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[mlir][tosa] Convert group tosa::Conv2DOp to linalg conv
This patch adds two new ops: linalg::Conv2DNhwgcGfhwcOp and linalg::Conv2DNhwgcGfhwcQOp, and uses them to convert tosa group conv2d Ops. - Added linalg::Conv2DNhwgcGfhwcOp and linalg::Conv2DNhwgcGfhwcQOp. - Updated the conversion process to use these new ops for tosa group conv2d operations.
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‎mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml‎

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Original file line numberDiff line numberDiff line change
@@ -3410,6 +3410,243 @@ structured_op: !LinalgStructuredOpConfig
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- !ScalarExpression
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scalar_arg: K
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--- !LinalgOpConfig
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metadata: !LinalgOpMetadata
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name: conv_2d_nhwgc_gfhwc
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cpp_class_name: Conv2DNhwgcGfhwcOp
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doc: |-
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Performs 2-D grouped convolution.
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Layout:
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* Input: NHWGC.
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* Kernel: GFHWC.
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Numeric casting is performed on the operands to the inner multiply, promoting
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them to the same data type as the accumulator/output.
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implements:
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- LinalgConvolutionOpInterface
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structured_op: !LinalgStructuredOpConfig
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args:
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- !LinalgOperandDefConfig
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name: I
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kind: input_tensor
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type_var: T1
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shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11] ->
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(s0, s1 * s2 + s3 * s4, s5 * s6 + s7 * s8, s9, s10)>
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- !LinalgOperandDefConfig
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name: K
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kind: input_tensor
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type_var: T2
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shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11] ->
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(s9, s11, s3, s7, s10)>
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- !LinalgOperandDefConfig
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name: O
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kind: output_tensor
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type_var: U
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shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11] ->
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(s0, s1, s5, s9, s11)>
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- !LinalgOperandDefConfig
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name: strides
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kind: index_attr
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index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11]
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-> (s2, s6)>
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default_indices:
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- 1
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- 1
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- !LinalgOperandDefConfig
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name: dilations
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kind: index_attr
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index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11]
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-> (s4, s8)>
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default_indices:
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- 1
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- 1
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indexing_maps: !LinalgIndexingMapsConfig
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static_indexing_maps:
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> (d0, d1 * s2 + d5 * s4, d2 * s6 + d6 * s8, d3, d7)>
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> (d3, d4, d5, d6, d7)>
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> (d0, d1, d2, d3, d4)>
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iterator_types:
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- parallel
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- parallel
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- parallel
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- parallel
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- parallel
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- reduction
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- reduction
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- reduction
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assignments:
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- !ScalarAssign
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arg: O
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value: !ScalarExpression
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scalar_fn:
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kind: binary
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fn_name: add
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operands:
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- !ScalarExpression
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scalar_arg: O
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- !ScalarExpression
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scalar_fn:
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kind: binary
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fn_name: mul
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operands:
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- !ScalarExpression
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scalar_fn:
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kind: type
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fn_name: cast_signed
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type_var: U
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operands:
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- !ScalarExpression
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scalar_arg: I
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- !ScalarExpression
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scalar_fn:
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kind: type
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fn_name: cast_signed
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type_var: U
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operands:
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- !ScalarExpression
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scalar_arg: K
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--- !LinalgOpConfig
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metadata: !LinalgOpMetadata
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name: conv_2d_nhwgc_gfhwc_q
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cpp_class_name: Conv2DNhwgcGfhwcQOp
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doc: |-
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Performs 2-D grouped convolution with zero point offsets.
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Layout:
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* Input: NHWGC.
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* Kernel: GFHWC.
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Numeric casting is performed on the operands to the inner multiply, promoting
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them to the same data type as the accumulator/output. This includes the zero
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point offsets common to quantized operations.
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implements:
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- LinalgConvolutionOpInterface
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structured_op: !LinalgStructuredOpConfig
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args:
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- !LinalgOperandDefConfig
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name: I
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kind: input_tensor
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type_var: T1
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shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11] ->
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(s0, s1 * s2 + s3 * s4, s5 * s6 + s7 * s8, s9, s10)>
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- !LinalgOperandDefConfig
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name: K
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kind: input_tensor
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type_var: T2
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shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11] ->
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(s9, s11, s3, s7, s10)>
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- !LinalgOperandDefConfig
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name: IZp
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kind: scalar
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type_var: I32
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- !LinalgOperandDefConfig
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name: KZp
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kind: scalar
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type_var: I32
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- !LinalgOperandDefConfig
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name: O
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kind: output_tensor
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type_var: U
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shape_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11] ->
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(s0, s1, s5, s9, s11)>
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- !LinalgOperandDefConfig
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name: strides
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kind: index_attr
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index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11]
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-> (s2, s6)>
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default_indices:
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- 1
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- 1
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- !LinalgOperandDefConfig
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name: dilations
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kind: index_attr
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index_attr_map: affine_map<()[s0, s1, s2, s3, s4, s5, s6, s7, s8, s9, s10, s11]
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-> (s4, s8)>
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default_indices:
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- 1
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- 1
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indexing_maps: !LinalgIndexingMapsConfig
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static_indexing_maps:
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> (d0, d1 * s2 + d5 * s4, d2 * s6 + d6 * s8, d3, d7)>
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> (d3, d4, d5, d6, d7)>
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> ()>
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> ()>
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- affine_map<(d0, d1, d2, d3, d4, d5, d6, d7)[s0, s1, s2, s3, s4, s5, s6, s7,
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s8, s9, s10, s11] -> (d0, d1, d2, d3, d4)>
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iterator_types:
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- parallel
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- parallel
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- parallel
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- parallel
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- parallel
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- reduction
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- reduction
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- reduction
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assignments:
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- !ScalarAssign
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arg: O
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value: !ScalarExpression
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scalar_fn:
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kind: binary
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fn_name: add
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operands:
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- !ScalarExpression
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scalar_arg: O
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- !ScalarExpression
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scalar_fn:
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kind: binary
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fn_name: mul
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operands:
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- !ScalarExpression
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scalar_fn:
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kind: binary
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fn_name: sub
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operands:
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- !ScalarExpression
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scalar_fn:
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kind: type
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fn_name: cast_signed
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type_var: U
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operands:
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- !ScalarExpression
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scalar_arg: I
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- !ScalarExpression
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scalar_fn:
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kind: type
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fn_name: cast_signed
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type_var: U
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operands:
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- !ScalarExpression
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scalar_arg: IZp
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- !ScalarExpression
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scalar_fn:
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kind: binary
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fn_name: sub
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operands:
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- !ScalarExpression
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scalar_fn:
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kind: type
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fn_name: cast_signed
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type_var: U
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operands:
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- !ScalarExpression
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scalar_arg: K
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- !ScalarExpression
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scalar_fn:
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kind: type
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fn_name: cast_signed
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type_var: U
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operands:
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- !ScalarExpression
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scalar_arg: KZp
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--- !LinalgOpConfig
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metadata: !LinalgOpMetadata
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name: conv_2d_ngchw_gfchw_q
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cpp_class_name: Conv2DNgchwGfchwQOp

‎mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td‎

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Original file line numberDiff line numberDiff line change
@@ -133,6 +133,18 @@ def Tosa_ConvOpQuantInfoBuilder : OpBuilder<
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pad, stride, dilation);
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}]>;
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// Handles grouped convolution
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def Tosa_ConvOpGroupQuantBuilder : OpBuilder<
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(ins "::mlir::Type":$outputType, "::mlir::Value":$input,
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"::mlir::Value":$weight, "::mlir::Value":$bias,
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"::mlir::DenseI64ArrayAttr":$pad, "::mlir::DenseI64ArrayAttr":$stride,
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"::mlir::DenseI64ArrayAttr":$dilation, "::mlir::IntegerAttr":$group),
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[{
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buildConvOpWithQuantInfo($_builder, $_state, outputType,
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input, weight, bias,
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pad, stride, dilation, group);
146+
}]>;
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// Handles tosa.transpose_conv2d which has an outpad and output shape attribute.
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def Tosa_TransConvOpQuantInfoBuilder : OpBuilder<
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(ins "::mlir::Type":$outputType, "::mlir::Value":$input,

‎mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -108,6 +108,7 @@ def Tosa_Conv2DOp : Tosa_InferShapedTypeOp<"conv2d"> {
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Tosa_IntArrayAttr4:$pad,
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Tosa_IntArrayAttr2:$stride,
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Tosa_IntArrayAttr2:$dilation,
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OptionalAttr<I64Attr>:$group,
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OptionalAttr<Tosa_ConvOpQuantizationAttr>:$quantization_info,
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DefaultValuedOptionalAttr<BoolAttr, "false">:$local_bound
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);
@@ -116,7 +117,7 @@ def Tosa_Conv2DOp : Tosa_InferShapedTypeOp<"conv2d"> {
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Tosa_Tensor4D:$output
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);
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119-
let builders = [Tosa_ConvOpQuantInfoBuilder];
120+
let builders = [Tosa_ConvOpQuantInfoBuilder, Tosa_ConvOpGroupQuantBuilder];
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let hasVerifier = 1;
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}
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