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@ -462,15 +462,6 @@ class Tempformer(EncoderInterface):
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if subsampling_factor != 4:
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raise NotImplementedError("Support only 'subsampling_factor=4'.")
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# self.encoder_embed converts the input of shape (N, T, num_features)
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# to the shape (N, T//subsampling_factor, d_model).
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# That is, it does two things simultaneously:
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# (1) subsampling: T -> T//subsampling_factor
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# (2) embedding: num_features -> d_model
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self.encoder_embed = Conv2dSubsampling(num_features, d_model)
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self.encoder_pos = RelPositionalEncoding(d_model, dropout)
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self.encoder_layers = num_encoder_layers
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self.d_model = d_model
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self.cnn_module_kernel = cnn_module_kernel
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