Rename ConvLayoutAttr to ConvolutionLayout

include/ttmlir/Dialect/TTIR/IR/TTIROps.td

@@ -573,16 +573,16 @@ def TTIR_ConvolutionOp : TTIR_DPSOp<"convolution"> {
     Optional<AnyRankedTensor>:$bias,
     AnyRankedTensor:$output,
     // Default value: one for each of the spatial dimension.
-    DefaultValuedOptionalAttr<DenseI64ArrayAttr, "std::vector<int64_t>(getConvLayout().getInputSpatialDimensions().size(), 1)">:$window_strides,
+    DefaultValuedOptionalAttr<DenseI64ArrayAttr, "SmallVector<int64_t>(getConvolutionLayout().getInputSpatialDimensions().size(), 1)">:$window_strides,
     // Default value: two zeros for each of the spatial dimension.
-    DefaultValuedOptionalAttr<I64ElementsAttr, "std::vector<int64_t>(getConvLayout().getInputSpatialDimensions().size()*2, 0)">:$padding,
+    DefaultValuedOptionalAttr<I64ElementsAttr, "SmallVector<int64_t>(getConvolutionLayout().getInputSpatialDimensions().size()*2, 0)">:$padding,
     // Default value: one for each of the spatial dimension.
-    DefaultValuedOptionalAttr<DenseI64ArrayAttr, "std::vector<int64_t>(getConvLayout().getInputSpatialDimensions().size(), 1)">:$input_dilation,
+    DefaultValuedOptionalAttr<DenseI64ArrayAttr, "SmallVector<int64_t>(getConvolutionLayout().getInputSpatialDimensions().size(), 1)">:$input_dilation,
     // Default value: one for each of the spatial dimension.
-    DefaultValuedOptionalAttr<DenseI64ArrayAttr, "std::vector<int64_t>(getConvLayout().getInputSpatialDimensions().size(), 1)">:$weight_dilation,
+    DefaultValuedOptionalAttr<DenseI64ArrayAttr, "SmallVector<int64_t>(getConvolutionLayout().getInputSpatialDimensions().size(), 1)">:$weight_dilation,
     // Default value: false for each of the spatial dimension.
-    DefaultValuedOptionalAttr<DenseBoolArrayAttr, "ConvolutionOp::getDefaultWindowReversal(getConvLayout())">:$window_reversal,
-    TTIR_ConvLayoutAttr:$conv_layout,
+    DefaultValuedOptionalAttr<DenseBoolArrayAttr, "SmallVector<bool>(getConvolutionLayout().getInputSpatialDimensions().size(), false)">:$window_reversal,
+    TTIR_ConvolutionLayoutAttr:$convolution_layout,
     ConfinedAttr<I64Attr, [IntPositive]>:$feature_group_count,
     ConfinedAttr<I64Attr, [IntPositive]>:$batch_group_count,
     TT_OperandConstraintArrayAttr:$operand_constraints
@@ -593,17 +593,6 @@ def TTIR_ConvolutionOp : TTIR_DPSOp<"convolution"> {
 
   let extraClassDeclaration = [{
       MutableOperandRange getDpsInitsMutable() { return getOutputMutable(); }
-
-      static ArrayRef<bool> getDefaultWindowReversal(const ConvLayoutAttr &convLayout) {
-        static bool boolArray[1000];
-
-        assert (convLayout.getInputSpatialDimensions().size() < 100 && "Too many spatial dimensions");
-        for (uint32_t i = 0; i < convLayout.getInputSpatialDimensions().size(); i++) {
-          boolArray[i] = false;
-        }
-
-        return ArrayRef<bool>(boolArray, convLayout.getInputSpatialDimensions().size());
-      }
     }];
 }
 

include/ttmlir/Dialect/TTIR/IR/TTIROpsAttrs.td

@@ -8,9 +8,9 @@
 include "mlir/IR/AttrTypeBase.td"
 include "ttmlir/Dialect/TTIR/IR/TTIRBase.td"
 
-def TTIR_ConvLayoutAttr : AttrDef<TTIR_Dialect, "ConvLayout", [], "::mlir::Attribute"> {
-  let mnemonic = "conv";
-  let summary = "Structure of dimension information for conv op";
+def TTIR_ConvolutionLayoutAttr : AttrDef<TTIR_Dialect, "ConvolutionLayout", [], "::mlir::Attribute"> {
+  let mnemonic = "convolution_layout";
+  let summary = "Structure of dimension information for convolution op";
   let description = [{
     Holds the layout information for the input activation, weights, and output.
   }];

lib/Conversion/StableHLOToTTIR/StableHLOToTTIRPatterns.cpp

@@ -380,7 +380,7 @@ class StableHLOToTTIRConvolutionOpConversionPattern
         mlir::Value(nullptr), outputTensor, adaptor.getWindowStridesAttr(),
         adaptor.getPaddingAttr(), adaptor.getLhsDilationAttr(),
         adaptor.getRhsDilationAttr(), adaptor.getWindowReversalAttr(),
-        mlir::tt::ttir::ConvLayoutAttr::get(
+        mlir::tt::ttir::ConvolutionLayoutAttr::get(
             getContext(), dimNums.getInputBatchDimension(),
             dimNums.getInputFeatureDimension(),
             dimNums.getInputSpatialDimensions(),

lib/Dialect/TTIR/IR/TTIROps.cpp

@@ -62,29 +62,33 @@ ::mlir::LogicalResult mlir::tt::ttir::Conv2dOp::verify() {
   return success();
 }
 
+//===----------------------------------------------------------------------===//
+// ConvolutionOp
+//===----------------------------------------------------------------------===//
+
 ::mlir::LogicalResult mlir::tt::ttir::ConvolutionOp::verify() {
-  if (getConvLayout().getInputSpatialDimensions().size() !=
-      getConvLayout().getOutputSpatialDimensions().size()) {
+  if (getConvolutionLayout().getInputSpatialDimensions().size() !=
+      getConvolutionLayout().getOutputSpatialDimensions().size()) {
     return emitOpError("Convolution input, output, and kernel must have the "
                        "same number of spatial dimensions");
   }
-  if (getConvLayout().getInputSpatialDimensions().size() !=
-      getConvLayout().getKernelSpatialDimensions().size()) {
+  if (getConvolutionLayout().getInputSpatialDimensions().size() !=
+      getConvolutionLayout().getKernelSpatialDimensions().size()) {
     return emitOpError("Convolution input, output, and kernel must have the "
                        "same number of spatial dimensions");
   }
 
   // Subtract 2 from the rank as to not count batch and feature dimension
   if (getInput().getType().getRank() - 2 !=
-      (int64_t)getConvLayout().getInputSpatialDimensions().size()) {
+      (int64_t)getConvolutionLayout().getInputSpatialDimensions().size()) {
     return emitOpError("Input tensor must have the same number of spatial "
-                       "dimensions as specified in the ConvLayout");
+                       "dimensions as specified in the ConvolutionLayout");
   }
 
   if (getWeight().getType().getRank() - 2 !=
-      (int64_t)getConvLayout().getKernelSpatialDimensions().size()) {
+      (int64_t)getConvolutionLayout().getKernelSpatialDimensions().size()) {
     return emitOpError("Weight tensor must have the same number of spatial "
-                       "dimensions as specified in the ConvLayout");
+                       "dimensions as specified in the ConvolutionLayout");
   }
 
   std::optional<::mlir::RankedTensorType> biasType =

lib/Dialect/TTIR/Transforms/Transforms.cpp

@@ -223,13 +223,14 @@ static std::vector<TransposeDims> generateKernelTransposeIndices(
   std::vector<int64_t> kernel_layout(
       ttnn_convolution_kernel_layout.size(),
       ConvolutionKernelDimension::INVALID_KERNEL_DIM);
-  kernel_layout[op.getConvLayout().getKernelOutputFeatureDimension()] =
+  kernel_layout[op.getConvolutionLayout().getKernelOutputFeatureDimension()] =
       ConvolutionKernelDimension::OUTPUT_FEATURES;
-  kernel_layout[op.getConvLayout().getKernelInputFeatureDimension()] =
+  kernel_layout[op.getConvolutionLayout().getKernelInputFeatureDimension()] =
       ConvolutionKernelDimension::INPUT_FEATURES;
 
   int64_t spatial_count = 0;
-  for (int64_t spatial_dim : op.getConvLayout().getKernelSpatialDimensions()) {
+  for (int64_t spatial_dim :
+       op.getConvolutionLayout().getKernelSpatialDimensions()) {
     kernel_layout[spatial_dim] = spatial_count;
     spatial_count++;
   }
@@ -256,13 +257,14 @@ static std::vector<TransposeDims> generateInputTransposeIndices(
 
   std::vector<int64_t> input_layout(ttnn_convolution_layout.size(),
                                     ConvolutionDimension::INVALID_DIM);
-  input_layout[op.getConvLayout().getInputBatchDimension()] =
+  input_layout[op.getConvolutionLayout().getInputBatchDimension()] =
       ConvolutionDimension::BATCH;
-  input_layout[op.getConvLayout().getInputFeatureDimension()] =
+  input_layout[op.getConvolutionLayout().getInputFeatureDimension()] =
       ConvolutionDimension::FEATURE;
 
   int64_t spatial_count = 0;
-  for (int64_t spatial_dim : op.getConvLayout().getInputSpatialDimensions()) {
+  for (int64_t spatial_dim :
+       op.getConvolutionLayout().getInputSpatialDimensions()) {
     input_layout[spatial_dim] = spatial_count;
     spatial_count++;
   }
@@ -295,13 +297,14 @@ static std::vector<TransposeDims> generateOutputTransposeIndices(
 
   std::vector<int64_t> desired_output_layout(ttnn_convolution_layout.size(),
                                              ConvolutionDimension::INVALID_DIM);
-  desired_output_layout[op.getConvLayout().getOutputBatchDimension()] =
+  desired_output_layout[op.getConvolutionLayout().getOutputBatchDimension()] =
       ConvolutionDimension::BATCH;
-  desired_output_layout[op.getConvLayout().getOutputFeatureDimension()] =
+  desired_output_layout[op.getConvolutionLayout().getOutputFeatureDimension()] =
       ConvolutionDimension::FEATURE;
 
   int64_t spatial_count = 0;
-  for (int64_t spatial_dim : op.getConvLayout().getOutputSpatialDimensions()) {
+  for (int64_t spatial_dim :
+       op.getConvolutionLayout().getOutputSpatialDimensions()) {
     desired_output_layout[spatial_dim] = spatial_count;
     spatial_count++;
   }
@@ -351,16 +354,16 @@ class ConvolutionToConv2dPatternRewriter
 
     // Conv2d will have 2 spatial dimensions
 
-    assert(op.getConvLayout().getInputSpatialDimensions().size() ==
-               op.getConvLayout().getOutputSpatialDimensions().size() &&
+    assert(op.getConvolutionLayout().getInputSpatialDimensions().size() ==
+               op.getConvolutionLayout().getOutputSpatialDimensions().size() &&
            "Convolution input, output, and kernel must have the same number of "
            "spatial dimensions");
-    assert(op.getConvLayout().getInputSpatialDimensions().size() ==
-               op.getConvLayout().getKernelSpatialDimensions().size() &&
+    assert(op.getConvolutionLayout().getInputSpatialDimensions().size() ==
+               op.getConvolutionLayout().getKernelSpatialDimensions().size() &&
            "Convolution input, output, and kernel must have the same number of "
            "spatial dimensions");
 
-    if (op.getConvLayout().getInputSpatialDimensions().size() != 2) {
+    if (op.getConvolutionLayout().getInputSpatialDimensions().size() != 2) {
       return failure();
     }
 
@@ -409,10 +412,10 @@ class ConvolutionToConv2dPatternRewriter
 
     auto output_shape = op.getResult().getType().getShape().vec();
     std::vector<int64_t> new_output_shape = {
-        output_shape[op.getConvLayout().getOutputBatchDimension()],
-        output_shape[op.getConvLayout().getOutputSpatialDimensions()[0]],
-        output_shape[op.getConvLayout().getOutputSpatialDimensions()[1]],
-        output_shape[op.getConvLayout().getOutputFeatureDimension()]};
+        output_shape[op.getConvolutionLayout().getOutputBatchDimension()],
+        output_shape[op.getConvolutionLayout().getOutputSpatialDimensions()[0]],
+        output_shape[op.getConvolutionLayout().getOutputSpatialDimensions()[1]],
+        output_shape[op.getConvolutionLayout().getOutputFeatureDimension()]};
 
     auto inputType = mlir::cast<RankedTensorType>(op.getInput().getType());
     auto outputType =

test/ttmlir/Conversion/StableHLOToTTIR/conv2d_op.mlir

@@ -7,9 +7,6 @@ module @jit_convolution attributes {} {
       window = {
         stride = [1, 1],
         pad = [[1, 1], [1, 1]],
-        lhs_dilate = [1, 1],
-        rhs_dilate = [1, 1],
-        reverse = [0, 0]
       } {
         feature_group_count = 1 : i64,
         batch_group_count = 1 : i64,

test/ttmlir/Dialect/TTNN/complex_conv_channel_first.mlir

@@ -11,7 +11,7 @@ module @jit_convolution {
     // CHECK: %[[C:.*]] = "ttnn.conv2d"[[C:.*]]
     %1 = "ttir.convolution"(%arg0, %arg1, %0) <{
       batch_group_count = 1 : i64,
-      conv_layout = #ttir<conv
+      convolution_layout = #ttir<convolution_layout
         input_batch = 0,
         input_feature = 1,
         input_spatial_dimensions = 2x3,