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78 lines
3.1 KiB
Python
78 lines
3.1 KiB
Python
import numpy as np
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import paddle
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from paddlevideo.utils import get_logger
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from .base import BaseMetric
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from .registry import METRIC
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logger = get_logger("paddlevideo")
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@METRIC.register
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class DepthMetric(BaseMetric):
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def __init__(self, data_size, batch_size, log_interval=1):
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"""prepare for metrics
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"""
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super().__init__(data_size, batch_size, log_interval)
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self.abs_rel = []
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self.sq_rel = []
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self.rmse = []
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self.rmse_log = []
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self.a1 = []
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self.a2 = []
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self.a3 = []
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def update(self, batch_id, data, outputs):
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"""update metrics during each iter
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"""
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abs_rel, sq_rel, rmse, rmse_log, a1, a2, a3 = outputs['abs_rel'], outputs['sq_rel'], outputs['rmse'], \
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outputs['rmse_log'], outputs['a1'], outputs['a2'],outputs['a3']
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# preds ensemble
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if self.world_size > 1:
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abs_rel = paddle.distributed.all_reduce(
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outputs['abs_rel'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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sq_rel = paddle.distributed.all_reduce(
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outputs['sq_rel'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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rmse = paddle.distributed.all_reduce(
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outputs['rmse'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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rmse_log = paddle.distributed.all_reduce(
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outputs['rmse_log'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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a1 = paddle.distributed.all_reduce(
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outputs['a1'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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a2 = paddle.distributed.all_reduce(
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outputs['a2'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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a3 = paddle.distributed.all_reduce(
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outputs['a3'],
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op=paddle.distributed.ReduceOp.SUM) / self.world_size
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self.abs_rel.append(abs_rel)
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self.sq_rel.append(sq_rel)
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self.rmse.append(rmse)
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self.rmse_log.append(rmse_log)
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self.a1.append(a1)
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self.a2.append(a2)
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self.a3.append(a3)
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if batch_id % self.log_interval == 0:
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logger.info("[TEST] Processing batch {}/{} ...".format(
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batch_id,
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self.data_size // (self.batch_size * self.world_size)))
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def accumulate(self):
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"""accumulate metrics when finished all iters.
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"""
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logger.info(
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'[TEST] finished, abs_rel= {}, sq_rel= {} , rmse= {}, rmse_log= {},'
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'a1= {}, a2= {}, a3= {}'.format(np.mean(np.array(self.abs_rel)),
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np.mean(np.array(self.sq_rel)),
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np.mean(np.array(self.rmse)),
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np.mean(np.array(self.rmse_log)),
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np.mean(np.array(self.a1)),
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np.mean(np.array(self.a2)),
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np.mean(np.array(self.a3))))
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