Commit 6db943f
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FP32 ReduceMean operator improvement (#137)
This PR fixes the tiling implementation for the PULPOpen FP32 ReduceMean operator ([Issue #134](#134)) and adds parallelization support. It also extends ReduceMean to support ONNX opset >= 18, reorganizes the FP32 TinyViT kernel test suite, and adds extensive ReduceMean test coverage.
## Added
- Support for an unknown number of data dimensions in the tiler
- Parallelization support for the FP32 ReduceMean operator on PULPOpen
- Extensive testing for the ReduceMean operator
- Pass to remove ReduceMean operators that don't change data content, but only its shape
## Changed
- Structure of Tests subdir for improved ordering
- Structure of `.gitignore` file for improved ordering
## Fixed
- Fixed ReduceMean parallelization and tiling issues described in Issue [#134](#134).1 parent ecae48a commit 6db943f
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533 files changed
+948
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lines changed- .github/workflows
- .vscode
- DeeployTest
- Tests
- Kernels
- FP32
- Add
- Large
- Regular
- Conv
- DW_2D_Bias
- DW_2D_NoBias
- DW_2D_ZeroValuedBias
- Regular_2D_Bias
- Regular_2D_NoBias
- Regular_2D_ZeroValuedBias
- Div
- GELU
- GEMM
- NoBias
- Regular
- TransB
- LayerNorm
- MatMul
- MaxPool
- Mul
- Pad
- Pow
- Scalar
- Vector
- RMSNorm
- ReLU
- ReduceMean
- KeepDims
- Add_ReduceMean_Add
- Add_ReduceMean
- AllAxes
- Axes1_2_3
- Axes1_3
- Axes2_1
- Axis0
- Axis2
- ReduceMean_Add
- NoKeepDims
- Add_ReduceMean_Add
- Add_ReduceMean
- AllAxes
- Axes1_2_3
- Axes1_3
- Axes2_1
- Axis0
- Axis2
- ReduceMean_Add
- ReduceSum
- Reshape
- Regular
- SkipConnection
- Softmax
- CrossEntropyGrad
- CrossEntropy
- Grad
- Regular
- Sqrt
- Squeeze
- Transpose
- Integer
- Add
- Large
- MultIO
- Regular_RQ
- Regular
- Attention
- Concat
- Conv
- DW_1D
- DW_2D_RQ
- DW_2D
- PW_2D_RQ
- Regular_RQ
- Unsigned_RQ
- PW_2D
- Regular_1D
- Regular_2D_RQ
- Regular_2D
- StriddedPadded_2D_RQ
- GEMM
- Batch_RQ
- Regular_RQPerColumn
- Regular_RQPerRow
- Regular
- TransB_RQ
- Hardswish
- Regular_RQ
- Regular
- Identity
- InputIdentity
- MultiOutputIdentity
- OutputIdentity
- MatMul
- Add
- Batch
- Regular_RQ
- Regular
- MaxPool
- Pad
- Regular_1D
- Regular_2D
- RMSNorm
- ReduceMean
- ReduceSum
- Slice
- Softmax
- Large
- Regular
- TrueIntegerDiv
- iNoNorm
- Mixed
- Dequant
- Quant
- Models
- Autoencoder1D
- CCT_Train
- CCT2_FT1
- CCT2_FT2
- CCT2_LP
- CCT2_LoRA1
- CCT2_LoRA2
- CCT
- FP32
- CCT_1_16_16_128
- CCT_1_16_16_32
- CCT_1_16_16_64
- CCT_1_16_16_8
- CCT_1_32_32_32
- CCT_1_32_32_8
- CCT_2_32_32_128_Opset20
- CCT_2_32_32_128
- Int
- ICCT_8
- ICCT_ITA_8
- ICCT_ITA
- ICCT
- CNN_Linear1
- CNN_Linear2
- EEGFormer
- MLPerf
- AnomalyDetection
- ImageClassification
- KeywordSpotting
- VisualWakeWords
- MobileNetv2
- TinyViT
- 5M/Layers/FP32/ReduceMean
- Demo
- Transformer_DeepQuant
- Transformer_Train
- Transformer
- WaveFormer
- microLlama
- microLlama128
- microLlama16_parallel
- microLlama16
- microLlama1_parallel
- microLlama1
- microLlama256
- microLlama2_parallel
- microLlama2
- microLlama32_parallel
- microLlama32
- microLlama4_parallel
- microLlama4
- microLlama64_parallel
- microLlama64
- microLlama8_parallel
- microLlama8
- miniMobileNetv2
- miniMobileNet
- Others
- Backtracking
- TypeInference
- test2DRequantizedConv
- Deeploy
- CommonExtensions
- CodeTransformationPasses
- OptimizationPasses/TopologyOptimizationPasses
- Targets
- Generic
- Templates
- PULPOpen
- Templates
- TileConstraints
- docs
- tutorials
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