| | |
|---|
| | | ) |
|---|
| | | denominator = torch.sum(mask) |
|---|
| | | return float(numerator) / float(denominator) |
|---|
| | | |
|---|
| | | def compute_accuracy(pad_outputs, pad_targets, ignore_label): |
|---|
| | | """Calculate accuracy. |
|---|
| | | |
|---|
| | | Args: |
|---|
| | | pad_outputs (LongTensor): Prediction tensors (B, Lmax). |
|---|
| | | pad_targets (LongTensor): Target label tensors (B, Lmax). |
|---|
| | | ignore_label (int): Ignore label id. |
|---|
| | | |
|---|
| | | Returns: |
|---|
| | | float: Accuracy value (0.0 - 1.0). |
|---|
| | | |
|---|
| | | """ |
|---|
| | | mask = pad_targets != ignore_label |
|---|
| | | numerator = torch.sum( |
|---|
| | | pad_outputs.masked_select(mask) == pad_targets.masked_select(mask) |
|---|
| | | ) |
|---|
| | | denominator = torch.sum(mask) |
|---|
| | | return numerator.float() / denominator.float() #(FIX:MZY):return torch.Tensor type |
|---|
