Shortcuts

Source code for pytorch_lightning.metrics.classification.hamming_distance

# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Callable, Optional

import torch

from pytorch_lightning.metrics.functional.hamming_distance import _hamming_distance_compute, _hamming_distance_update
from pytorch_lightning.metrics.metric import Metric


[docs]class HammingDistance(Metric): r""" Computes the average `Hamming distance <https://en.wikipedia.org/wiki/Hamming_distance>`_ (also known as Hamming loss) between targets and predictions: .. math:: \text{Hamming distance} = \frac{1}{N \cdot L}\sum_i^N \sum_l^L 1(y_{il} \neq \hat{y_{il}}) Where :math:`y` is a tensor of target values, :math:`\hat{y}` is a tensor of predictions, and :math:`\bullet_{il}` refers to the :math:`l`-th label of the :math:`i`-th sample of that tensor. This is the same as ``1-accuracy`` for binary data, while for all other types of inputs it treats each possible label separately - meaning that, for example, multi-class data is treated as if it were multi-label. Accepts all input types listed in :ref:`extensions/metrics:input types`. Args: threshold: Threshold probability value for transforming probability predictions to binary (0 or 1) predictions, in the case of binary or multi-label inputs. compute_on_step: 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) dist_sync_fn: Callback that performs the allgather operation on the metric state. When ``None``, DDP will be used to perform the all gather. Example: >>> from pytorch_lightning.metrics import HammingDistance >>> target = torch.tensor([[0, 1], [1, 1]]) >>> preds = torch.tensor([[0, 1], [0, 1]]) >>> hamming_distance = HammingDistance() >>> hamming_distance(preds, target) tensor(0.2500) """ def __init__( self, threshold: float = 0.5, compute_on_step: bool = True, dist_sync_on_step: bool = False, process_group: Optional[Any] = None, dist_sync_fn: Callable = None, ): super().__init__( compute_on_step=compute_on_step, dist_sync_on_step=dist_sync_on_step, process_group=process_group, dist_sync_fn=dist_sync_fn, ) self.add_state("correct", default=torch.tensor(0), dist_reduce_fx="sum") self.add_state("total", default=torch.tensor(0), dist_reduce_fx="sum") if not 0 < threshold < 1: raise ValueError("The `threshold` should lie in the (0,1) interval.") self.threshold = threshold
[docs] def update(self, preds: torch.Tensor, target: torch.Tensor): """ Update state with predictions and targets. See :ref:`extensions/metrics:input types` for more information on input types. Args: preds: Predictions from model (probabilities, or labels) target: Ground truth labels """ correct, total = _hamming_distance_update(preds, target, self.threshold) self.correct += correct self.total += total
[docs] def compute(self) -> torch.Tensor: """ Computes hamming distance based on inputs passed in to ``update`` previously. """ return _hamming_distance_compute(self.correct, self.total)

© Copyright Copyright (c) 2018-2021, William Falcon et al... Revision b3b8f95e.

Built with Sphinx using a theme provided by Read the Docs.
Read the Docs v: stable
Versions
latest
stable
1.2.2
1.2.1
1.2.0
1.1.8
1.1.7
1.1.6
1.1.5
1.1.4
1.1.3
1.1.2
1.1.1
1.1.0
1.0.8
1.0.7
1.0.6
1.0.5
1.0.4
1.0.3
1.0.2
1.0.1
1.0.0
0.10.0
0.9.0
0.8.5
0.8.4
0.8.3
0.8.2
0.8.1
0.8.0
0.7.6
0.7.5
0.7.4
0.7.3
0.7.2
0.7.1
0.7.0
0.6.0
0.5.3.2
0.5.3
0.4.9
release-1.2-dev
release-1.0.x
Downloads
pdf
html
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.