metric.py

25 E501: line too long (82 > 79 characters) (and 15 similar)
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  28 Given a list/numpy array/Tensor of metrics, computes the worst-case metric
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  40 Used to name the key in the results dictionaries returned by the metric.
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  47 The name of the key in the results dictionary returned by Metric.compute().
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  48 This should correspond to the aggregate metric computed on all of y_pred and y_true,
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  81 - return_dict (bool): Whether to return the output as a dictionary or a tensor
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  83 - metric (0-dim tensor): metric. If the inputs are empty, returns tensor(0.)
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  85 - results (dict): Dictionary of results, mapping metric.agg_metric_field to avg_metric
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  99 def compute_group_wise(self, y_pred, y_true, g, n_groups, return_dict=True):
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  107 - return_dict (bool): Whether to return the output as a dictionary or a tensor
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  109 - group_metrics (Tensor): tensor of size (n_groups, ) including the average metric for each group
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  110 - group_counts (Tensor): tensor of size (n_groups, ) including the group count
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  116 group_metrics, group_counts, worst_group_metric = self._compute_group_wise(y_pred, y_true, g, n_groups)
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  120 results[self.group_metric_field(group_idx)] = group_metrics[group_idx].item()
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  121 results[self.group_count_field(group_idx)] = group_counts[group_idx].item()
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  163 Given a list/numpy array/Tensor of metrics, computes the worst-case metric
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  186 group_metrics, group_counts = avg_over_groups(element_wise_metrics, g, n_groups)
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  193 The name of the key in the results dictionary returned by Metric.compute().
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  203 - return_dict (bool): Whether to return the output as a dictionary or a tensor
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  207 - results (dict): Dictionary of results, mapping metric.name to element_wise_metrics
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  212 assert element_wise_metrics.dim()==1 and element_wise_metrics.numel()==batch_size
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  219 flattened_metrics = self.compute_element_wise(y_pred, y_true, return_dict=False)
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  232 flattened_metrics, _ = self.compute_flattened(y_pred, y_true, return_dict=False)
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  239 flattened_metrics, indices = self.compute_flattened(y_pred, y_true, return_dict=False)
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  241 group_metrics, group_counts = avg_over_groups(flattened_metrics, flattened_g, n_groups)
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  252 flattened_metrics = self._compute_flattened(flattened_y_pred, flattened_y_true)
2 E225: missing whitespace around operator
- Missing whitespace around operator (in 2 places):
  212 assert element_wise_metrics.dim()==1 and element_wise_metrics.numel()==batch_size