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__version__ = '0.0.1' | ||
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from .core import * | ||
from .layers import * |
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from .nac_cell import NacCell | ||
from .nalu_cell import NaluCell |
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from .nalu_layer import NaluLayer |
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from torch.nn import Sequential | ||
from torch import nn | ||
from nalu.core.nalu_cell import NaluCell | ||
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class NaluLayer(nn.Module): | ||
def __init__(self, input_shape, output_shape, n_layers, hidden_shape): | ||
super().__init__() | ||
self.input_shape = input_shape | ||
self.output_shape = output_shape | ||
self.n_layers = n_layers | ||
self.hidden_shape = hidden_shape | ||
layers = [NaluCell(hidden_shape if n > 0 else input_shape, | ||
hidden_shape if n < n_layers - 1 else output_shape) for n in range(n_layers)] | ||
self.model = Sequential(*layers) | ||
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def forward(self, data): | ||
return self.model(data) |
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torch | ||
numpy | ||
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