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fix: num groups for conv operations should be specified at load time #828

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merged 4 commits into from
Jul 18, 2024
Merged

fix: num groups for conv operations should be specified at load time #828

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fef1d28
fix: num groups for conv operations should be specified at load time
alexander-camuto Jul 17, 2024
cf3f6a1
Update layouts.rs
alexander-camuto Jul 17, 2024
9362926
fix: add group to unit tests
alexander-camuto Jul 17, 2024
eec017d
fix: deconv unit tests should specify groups
alexander-camuto Jul 17, 2024
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1 change: 1 addition & 0 deletions benches/accum_conv.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,7 @@ impl Circuit<Fr> for MyCircuit {
Box::new(PolyOp::Conv {
padding: vec![(0, 0)],
stride: vec![1; 2],
group: 1,
}),
)
.unwrap();
Expand Down
1 change: 1 addition & 0 deletions examples/conv2d_mnist/main.rs
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Expand Up @@ -205,6 +205,7 @@ where
let op = PolyOp::Conv {
padding: vec![(PADDING, PADDING); 2],
stride: vec![STRIDE; 2],
group: 1,
};
let x = config
.layer_config
Expand Down
51 changes: 29 additions & 22 deletions src/circuit/ops/layouts.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -3023,7 +3023,7 @@ pub fn sumpool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + IntoI
.map(|coord| {
let (b, i) = (coord[0], coord[1]);
let input = values[0].get_slice(&[b..b + 1, i..i + 1])?;
let output = conv(config, region, &[input, kernel.clone()], padding, stride)?;
let output = conv(config, region, &[input, kernel.clone()], padding, stride, 1)?;
res.push(output);
Ok(())
})
Expand Down Expand Up @@ -3159,7 +3159,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// &[1, 1, 2, 2],
/// ).unwrap());
///
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, c], &vec![(1, 1); 2], &vec![1;2], &vec![2;2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, c], &vec![(1, 1); 2], &vec![1;2], &vec![2;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[0, 32, 0, 32, 0, 6, 0, 12, 0, 4, 0, 8, 0, 4, 0, 8, 0, 0, 0, 3, 0, 0, 0, 2]), &[1, 2, 3, 4]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3171,7 +3171,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[3, 1, 1, 5]),
/// &[1, 1, 2, 2],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![1;2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![1;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[6, 14, 4, 2, 17, 21, 0, 1, 5]), &[1, 1, 3, 3]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3184,7 +3184,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[3, 1, 1, 5]),
/// &[1, 1, 2, 2],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![1;2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![1;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[17]), &[1, 1, 1, 1]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3197,7 +3197,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[3, 1, 1, 5]),
/// &[1, 1, 2, 2],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![2; 2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![2; 2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[10, 4, 0, 3]), &[1, 1, 2, 2]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3209,7 +3209,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[3, 1, 1, 5]),
/// &[1, 1, 2, 2],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![2; 2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![2; 2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[6, 2, 12, 4, 2, 10, 4, 20, 0, 0, 3, 1, 0, 0, 1, 5]), &[1, 1, 4, 4]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3221,7 +3221,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[3, 2]),
/// &[1, 1, 2, 1],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![2; 2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![2; 2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[0, 0]), &[1, 1, 2, 1]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3233,7 +3233,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[3, 2]),
/// &[1, 1, 2, 1],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![2; 2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![2; 2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[6, 0, 12, 4, 0, 8, 0, 0, 3, 0, 0, 2]), &[1, 1, 4, 3]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3244,7 +3244,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// &[1, 1, 2, 2],
/// ).unwrap());
///
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, c], &vec![(1, 1); 2], &vec![0;2], &vec![2;2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, c], &vec![(1, 1); 2], &vec![0;2], &vec![2;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[0, 32, 0, 0, 6, 0, 0, 4, 0, 0, 0, 0]), &[1, 2, 2, 3]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
/// let x = ValTensor::from_i64_tensor(Tensor::<i64>::new(
Expand All @@ -3259,7 +3259,7 @@ pub fn max_pool<F: PrimeField + TensorType + PartialOrd + std::hash::Hash + Into
/// Some(&[1]),
/// &[1],
/// ).unwrap());
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(1, 1); 2], &vec![0;2], &vec![1;2]).unwrap();
/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(1, 1); 2], &vec![0;2], &vec![1;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[55, 58, 66, 69]), &[1, 1, 2, 2]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3279,6 +3279,7 @@ pub fn deconv<
padding: &[(usize, usize)],
output_padding: &[usize],
stride: &[usize],
num_groups: usize,
) -> Result<ValTensor<F>, CircuitError> {
let has_bias = inputs.len() == 3;
let (image, kernel) = (&inputs[0], &inputs[1]);
Expand Down Expand Up @@ -3364,6 +3365,7 @@ pub fn deconv<
&conv_input,
&vec![(0, 0); conv_dim],
&vec![1; conv_dim],
num_groups,
)?;

Ok(output)
Expand Down Expand Up @@ -3395,7 +3397,7 @@ pub fn deconv<
/// Some(&[0]),
/// &[1],
/// ).unwrap());
/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2]).unwrap();
/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[31, 16, 8, 26]), &[1, 1, 2, 2]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3413,7 +3415,7 @@ pub fn deconv<
/// &[2],
/// ).unwrap());
///
/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2]).unwrap();
/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2], 2).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[32, 17, 9, 27, 34, 20, 13, 26]), &[1, 2, 2, 2]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
///
Expand All @@ -3431,7 +3433,7 @@ pub fn deconv<
/// &[4],
/// ).unwrap());
///
/// let result =conv(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2]).unwrap();
/// let result =conv(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2], 1).unwrap();
/// let expected = Tensor::<i64>::new(Some(&[65, 36, 21, 52, 73, 48, 37, 48, 65, 36, 21, 52, 73, 48, 37, 48]), &[1, 4, 2, 2]).unwrap();
/// assert_eq!(result.get_int_evals().unwrap(), expected);
/// ```
Expand All @@ -3450,6 +3452,7 @@ pub fn conv<
values: &[ValTensor<F>],
padding: &[(usize, usize)],
stride: &[usize],
num_groups: usize,
) -> Result<ValTensor<F>, CircuitError> {
let has_bias = values.len() == 3;
let (mut image, mut kernel) = (values[0].clone(), values[1].clone());
Expand Down Expand Up @@ -3480,6 +3483,11 @@ pub fn conv<
region.increment(*assigned_len.iter().max().unwrap());
}

// if image is 3d add a dummy batch dimension
if image.dims().len() == kernel.dims().len() - 1 {
image.reshape(&[1, image.dims()[0], image.dims()[1], image.dims()[2]])?;
}

let image_dims = image.dims();
let kernel_dims = kernel.dims();

Expand Down Expand Up @@ -3513,25 +3521,24 @@ pub fn conv<

log::debug!("slides: {:?}", slides);

let num_groups = input_channels / kernel_dims[1];
let input_channels_per_group = input_channels / num_groups;
let output_channels_per_group = output_channels / num_groups;

if output_channels_per_group == 0 || input_channels_per_group == 0 {
return Err(TensorError::DimMismatch(format!(
"Given groups={}, expected input channels and output channels to be divisible by groups, but got input_channels={}, output_channels={}",
num_groups, input_channels, output_channels
))
.into());
}

log::debug!(
"num_groups: {}, input_channels_per_group: {}, output_channels_per_group: {}",
num_groups,
input_channels_per_group,
output_channels_per_group
);

if output_channels_per_group == 0 {
return Err(TensorError::DimMismatch(format!(
"Given groups={}, expected kernel to be at least {} at dimension 0 but got {} instead",
num_groups, num_groups, output_channels_per_group
))
.into());
}

let num_outputs =
batch_size * num_groups * output_channels_per_group * slides.iter().product::<usize>();

Expand Down
35 changes: 28 additions & 7 deletions src/circuit/ops/poly.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,7 @@ pub enum PolyOp {
Conv {
padding: Vec<(usize, usize)>,
stride: Vec<usize>,
group: usize,
},
Downsample {
axis: usize,
Expand All @@ -43,6 +44,7 @@ pub enum PolyOp {
padding: Vec<(usize, usize)>,
output_padding: Vec<usize>,
stride: Vec<usize>,
group: usize,
},
Add,
Sub,
Expand Down Expand Up @@ -148,17 +150,25 @@ impl<
PolyOp::Sum { axes } => format!("SUM (axes={:?})", axes),
PolyOp::Prod { .. } => "PROD".into(),
PolyOp::Pow(_) => "POW".into(),
PolyOp::Conv { stride, padding } => {
format!("CONV (stride={:?}, padding={:?})", stride, padding)
PolyOp::Conv {
stride,
padding,
group,
} => {
format!(
"CONV (stride={:?}, padding={:?}, group={})",
stride, padding, group
)
}
PolyOp::DeConv {
stride,
padding,
output_padding,
group,
} => {
format!(
"DECONV (stride={:?}, padding={:?}, output_padding={:?})",
stride, padding, output_padding
"DECONV (stride={:?}, padding={:?}, output_padding={:?}, group={})",
stride, padding, output_padding, group
)
}
PolyOp::Concat { axis } => format!("CONCAT (axis={})", axis),
Expand Down Expand Up @@ -212,9 +222,18 @@ impl<
PolyOp::Prod { axes, .. } => {
layouts::prod_axes(config, region, values[..].try_into()?, axes)?
}
PolyOp::Conv { padding, stride } => {
layouts::conv(config, region, values[..].try_into()?, padding, stride)?
}
PolyOp::Conv {
padding,
stride,
group,
} => layouts::conv(
config,
region,
values[..].try_into()?,
padding,
stride,
*group,
)?,
PolyOp::GatherElements { dim, constant_idx } => {
if let Some(idx) = constant_idx {
tensor::ops::gather_elements(values[0].get_inner_tensor()?, idx, *dim)?.into()
Expand Down Expand Up @@ -261,13 +280,15 @@ impl<
padding,
output_padding,
stride,
group,
} => layouts::deconv(
config,
region,
values[..].try_into()?,
padding,
output_padding,
stride,
*group,
)?,
PolyOp::Add => layouts::pairwise(config, region, values[..].try_into()?, BaseOp::Add)?,
PolyOp::Sub => layouts::pairwise(config, region, values[..].try_into()?, BaseOp::Sub)?,
Expand Down
3 changes: 3 additions & 0 deletions src/circuit/tests.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -1050,6 +1050,7 @@ mod conv {
Box::new(PolyOp::Conv {
padding: vec![(1, 1); 2],
stride: vec![2; 2],
group: 1,
}),
)
.map_err(|_| Error::Synthesis)
Expand Down Expand Up @@ -1200,6 +1201,7 @@ mod conv_col_ultra_overflow {
Box::new(PolyOp::Conv {
padding: vec![(1, 1); 2],
stride: vec![2; 2],
group: 1,
}),
)
.map_err(|_| Error::Synthesis)
Expand Down Expand Up @@ -1345,6 +1347,7 @@ mod conv_relu_col_ultra_overflow {
Box::new(PolyOp::Conv {
padding: vec![(1, 1); 2],
stride: vec![2; 2],
group: 1,
}),
)
.map_err(|_| Error::Synthesis);
Expand Down
14 changes: 9 additions & 5 deletions src/graph/utilities.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -283,10 +283,7 @@ pub fn new_op_from_onnx(
.flat_map(|x| x.out_scales())
.collect::<Vec<_>>();

let input_dims = inputs
.iter()
.flat_map(|x| x.out_dims())
.collect::<Vec<_>>();
let input_dims = inputs.iter().flat_map(|x| x.out_dims()).collect::<Vec<_>>();

let mut replace_const = |scale: crate::Scale,
index: usize,
Expand Down Expand Up @@ -1192,7 +1189,13 @@ pub fn new_op_from_onnx(
}
}

SupportedOp::Linear(PolyOp::Conv { padding, stride })
let group = conv_node.group;

SupportedOp::Linear(PolyOp::Conv {
padding,
stride,
group,
})
}
"Not" => SupportedOp::Linear(PolyOp::Not),
"And" => SupportedOp::Linear(PolyOp::And),
Expand Down Expand Up @@ -1247,6 +1250,7 @@ pub fn new_op_from_onnx(
padding,
output_padding: deconv_node.adjustments.to_vec(),
stride,
group: deconv_node.group,
})
}
"Downsample" => {
Expand Down
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