classy_vision/meters/accuracy_meter.py [155:178]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        self._curr_sample_count += model_output.shape[0]

    def reset(self):
        self._total_correct_predictions_k = torch.zeros(len(self._topk))
        self._total_sample_count = torch.zeros(1)
        self._curr_correct_predictions_k = torch.zeros(len(self._topk))
        self._curr_sample_count = torch.zeros(1)

    def validate(self, model_output_shape, target_shape):
        assert (
            len(model_output_shape) == 2
        ), "model_output_shape must be (B, C) \
            Found shape {}".format(
            model_output_shape
        )
        assert (
            len(target_shape) > 0 and len(target_shape) < 3
        ), "target_shape must be (B) or (B, C) \
            Found shape {}".format(
            target_shape
        )
        assert (
            max(self._topk) < model_output_shape[1]
        ), "k in top_k, for \
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



classy_vision/meters/precision_meter.py [159:182]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        self._curr_sample_count += model_output.shape[0]

    def reset(self):
        self._total_correct_predictions_k = torch.zeros(len(self._topk))
        self._total_sample_count = torch.zeros(1)
        self._curr_correct_predictions_k = torch.zeros(len(self._topk))
        self._curr_sample_count = torch.zeros(1)

    def validate(self, model_output_shape, target_shape):
        assert (
            len(model_output_shape) == 2
        ), "model_output_shape must be (B, C) \
            Found shape {}".format(
            model_output_shape
        )
        assert (
            len(target_shape) > 0 and len(target_shape) < 3
        ), "target_shape must be (B) or (B, C) \
            Found shape {}".format(
            target_shape
        )
        assert (
            max(self._topk) < model_output_shape[1]
        ), "k in top_k, for \
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -