27 lines
776 B
Python
27 lines
776 B
Python
import logging
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import torch
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import torch.nn as nn
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from torch import Tensor
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logger = logging.getLogger(__name__)
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class PyTorchMLPModel(nn.Module):
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def __init__(self, input_dim: int, hidden_dim: int, output_dim: int):
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super(PyTorchMLPModel, self).__init__()
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self.input_layer = nn.Linear(input_dim, hidden_dim)
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self.hidden_layer = nn.Linear(hidden_dim, hidden_dim)
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self.output_layer = nn.Linear(hidden_dim, output_dim)
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self.relu = nn.ReLU()
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self.dropout = nn.Dropout(p=0.2)
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def forward(self, x: Tensor) -> Tensor:
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x = self.relu(self.input_layer(x))
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x = self.dropout(x)
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x = self.relu(self.hidden_layer(x))
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x = self.dropout(x)
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logits = self.output_layer(x)
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return logits
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