[Mlir-commits] [mlir] 8fd2f56 - [mlir][Linalg] Add 1-d depthwise conv with opdsl
Nicolas Vasilache
llvmlistbot at llvm.org
Thu Nov 11 09:51:50 PST 2021
Author: Nicolas Vasilache
Date: 2021-11-11T17:49:26Z
New Revision: 8fd2f56c990e2c9f2ea2578b136d0fdad1972a8d
URL: https://github.com/llvm/llvm-project/commit/8fd2f56c990e2c9f2ea2578b136d0fdad1972a8d
DIFF: https://github.com/llvm/llvm-project/commit/8fd2f56c990e2c9f2ea2578b136d0fdad1972a8d.diff
LOG: [mlir][Linalg] Add 1-d depthwise conv with opdsl
Differential Revision: https://reviews.llvm.org/D113686
Added:
Modified:
mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
mlir/test/Dialect/Linalg/named-ops.mlir
Removed:
################################################################################
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
index 2d8b02bb8ee57..80560b9f363b5 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOps.yaml
@@ -1383,6 +1383,83 @@ structured_op: !LinalgStructuredOpConfig
scalar_arg: K
is_unsigned_cast: false
--- !LinalgOpConfig
+metadata: !LinalgOpMetadata
+ name: depthwise_conv1D_nw
+ cpp_class_name: DepthwiseConv1DNwOp
+ doc: |-
+ Performs depth-wise 1-D convolution.
+
+ Numeric casting is performed on the operands to the inner multiply, promoting
+ them to the same data type as the accumulator/output. Multiplier is set to 1
+ which is a special case for most dpethwise convolutions.
+ implements:
+ - LinalgConvolutionOpInterface
+structured_op: !LinalgStructuredOpConfig
+ args:
+ - !LinalgOperandDefConfig
+ name: I
+ usage: InputOperand
+ type_var: T1
+ shape_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s0, s1 * s2 + s3 * s4, s5)>
+ - !LinalgOperandDefConfig
+ name: K
+ usage: InputOperand
+ type_var: T2
+ shape_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s3, s5)>
+ - !LinalgOperandDefConfig
+ name: O
+ usage: OutputOperand
+ type_var: U
+ shape_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s0, s1, s5)>
+ - !LinalgOperandDefConfig
+ name: strides
+ usage: IndexAttribute
+ type_var: I64
+ attribute_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s2)>
+ - !LinalgOperandDefConfig
+ name: dilations
+ usage: IndexAttribute
+ type_var: I64
+ attribute_map: affine_map<()[s0, s1, s2, s3, s4, s5] -> (s4)>
+ indexing_maps: !LinalgIndexingMapsConfig
+ static_indexing_maps:
+ - affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3, s4, s5] -> (d0, d1 * s2 + d3 * s4,
+ d2)>
+ - affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3, s4, s5] -> (d3, d2)>
+ - affine_map<(d0, d1, d2, d3)[s0, s1, s2, s3, s4, s5] -> (d0, d1, d2)>
+ iterator_types:
+ - parallel
+ - parallel
+ - parallel
+ - reduction
+ assignments:
+ - !ScalarAssign
+ arg: O
+ value: !ScalarExpression
+ scalar_apply:
+ fn_name: add
+ operands:
+ - !ScalarExpression
+ scalar_arg: O
+ - !ScalarExpression
+ scalar_apply:
+ fn_name: mul
+ operands:
+ - !ScalarExpression
+ symbolic_cast:
+ type_var: U
+ operands:
+ - !ScalarExpression
+ scalar_arg: I
+ is_unsigned_cast: false
+ - !ScalarExpression
+ symbolic_cast:
+ type_var: U
+ operands:
+ - !ScalarExpression
+ scalar_arg: K
+ is_unsigned_cast: false
+--- !LinalgOpConfig
metadata: !LinalgOpMetadata
name: depthwise_conv2D_nhw
cpp_class_name: DepthwiseConv2DNhwOp
diff --git a/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py b/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
index 9f5b27ea000eb..2e6b04118ef15 100644
--- a/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
+++ b/mlir/python/mlir/dialects/linalg/opdsl/ops/core_named_ops.py
@@ -309,6 +309,25 @@ def conv_3d_ndhwc_dhwcf(
U, I[D.n, D.od * S.SD + D.kd * S.DD, D.oh * S.SH + D.kh * S.DH, D.ow * S.SW + D.kw * S.DW, D.c
]) * cast(U, K[D.kd, D.kh, D.kw, D.c, D.f])
+ at linalg_structured_op
+def depthwise_conv1D_nw(
+ I=TensorDef(T1, S.N, S.OW * S.SW + S.KW * S.DW, S.IC),
+ K=TensorDef(T2, S.KW, S.IC),
+ O=TensorDef(U, S.N, S.OW, S.IC, output=True),
+ strides=AttributeDef(S.SW),
+ dilations=AttributeDef(S.DW)):
+ """Performs depth-wise 1-D convolution.
+
+ Numeric casting is performed on the operands to the inner multiply, promoting
+ them to the same data type as the accumulator/output. Multiplier is set to 1
+ which is a special case for most dpethwise convolutions.
+ """
+ implements(ConvolutionOpInterface)
+ domain(D.n, D.ow, D.ic, D.kw)
+ O[D.n, D.ow, D.ic] += \
+ cast(U, I[D.n, D.ow * S.SW + D.kw * S.DW, D.ic]) * \
+ cast(U, K[D.kw, D.ic])
+
@linalg_structured_op
def depthwise_conv2D_nhw(
I=TensorDef(T1, S.N, S.OH * S.SH + S.KH * S.DH, S.OW * S.SW + S.KW * S.DW, S.IC),
diff --git a/mlir/test/Dialect/Linalg/named-ops.mlir b/mlir/test/Dialect/Linalg/named-ops.mlir
index 86eefbcd6afec..cd01b6a0a920b 100644
--- a/mlir/test/Dialect/Linalg/named-ops.mlir
+++ b/mlir/test/Dialect/Linalg/named-ops.mlir
@@ -29,6 +29,19 @@ func @depthwise_conv2D_nhwc_memref(%input: memref<2x4x5x2xf32>, %filter: memref<
return
}
+// CHECK-LABEL: func @depthwise_conv1D_nw_tensor
+func @depthwise_conv1D_nw_tensor(%input: tensor<1x113x96xf32>, %filter: tensor<3x96xf32>) -> tensor<1x56x96xf32> {
+ %init = linalg.init_tensor [1, 56, 96] : tensor<1x56x96xf32>
+ // CHECK: %{{.+}} = linalg.depthwise_conv1D_nw
+ // CHECK-SAME: {dilations = dense<1> : vector<1xi64>, strides = dense<2> : vector<1xi64>}
+ // CHECK-SAME: ins(%{{.+}}, %{{.+}} : tensor<1x113x96xf32>, tensor<3x96xf32>)
+ // CHECK-SAME: outs(%{{.+}} : tensor<1x56x96xf32>) -> tensor<1x56x96xf32>
+ %0 = linalg.depthwise_conv1D_nw {dilations = dense<1> : vector<1xi64>, strides = dense<2> : vector<1xi64>}
+ ins(%input, %filter: tensor<1x113x96xf32>, tensor<3x96xf32>)
+ outs(%init: tensor<1x56x96xf32>) -> tensor<1x56x96xf32>
+ return %0: tensor<1x56x96xf32>
+}
+
// CHECK-LABEL: func @depthwise_conv2D_nhw_tensor
func @depthwise_conv2D_nhw_tensor(%input: tensor<1x113x113x96xf32>, %filter: tensor<3x3x96xf32>) -> tensor<1x56x56x96xf32> {
%init = linalg.init_tensor [1, 56, 56, 96] : tensor<1x56x56x96xf32>
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