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Implementation:Microsoft Onnxruntime CPU LSTM Forward

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Knowledge Sources
Domains Training, CPU_Kernels
Last Updated 2026-02-10 04:00 GMT

Overview

Concrete tool for running the LSTM forward pass during training on CPU in the ONNX Runtime training framework.

Description

This file implements the LSTMTraining kernel, which wraps the existing UniDirectionalLstm forward implementation with training mode enabled. It parses LSTM inputs and attributes via the lstm::LSTMInputs and lstm::LSTMOutputs utilities, then invokes the deep CPU LSTM computation. The kernel outputs all hidden states, the final hidden state, the final cell state, all cell states, and the iofc gate activations (input, output, forget, cell) needed for gradient computation in the backward pass. It is registered under the kMSDomain with opset version 1.

Usage

This kernel is invoked during the forward pass of LSTM training. The computed gate activations (iofc), all hidden states, and all cell states are stored as outputs and later consumed by the LSTMGrad kernel during backpropagation.

Code Reference

Source Location

Signature

template <typename T>
Status LSTMTraining<T>::Compute(OpKernelContext* context) const;

Import

#include "orttraining/orttraining/training_ops/cpu/rnn/lstm.h"

I/O Contract

Inputs

Name Type Required Description
X Tensor(float) Yes Input sequence [seq_length, batch_size, input_size]
W Tensor(float) Yes Weights [directions, 4*H, input_size]
R Tensor(float) Yes Recurrence weights [directions, 4*H, H]
B Tensor(float) No Bias [directions, 8*H]
sequence_lengths Tensor(int) No Per-sequence lengths (not supported)
initial_h Tensor(float) No Initial hidden state [directions, batch, H]
initial_c Tensor(float) No Initial cell state [directions, batch, H]
P Tensor(float) No Peephole weights [directions, 3*H]

Outputs

Name Type Description
HAll Tensor(float) All hidden states [seq_length, directions, batch, H]
Ht Tensor(float) Final hidden state [directions, batch, H]
Ct Tensor(float) Final cell state [directions, batch, H]
CAll Tensor(float) All cell states [seq_length, directions, batch, H]
IOFC Tensor(float) Gate activations [seq_length, directions, batch, 4*H]

Usage Examples

ONNX_OPERATOR_TYPED_KERNEL_EX(
    LSTMTraining, kMSDomain, 1, float, kCpuExecutionProvider,
    (*KernelDefBuilder::Create())
        .TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
    LSTMTraining<float>);

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