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34 lines
1.2 KiB
34 lines
1.2 KiB
import torch
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from colossalai.constants import INPUT_GROUP_3D, WEIGHT_GROUP_3D
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from colossalai.nn.layer.parallel_3d import reduce_by_batch_3d, split_tensor_3d
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from colossalai.nn.layer.parallel_3d._utils import get_parallel_mode_from_env
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from torch import nn
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from ._utils import calc_acc
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class Accuracy3D(nn.Module):
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"""Accuracy for 3D parallelism
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"""
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def __init__(self):
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super().__init__()
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self.input_parallel_mode = get_parallel_mode_from_env(INPUT_GROUP_3D)
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self.weight_parallel_mode = get_parallel_mode_from_env(WEIGHT_GROUP_3D)
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def forward(self, logits, targets):
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"""Calculate the accuracy of predicted labels.
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Args:
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logits (:class:`torch.tensor`): Predicted labels.
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targets (:class:`torch.tensor`): True labels from data.
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Returns:
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float: the accuracy of prediction.
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"""
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with torch.no_grad():
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targets = split_tensor_3d(targets, 0, self.weight_parallel_mode)
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targets = split_tensor_3d(targets, 0, self.input_parallel_mode)
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correct = calc_acc(logits, targets)
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correct = reduce_by_batch_3d(correct, self.input_parallel_mode, self.weight_parallel_mode)
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return correct
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