ class BinnedRecallAtFixedPrecision(BinnedPrecisionRecallCurve):
  It is used for computation will lead to more detailed curve and accurate estimates,
  but will be slower and consume more memory
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Raises:
  ValueError:

torchmetrics/classification/calibration_error.py

@@ -57,7 +57,6 @@ class CalibrationError(Metric):
  dist_sync_on_step: Synchronize metric state across processes at each ``forward()``
  before returning the value at the step
  process_group: Specify the process group on which synchronization is called.
- default: None (which selects the entire world)
  """
  DISTANCES = {"l1", "l2", "max"}
  higher_is_better = False

torchmetrics/classification/cohen_kappa.py

@@ -59,14 +59,14 @@ class labels.
  of binary or multi-label inputs. Default value of 0.5 corresponds to input being probabilities.
 
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
 
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
 
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Example:
  >>> from torchmetrics import CohenKappa

torchmetrics/classification/confusion_matrix.py

@@ -56,12 +56,12 @@ class ConfusionMatrix(Metric):
  multilabel:
  determines if data is multilabel or not.
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Example (binary data):
  >>> from torchmetrics import ConfusionMatrix

torchmetrics/classification/jaccard.py

@@ -65,7 +65,7 @@ class JaccardIndex(ConfusionMatrix):
  Synchronize metric state across processes at each ``forward()``
  before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Example:
  >>> from torchmetrics import JaccardIndex

torchmetrics/classification/matthews_corrcoef.py

@@ -52,14 +52,14 @@ class MatthewsCorrcoef(Metric):
  Args:
  num_classes: Number of classes in the dataset.
  threshold:
- Threshold value for binary or multi-label probabilites. default: 0.5
+ Threshold value for binary or multi-label probabilites.
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When ``None``, DDP
  will be used to perform the allgather

torchmetrics/classification/precision_recall_curve.py

@@ -44,12 +44,12 @@ class PrecisionRecallCurve(Metric):
  this argument should not be set as we iteratively change it in the
  range [0,num_classes-1]
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
 
  Example (binary case):
  >>> from torchmetrics import PrecisionRecallCurve

torchmetrics/classification/roc.py

@@ -45,12 +45,12 @@ class ROC(Metric):
  this argument should not be set as we iteratively change it in the
  range [0,num_classes-1]
  compute_on_step:
- Forward only calls ``update()`` and return None if this is set to False. default: True
+ Forward only calls ``update()`` and return None if this is set to False.
  dist_sync_on_step:
  Synchronize metric state across processes at each ``forward()``
- before returning the value at the step. default: False
+ before returning the value at the step.
  process_group:
- Specify the process group on which synchronization is called. default: None (which selects the entire world)
+ Specify the process group on which synchronization is called.
  dist_sync_fn:
  Callback that performs the allgather operation on the metric state. When ``None``, DDP
  will be used to perform the allgather