gluonts.mx.block.enc2dec module¶
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class
gluonts.mx.block.enc2dec.
FutureFeatIntegratorEnc2Dec
(**kwargs)[source]¶ Bases:
gluonts.mx.block.enc2dec.Seq2SeqEnc2Dec
Integrates the encoder_output_dynamic and future_features_dynamic into one and passes them through as the dynamic input to the decoder.
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hybrid_forward
(F, encoder_output_static: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], encoder_output_dynamic: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], future_features_dynamic: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]) → Tuple[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]][source]¶ - Parameters
encoder_output_static – shape (batch_size, channels_seq[-1] + 1) or (N, C)
encoder_output_dynamic – shape (batch_size, sequence_length, channels_seq[-1] + 1) or (N, T, C)
future_features_dynamic – shape (batch_size, sequence_length, prediction_length=decoder_length, num_feat_dynamic) or (N, T, P, C`)
- Returns
Tensor – shape (batch_size, channels_seq[-1] + 1) or (N, C)
Tensor – shape (batch_size, prediction_length=decoder_length, channels_seq[-1] + 1 + decoder_length * num_feat_dynamic) or (N, T, C)
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class
gluonts.mx.block.enc2dec.
PassThroughEnc2Dec
(**kwargs)[source]¶ Bases:
gluonts.mx.block.enc2dec.Seq2SeqEnc2Dec
Simplest class for passing encoder tensors do decoder. Passes through tensors, except that future_features_dynamic is dropped.
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hybrid_forward
(F, encoder_output_static: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], encoder_output_dynamic: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], future_features_dynamic: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]) → Tuple[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]][source]¶ - Parameters
encoder_output_static – shape (batch_size, channels_seq[-1] + 1) or (N, C)
encoder_output_dynamic – shape (batch_size, sequence_length, channels_seq[-1] + 1) or (N, T, C)
future_features_dynamic – shape (batch_size, sequence_length, prediction_length=decoder_length, num_feat_dynamic) or (N, T, P, C`)
- Returns
Tensor – shape (batch_size, channels_seq[-1] + 1) or (N, C)
Tensor – shape (batch_size, sequence_length, channels_seq[-1] + 1) or (N, T, C)
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class
gluonts.mx.block.enc2dec.
Seq2SeqEnc2Dec
(**kwargs)[source]¶ Bases:
mxnet.gluon.block.HybridBlock
Abstract class for any module that pass encoder to decoder, such as attention network.
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hybrid_forward
(F, encoder_output_static: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], encoder_output_dynamic: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], future_features_dynamic: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]) → Tuple[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]][source]¶ - Parameters
encoder_output_static – shape (batch_size, channels_seq[-1] + 1) or (N, C)
encoder_output_dynamic – shape (batch_size, sequence_length, channels_seq[-1] + 1) or (N, T, C)
future_features_dynamic – shape (batch_size, sequence_length, prediction_length=decoder_length, num_feat_dynamic) or (N, T, P, C`)
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