Searched refs:total_cm (Results 1 – 3 of 3) sorted by relevance
| /external/tensorflow/tensorflow/python/ops/ |
| D | metrics_impl.py | 255 total_cm = metric_variable(
276 update_op = state_ops.assign_add(total_cm, current_cm)
277 return total_cm, update_op
1163 total_cm, update_op = _streaming_confusion_matrix(labels, predictions,
1166 def compute_mean_iou(_, total_cm): argument
1169 math_ops.reduce_sum(total_cm, 0), dtypes.float32)
1171 math_ops.reduce_sum(total_cm, 1), dtypes.float32)
1172 cm_diag = math_ops.cast(array_ops.diag_part(total_cm), dtypes.float32)
1197 metrics_collections, compute_mean_iou, total_cm)
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| /external/tensorflow/tensorflow/python/keras/ |
| D | metrics.py | 2838 self.total_cm = self.add_weight(
2879 return self.total_cm.assign_add(current_cm)
2884 math_ops.reduce_sum(self.total_cm, axis=0), dtype=self._dtype)
2886 math_ops.reduce_sum(self.total_cm, axis=1), dtype=self._dtype)
2888 array_ops.tensor_diag_part(self.total_cm), dtype=self._dtype)
2906 K.set_value(self.total_cm, np.zeros((self.num_classes, self.num_classes)))
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| D | metrics_test.py | 2314 self.assertArrayNear(self.evaluate(m_obj.total_cm)[0], [1, 0], 1e-1)
2315 self.assertArrayNear(self.evaluate(m_obj.total_cm)[1], [3, 0], 1e-1)
2317 self.assertArrayNear(self.evaluate(m_obj.total_cm)[0], [1, 0], 1e-1)
2318 self.assertArrayNear(self.evaluate(m_obj.total_cm)[1], [3, 0], 1e-1)
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