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| # *************************************************************************** # | |
| # # | |
| # logits.py # | |
| # # | |
| # By: Widium <ebennace@student.42lausanne.ch> # | |
| # Github : https://github.com/widium # | |
| # # | |
| # Created: 2023/04/24 10:34:02 by Widium # | |
| # Updated: 2023/04/24 10:34:02 by Widium # | |
| # # | |
| # **************************************************************************** # | |
| import torch | |
| from torch import Tensor | |
| def logits_to_class_integer(logits : Tensor)->Tensor: | |
| """Convert Logits to Class Integers for Binary or Multi Classification | |
| Check the shape of Logits fo define type of Classification | |
| Args: | |
| logits (Tensor): 2 dimensional Tensor with logits | |
| Returns: | |
| Tensor: Scalar of class prediction | |
| """ | |
| if (len(logits.shape) == 1 or logits.shape[1] == 1): | |
| # BinaryClass | |
| y_preds = torch.sigmoid(logits) | |
| y_preds = torch.round(y_preds) | |
| elif (logits.shape[1] > 1): | |
| # MultiClass | |
| y_preds = torch.softmax(logits, dim=1) | |
| y_preds = torch.argmax(y_preds, dim=1) | |
| return (y_preds) | |
| # **************************************************************************** # | |
| def logits_to_probs(logits : Tensor)->Tensor: | |
| """Convert logits to Probability of Class Prediction | |
| Args: | |
| logits (Tensor): 2 dimensional Tensor with logits | |
| Returns: | |
| Tensor: Float Scalar of class Probability | |
| """ | |
| if (len(logits.shape) == 1 or logits.shape[1] == 1): | |
| # BinaryClass | |
| y_probs = torch.sigmoid(logits) | |
| if y_probs < 0.5: | |
| y_probs = 1 - y_probs | |
| elif (logits.shape[1] > 1): | |
| # MultiClass | |
| y_preds = torch.softmax(logits, dim=1) | |
| y_probs = y_preds.max() | |
| return (y_probs * 100) |