iree-org/iree

[TFL] `tfl.lstm` should have a stateful decomposition to other TFLite operations

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#9,190 opened on May 23, 2022

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bug 🐞help wantedintegrations/tosa

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Description

Some significant models are blocked by tfl.lstm which can be decomposed into already support tflite operations. Adding the decomposition should unblock these models.

/tmp/test.tflite:0:0: note: see current operation: %95 = "tfl.lstm"(%arg0, %44, %42, %41, %40, %44, %39, %38, %37, %44, %44, %44, %44, %92, %91, %90, %36, %44, %89, %88, %44, %87, %86, %85) ({
}) {asymmetric_quantize_inputs = false, cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", kernel_type = "FULL", proj_clip = 0.000000e+00 : f32} : (tensor<1x1280xf32>, none, tensor<2048x1280xi8>, tensor<2048x1280xi8>, tensor<2048x1280xi8>, none, tensor<2048x640xi8>, tensor<2048x640xi8>, tensor<2048x640xi8>, none, none, none, none, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>, tensor<640x2048xi8>, none, tensor<1x640xf32>, tensor<1x2048xf32>, none, tensor<2048xf32>, tensor<2048xf32>, tensor<2048xf32>) -> tensor<*xf32>

Contributor guide

Research direction
Implement a pass that decomposes tfl.lstm into basic TFLite operations like tfl.fully connected, tfl.add, tfl.mul, etc., using MLIR patterns.
Tech stack
cpp
Domain
compilersmachine learning
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
MLIRTFLiteC++
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
20