27 lines
1003 B
Python
27 lines
1003 B
Python
import mlx.core as mx
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from mlx import nn
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from mflux.models.vae.common.resnet_block_2d import ResnetBlock2D
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from mflux.models.vae.encoder.down_sampler import DownSampler
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class DownBlock3(nn.Module):
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def __init__(self):
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super().__init__()
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# fmt: off
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self.resnets = [
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ResnetBlock2D(norm1=256, conv1_in=256, conv1_out=512, norm2=512, conv2_in=512, conv2_out=512, is_conv_shortcut=True, conv_shortcut_in=256, conv_shortcut_out=512),
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ResnetBlock2D(norm1=512, conv1_in=512, conv1_out=512, norm2=512, conv2_in=512, conv2_out=512),
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]
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# fmt: on
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self.downsamplers = [DownSampler(conv_in=512, conv_out=512)]
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def forward(self, input_array: mx.array) -> mx.array:
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hidden_states = self.resnets[0].forward(input_array)
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hidden_states = self.resnets[1].forward(hidden_states)
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if self.downsamplers is not None:
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hidden_states = self.downsamplers[0].forward(hidden_states)
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return hidden_states
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