# Validation Operations

ONNX test models used by `validate.py` to verify the Raptor compiler + PIM simulator pipeline.

Generated tests can be regenerated with:
```
python3 validation/operations/gen_tests.py
```

## Conv

| Test | Directory | Input | Output | Kernel | Stride | Padding | Bias | Notes |
|------|-----------|-------|--------|--------|--------|---------|------|-------|
| Simple | `conv/simple` | [1,3,3,3] | [1,1,2,2] | 2x2 | 1 | none | no | Basic conv, hand-crafted |
| With constant | `conv/with_constant` | [1,3,3,3] | [1,1,3,3] | 2x2 | 1 | SAME_UPPER | yes | Hand-crafted, constant weight+bias |
| Batch 2 | `conv/batch_2` | [2,3,3,3] | [2,1,3,3] | 2x2 | 1 | SAME_UPPER | yes | Batched input |
| Kernel 3x3 | `conv/kernel_3x3` | [1,1,5,5] | [1,1,3,3] | 3x3 | 1 | none | no | Larger kernel |
| Stride 2 | `conv/stride_2` | [1,1,6,6] | [1,1,2,2] | 3x3 | 2 | none | no | Strided convolution |
| Multi channel | `conv/multi_channel` | [1,3,5,5] | [1,4,3,3] | 3x3 | 1 | none | no | 3 in channels, 4 out channels |
| Pointwise 1x1 | `conv/pointwise_1x1` | [1,8,4,4] | [1,4,4,4] | 1x1 | 1 | none | no | Channel mixing |
| SAME padding 3x3 | `conv/same_padding_3x3` | [1,1,5,5] | [1,1,5,5] | 3x3 | 1 | SAME_UPPER | no | Spatial dims preserved |
| Explicit padding | `conv/explicit_padding` | [1,1,4,4] | [1,1,4,4] | 3x3 | 1 | [1,1,1,1] | no | Symmetric explicit pads |
| With bias 3x3 | `conv/with_bias_3x3` | [1,3,5,5] | [1,2,3,3] | 3x3 | 1 | none | yes | Multi-channel with bias |
| Large spatial | `conv/large_spatial` | [1,1,8,8] | [1,1,6,6] | 3x3 | 1 | none | no | Larger spatial input |

## Pool

| Test | Directory | Input | Output | Kernel | Stride | Padding | Notes |
|------|-----------|-------|--------|--------|--------|---------|-------|
| Max basic | `pool/max_basic` | [1,1,4,4] | [1,1,3,3] | 2x2 | 1 | none | Basic max pooling |
| Max stride 2 multi-channel | `pool/max_stride2_multichannel` | [1,5,6,6] | [1,5,3,3] | 2x2 | 2 | none | Channel-preserving max pool |
| Max SAME_UPPER | `pool/max_same_upper` | [1,1,5,5] | [1,1,3,3] | 3x3 | 2 | SAME_UPPER | Deprecated auto_pad path |
| Avg basic | `pool/avg_basic` | [1,3,4,4] | [1,3,3,3] | 2x2 | 1 | none | Basic average pooling |
| Avg explicit padding | `pool/avg_explicit_padding` | [1,2,4,4] | [1,2,2,2] | 3x3 | 2 | [1,1,1,1] | `count_include_pad=0` |
| Avg include pad | `pool/avg_include_pad` | [1,2,4,4] | [1,2,2,2] | 3x3 | 2 | [1,1,1,1] | `count_include_pad=1` |
| Max after Conv | `pool/max_after_conv` | [1,3,6,6] | [1,4,2,2] | Conv 3x3 then Pool 2x2 | 2 | none | Regression for `pool(conv(...))` |

## Gemm

| Test | Directory | A (input) | W (weight) | Output | transB | alpha | beta | Bias | Notes |
|------|-----------|-----------|------------|--------|--------|-------|------|------|-------|
| Default | `gemm/` | [10,132] | [132,132] | [10,132] | no | 1 | 1 | no | Hand-crafted, square weights |
| Non-square | `gemm/non_square` | [4,128] | [128,64] | [4,64] | no | 1 | 1 | no | K != N |
| With bias | `gemm/with_bias` | [4,128] | [128,128] | [4,128] | no | 1 | 1 | [128] | Bias vector |
| transB | `gemm/transB` | [4,128] | [64,128] | [4,64] | yes | 1 | 1 | no | Transposed weight |
| Alpha/beta | `gemm/alpha_beta` | [4,64] | [64,64] | [4,64] | no | 0.5 | 0.25 | [64] | Scaled matmul + bias |
| Small | `gemm/small` | [2,8] | [8,4] | [2,4] | no | 1 | 1 | no | Tiny matrices |
| Large | `gemm/large` | [8,256] | [256,128] | [8,128] | no | 1 | 1 | no | Larger matrices |
| transB + bias | `gemm/transB_with_bias` | [4,128] | [64,128] | [4,64] | yes | 1 | 1 | [64] | Combined |

## Gemv

| Test | Directory | Input | W (weight) | Output | Bias | Notes |
|------|-----------|-------|------------|--------|------|-------|
| Simple | `gemv/simple` | [1,132] | [132,132] | [1,132] | no | Single-sample matmul |
| Constant | `gemv/constant` | _(none)_ | [132,132] | [1,132] | no | All inputs constant |
| Homogeneous const | `gemv/with_homogeneous_constant` | [1,132] | [132,132] | [1,132] | [1,132] | Bias matches output shape |
| Heterogeneous const | `gemv/with_heterogeneous_constant` | [1,132] | [132,132] | [1,132] | [1,132] | Different constant pattern |
| Scalar const | `gemv/with_scalar_constant` | [1,132] | [132,132] | [1,132] | [1,1] | Scalar bias, broadcast |