Merge branch 'main' into ac/small-worm

This reverts commit c6cba69bc3.

benches/accum_conv.rs

@@ -72,7 +72,6 @@ impl Circuit<Fr> for MyCircuit {
                         Box::new(PolyOp::Conv {
                             padding: vec![(0, 0)],
                             stride: vec![1; 2],
-                            group: 1,
                         }),
                     )
                     .unwrap();

docs/python/requirements-docs.txt

@@ -1,4 +1,4 @@
-ezkl==11.6.3
+ezkl==0.0.0
 sphinx
 sphinx-rtd-theme
 sphinxcontrib-napoleon

docs/python/src/conf.py

@@ -1,7 +1,7 @@
 import ezkl
 
 project = 'ezkl'
-release = '11.6.3'
+release = '0.0.0'
 version = release
 
 

examples/conv2d_mnist/main.rs

@@ -205,7 +205,6 @@ where
                     let op = PolyOp::Conv {
                         padding: vec![(PADDING, PADDING); 2],
                         stride: vec![STRIDE; 2],
-                        group: 1,
                     };
                     let x = config
                         .layer_config

src/circuit/ops/layouts.rs

@@ -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, 1)?;
+            let output = conv(config, region, &[input, kernel.clone()], padding, stride)?;
             res.push(output);
             Ok(())
         })
@@ -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], 1).unwrap();
+/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, c], &vec![(1, 1); 2], &vec![1;2], &vec![2;2]).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);
 ///
@@ -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], 1).unwrap();
+/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(0, 0); 2], &vec![0;2], &vec![1;2]).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);
 ///
@@ -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], 1).unwrap();
+/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, k], &vec![(1, 1); 2], &vec![0;2], &vec![1;2]).unwrap();
 /// let expected = Tensor::<i64>::new(Some(&[17]), &[1, 1, 1, 1]).unwrap();
 /// assert_eq!(result.get_int_evals().unwrap(), expected);
 ///
@@ -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], 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 expected = Tensor::<i64>::new(Some(&[10, 4, 0, 3]), &[1, 1, 2, 2]).unwrap();
 /// assert_eq!(result.get_int_evals().unwrap(), expected);
 ///
@@ -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], 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 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);
 ///
@@ -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], 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 expected = Tensor::<i64>::new(Some(&[0, 0]), &[1, 1, 2, 1]).unwrap();
 /// assert_eq!(result.get_int_evals().unwrap(), expected);
 ///
@@ -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], 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 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);
 ///
@@ -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], 1).unwrap();
+/// let result = deconv::<Fp>(&dummy_config, &mut dummy_region, &[x, c], &vec![(1, 1); 2], &vec![0;2], &vec![2;2]).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(
@@ -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], 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 expected = Tensor::<i64>::new(Some(&[55, 58, 66, 69]), &[1, 1, 2, 2]).unwrap();
 /// assert_eq!(result.get_int_evals().unwrap(), expected);
 ///
@@ -3279,7 +3279,6 @@ 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]);
@@ -3365,7 +3364,6 @@ pub fn deconv<
         &conv_input,
         &vec![(0, 0); conv_dim],
         &vec![1; conv_dim],
-        num_groups,
     )?;
 
     Ok(output)
@@ -3397,7 +3395,7 @@ 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], 1).unwrap();
+/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2]).unwrap();
 /// let expected = Tensor::<i64>::new(Some(&[31, 16, 8, 26]), &[1, 1, 2, 2]).unwrap();
 /// assert_eq!(result.get_int_evals().unwrap(), expected);
 ///
@@ -3415,7 +3413,7 @@ pub fn deconv<
 ///     &[2],
 /// ).unwrap());
 ///
-/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2], 2).unwrap();
+/// let result = conv::<Fp>(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;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);
 ///
@@ -3433,7 +3431,7 @@ pub fn deconv<
 ///     &[4],
 /// ).unwrap());
 ///
-/// let result =conv(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2], 1).unwrap();
+/// let result =conv(&dummy_config, &mut dummy_region, &[x, k, b], &vec![(0, 0); 2], &vec![1;2]).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);
 /// ```
@@ -3452,7 +3450,6 @@ 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());
@@ -3483,11 +3480,6 @@ 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();
 
@@ -3521,17 +3513,10 @@ 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,
@@ -3539,6 +3524,14 @@ pub fn conv<
         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>();
 

src/circuit/ops/poly.rs

@@ -33,7 +33,6 @@ pub enum PolyOp {
     Conv {
         padding: Vec<(usize, usize)>,
         stride: Vec<usize>,
-        group: usize,
     },
     Downsample {
         axis: usize,
@@ -44,7 +43,6 @@ pub enum PolyOp {
         padding: Vec<(usize, usize)>,
         output_padding: Vec<usize>,
         stride: Vec<usize>,
-        group: usize,
     },
     Add,
     Sub,
@@ -150,25 +148,17 @@ impl<
             PolyOp::Sum { axes } => format!("SUM (axes={:?})", axes),
             PolyOp::Prod { .. } => "PROD".into(),
             PolyOp::Pow(_) => "POW".into(),
-            PolyOp::Conv {
-                stride,
-                padding,
-                group,
-            } => {
-                format!(
-                    "CONV (stride={:?}, padding={:?}, group={})",
-                    stride, padding, group
-                )
+            PolyOp::Conv { stride, padding } => {
+                format!("CONV (stride={:?}, padding={:?})", stride, padding)
             }
             PolyOp::DeConv {
                 stride,
                 padding,
                 output_padding,
-                group,
             } => {
                 format!(
-                    "DECONV (stride={:?}, padding={:?}, output_padding={:?}, group={})",
-                    stride, padding, output_padding, group
+                    "DECONV (stride={:?}, padding={:?}, output_padding={:?})",
+                    stride, padding, output_padding
                 )
             }
             PolyOp::Concat { axis } => format!("CONCAT (axis={})", axis),
@@ -222,18 +212,9 @@ impl<
             PolyOp::Prod { axes, .. } => {
                 layouts::prod_axes(config, region, values[..].try_into()?, axes)?
             }
-            PolyOp::Conv {
-                padding,
-                stride,
-                group,
-            } => layouts::conv(
-                config,
-                region,
-                values[..].try_into()?,
-                padding,
-                stride,
-                *group,
-            )?,
+            PolyOp::Conv { padding, stride } => {
+                layouts::conv(config, region, values[..].try_into()?, padding, stride)?
+            }
             PolyOp::GatherElements { dim, constant_idx } => {
                 if let Some(idx) = constant_idx {
                     tensor::ops::gather_elements(values[0].get_inner_tensor()?, idx, *dim)?.into()
@@ -280,7 +261,6 @@ impl<
                 padding,
                 output_padding,
                 stride,
-                group,
             } => layouts::deconv(
                 config,
                 region,
@@ -288,7 +268,6 @@ impl<
                 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)?,

src/circuit/tests.rs

@@ -1050,7 +1050,6 @@ mod conv {
                                 Box::new(PolyOp::Conv {
                                     padding: vec![(1, 1); 2],
                                     stride: vec![2; 2],
-                                    group: 1,
                                 }),
                             )
                             .map_err(|_| Error::Synthesis)
@@ -1201,7 +1200,6 @@ mod conv_col_ultra_overflow {
                                 Box::new(PolyOp::Conv {
                                     padding: vec![(1, 1); 2],
                                     stride: vec![2; 2],
-                                    group: 1,
                                 }),
                             )
                             .map_err(|_| Error::Synthesis)
@@ -1347,7 +1345,6 @@ 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);

src/graph/utilities.rs

@@ -283,7 +283,10 @@ 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,
@@ -1189,13 +1192,7 @@ pub fn new_op_from_onnx(
                 }
             }
 
-            let group = conv_node.group;
-
-            SupportedOp::Linear(PolyOp::Conv {
-                padding,
-                stride,
-                group,
-            })
+            SupportedOp::Linear(PolyOp::Conv { padding, stride })
         }
         "Not" => SupportedOp::Linear(PolyOp::Not),
         "And" => SupportedOp::Linear(PolyOp::And),
@@ -1250,7 +1247,6 @@ pub fn new_op_from_onnx(
                 padding,
                 output_padding: deconv_node.adjustments.to_vec(),
                 stride,
-                group: deconv_node.group,
             })
         }
         "Downsample" => {