forked from ccf-ai-infra/GPUCodeForces
26 lines
633 B
Python
26 lines
633 B
Python
import torch
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import torch.nn as nn
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import torch.nn.functional as F
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class Model(nn.Module):
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def __init__(self, reduction='mean'):
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super().__init__()
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self.reduction = reduction
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def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
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return F.binary_cross_entropy_with_logits(input, target, reduction=self.reduction)
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batch_size = 128
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feature_dim = 1
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def get_inputs():
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pred = torch.randn(batch_size, feature_dim, dtype=torch.float32)
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target = torch.randint(0, 2, (batch_size, feature_dim)).float()
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return [pred, target]
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def get_init_inputs():
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return ['mean'] |