experiments/STT-tensorflow
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Use the separate matrix/vector scaling factor version of MatrixBatchVectorMultiplyAccumulate in projection too.

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PiperOrigin-RevId: 316926050
Change-Id: I64e9febce8590231c78a90a0a5aec5da11996195
This commit is contained in:
Robert David 2020-06-17 11:15:35 -07:00 committed by TensorFlower Gardener
parent c8dd07ae28
commit ab7cb8336c
1 changed files with 3 additions and 6 deletions
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9
tensorflow/lite/kernels/lstm_eval.cc
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@ -874,16 +874,13 @@ inline void LstmStepHybrid(
tensor_utils::BatchQuantizeFloats(
output_gate_scratch, n_batch, n_cell, quantized_cell_state_ptr,
scaling_factors, zero_points, asymmetric_quantize_inputs);
for (int b = 0; b < n_batch; ++b) {
scaling_factors_scratch[b] =
scaling_factors[b] * projection_weights_scale;
}
tensor_utils::MatrixBatchVectorMultiplyAccumulate(
projection_weights_ptr, n_output, n_cell, quantized_cell_state_ptr,
scaling_factors_scratch, n_batch, output_state_ptr,
projection_weights_scale, scaling_factors, n_batch, output_state_ptr,
/*per_channel_scale=*/nullptr,
asymmetric_quantize_inputs ? zero_points : nullptr, accum_scratch_ptr,
projection_weights_row_sums, compute_row_sums, context);
projection_weights_row_sums, compute_row_sums,
scaling_factors_scratch, context);
}
if (params->proj_clip > 0.0) {
tensor_utils::ClipVector(output_state_ptr, n_batch * n_output,