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revisit deprecation of is_multiclass #193

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Apr 21, 2021
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revisit deprecation of is_multiclass #193

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afcc813
revisit is_multiclass
Borda Apr 21, 2021
eab47af
prune
Borda Apr 21, 2021
9f05ee8
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Borda Apr 21, 2021
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27 changes: 12 additions & 15 deletions torchmetrics/classification/f_beta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,13 +12,13 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Callable, Optional
from warnings import warn

import torch
from torch import Tensor

from torchmetrics.classification.stat_scores import StatScores
from torchmetrics.functional.classification.f_beta import _fbeta_compute
from torchmetrics.utilities import _deprecation_warn_arg_multilabel


class FBeta(StatScores):
Expand Down Expand Up @@ -114,6 +114,9 @@ class FBeta(StatScores):
dist_sync_fn:
Callback that performs the allgather operation on the metric state. When ``None``, DDP
will be used to perform the allgather.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Raises:
ValueError:
Expand Down Expand Up @@ -143,14 +146,9 @@ def __init__(
dist_sync_on_step: bool = False,
process_group: Optional[Any] = None,
dist_sync_fn: Callable = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
):
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

self.beta = beta
allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
Expand Down Expand Up @@ -269,6 +267,10 @@ class F1(FBeta):
dist_sync_fn:
Callback that performs the allgather operation on the metric state. When ``None``, DDP
will be used to perform the allgather.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.


Example:
>>> from torchmetrics import F1
Expand All @@ -292,14 +294,9 @@ def __init__(
dist_sync_on_step: bool = False,
process_group: Optional[Any] = None,
dist_sync_fn: Callable = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
):
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

super().__init__(
num_classes=num_classes,
Expand Down
26 changes: 11 additions & 15 deletions torchmetrics/classification/precision_recall.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,13 +12,13 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Callable, Optional
from warnings import warn

import torch
from torch import Tensor

from torchmetrics.classification.stat_scores import StatScores
from torchmetrics.functional.classification.precision_recall import _precision_compute, _recall_compute
from torchmetrics.utilities import _deprecation_warn_arg_multilabel


class Precision(StatScores):
Expand Down Expand Up @@ -104,6 +104,9 @@ class Precision(StatScores):
dist_sync_fn:
Callback that performs the allgather operation on the metric state. When ``None``, DDP
will be used to perform the allgather.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Raises:
ValueError:
Expand Down Expand Up @@ -135,14 +138,9 @@ def __init__(
dist_sync_on_step: bool = False,
process_group: Optional[Any] = None,
dist_sync_fn: Callable = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
):
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
if average not in allowed_average:
Expand Down Expand Up @@ -263,6 +261,9 @@ class Recall(StatScores):
dist_sync_fn:
Callback that performs the allgather operation on the metric state. When ``None``, DDP
will be used to perform the allgather.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Raises:
ValueError:
Expand Down Expand Up @@ -294,14 +295,9 @@ def __init__(
dist_sync_on_step: bool = False,
process_group: Optional[Any] = None,
dist_sync_fn: Callable = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
):
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
if average not in allowed_average:
Expand Down
8 changes: 0 additions & 8 deletions torchmetrics/classification/stat_scores.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Callable, Optional, Tuple
from warnings import warn

import numpy as np
import torch
Expand Down Expand Up @@ -146,14 +145,7 @@ def __init__(
dist_sync_on_step: bool = False,
process_group: Optional[Any] = None,
dist_sync_fn: Callable = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
):
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass

super().__init__(
compute_on_step=compute_on_step,
Expand Down
26 changes: 11 additions & 15 deletions torchmetrics/functional/classification/f_beta.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,13 +12,13 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Optional
from warnings import warn

import torch
from torch import Tensor

from torchmetrics.classification.stat_scores import _reduce_stat_scores
from torchmetrics.functional.classification.stat_scores import _stat_scores_update
from torchmetrics.utilities import _deprecation_warn_arg_multilabel
from torchmetrics.utilities.enums import AverageMethod, MDMCAverageMethod


Expand Down Expand Up @@ -82,7 +82,7 @@ def fbeta(
threshold: float = 0.5,
top_k: Optional[int] = None,
multiclass: Optional[bool] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tensor:
r"""
Computes f_beta metric.
Expand Down Expand Up @@ -158,6 +158,9 @@ def fbeta(
than what they appear to be. See the parameter's
:ref:`documentation section <references/modules:using the multiclass parameter>`
for a more detailed explanation and examples.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Return:
The shape of the returned tensor depends on the ``average`` parameter
Expand All @@ -174,12 +177,7 @@ def fbeta(
tensor(0.3333)

"""
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
if average not in allowed_average:
Expand Down Expand Up @@ -222,7 +220,7 @@ def f1(
threshold: float = 0.5,
top_k: Optional[int] = None,
multiclass: Optional[bool] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tensor:
"""
Computes F1 metric. F1 metrics correspond to a equally weighted average of the
Expand Down Expand Up @@ -301,6 +299,9 @@ def f1(
than what they appear to be. See the parameter's
:ref:`documentation section <references/modules:using the multiclass parameter>`
for a more detailed explanation and examples.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Return:
The shape of the returned tensor depends on the ``average`` parameter
Expand All @@ -316,10 +317,5 @@ def f1(
>>> f1(preds, target, num_classes=3)
tensor(0.3333)
"""
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)
return fbeta(preds, target, 1.0, average, mdmc_average, ignore_index, num_classes, threshold, top_k, multiclass)
38 changes: 16 additions & 22 deletions torchmetrics/functional/classification/precision_recall.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,13 +12,13 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Optional, Tuple
from warnings import warn

import torch
from torch import Tensor

from torchmetrics.classification.stat_scores import _reduce_stat_scores
from torchmetrics.functional.classification.stat_scores import _stat_scores_update
from torchmetrics.utilities import _deprecation_warn_arg_multilabel


def _precision_compute(
Expand Down Expand Up @@ -49,7 +49,7 @@ def precision(
threshold: float = 0.5,
top_k: Optional[int] = None,
multiclass: Optional[bool] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tensor:
r"""
Computes `Precision <https://en.wikipedia.org/wiki/Precision_and_recall>`_:
Expand Down Expand Up @@ -124,6 +124,9 @@ def precision(
than what they appear to be. See the parameter's
:ref:`documentation section <references/modules:using the multiclass parameter>`
for a more detailed explanation and examples.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Return:
The shape of the returned tensor depends on the ``average`` parameter
Expand Down Expand Up @@ -154,12 +157,7 @@ def precision(
tensor(0.2500)

"""
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
if average not in allowed_average:
Expand Down Expand Up @@ -220,7 +218,7 @@ def recall(
threshold: float = 0.5,
top_k: Optional[int] = None,
multiclass: Optional[bool] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tensor:
r"""
Computes `Recall <https://en.wikipedia.org/wiki/Precision_and_recall>`_:
Expand Down Expand Up @@ -295,6 +293,9 @@ def recall(
than what they appear to be. See the parameter's
:ref:`documentation section <references/modules:using the multiclass parameter>`
for a more detailed explanation and examples.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Return:
The shape of the returned tensor depends on the ``average`` parameter
Expand Down Expand Up @@ -325,12 +326,7 @@ def recall(
tensor(0.2500)

"""
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
if average not in allowed_average:
Expand Down Expand Up @@ -372,7 +368,7 @@ def precision_recall(
threshold: float = 0.5,
top_k: Optional[int] = None,
multiclass: Optional[bool] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
multilabel: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tuple[Tensor, Tensor]:
r"""
Computes `Precision and Recall <https://en.wikipedia.org/wiki/Precision_and_recall>`_:
Expand Down Expand Up @@ -450,6 +446,9 @@ def precision_recall(
than what they appear to be. See the parameter's
:ref:`documentation section <references/modules:using the multiclass parameter>`
for a more detailed explanation and examples.
multilabel:
.. deprecated:: 0.3
Argument will not have any effect and will be removed in v0.4, please use ``multiclass`` intead.

Return:
The function returns a tuple with two elements: precision and recall. Their shape
Expand Down Expand Up @@ -481,12 +480,7 @@ def precision_recall(
(tensor(0.2500), tensor(0.2500))

"""
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass
_deprecation_warn_arg_multilabel(multilabel)

allowed_average = ["micro", "macro", "weighted", "samples", "none", None]
if average not in allowed_average:
Expand Down
15 changes: 0 additions & 15 deletions torchmetrics/functional/classification/stat_scores.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Optional, Tuple
from warnings import warn

import torch
from torch import Tensor, tensor
Expand Down Expand Up @@ -85,14 +84,7 @@ def _stat_scores_update(
threshold: float = 0.5,
multiclass: Optional[bool] = None,
ignore_index: Optional[int] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tuple[Tensor, Tensor, Tensor, Tensor]:
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass

preds, target, _ = _input_format_classification(
preds, target, threshold=threshold, num_classes=num_classes, multiclass=multiclass, top_k=top_k
Expand Down Expand Up @@ -155,7 +147,6 @@ def stat_scores(
threshold: float = 0.5,
multiclass: Optional[bool] = None,
ignore_index: Optional[int] = None,
is_multiclass: Optional[bool] = None, # todo: deprecated, remove in v0.4
) -> Tensor:
"""Computes the number of true positives, false positives, true negatives, false negatives.
Related to `Type I and Type II errors <https://en.wikipedia.org/wiki/Type_I_and_type_II_errors>`__
Expand Down Expand Up @@ -280,12 +271,6 @@ def stat_scores(
>>> stat_scores(preds, target, reduce='micro')
tensor([2, 2, 6, 2, 4])
"""
if is_multiclass is not None and multiclass is None:
warn(
"Argument `is_multiclass` was deprecated in v0.3.0 and will be removed in v0.4. Use `multiclass`.",
DeprecationWarning
)
multiclass = is_multiclass

if reduce not in ["micro", "macro", "samples"]:
raise ValueError(f"The `reduce` {reduce} is not valid.")
Expand Down
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