[mlir][tosa] Remove out_shape from transpose_conv2d #129133
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Member
|
@llvm/pr-subscribers-mlir-tosa @llvm/pr-subscribers-mlir Author: Jerry-Ge (Jerry-Ge) ChangesRemoved out_shape from transpose_conv2d to match the latest TOSA v1.0 specification (https://www.mlplatform.org/tosa/tosa_spec.html#_transpose_conv2d). Full diff: https://github.com/llvm/llvm-project/pull/129133.diff 6 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td
index 23692478755c6..ce17ad9362227 100644
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td
@@ -148,13 +148,11 @@ def Tosa_TransConvOpQuantInfoBuilder : OpBuilder<
"::mlir::Value":$weight, "mlir::Value":$bias,
"::mlir::DenseI64ArrayAttr":$outpad,
"::mlir::DenseI64ArrayAttr":$stride,
- "::mlir::DenseI64ArrayAttr":$outputShape,
"::mlir::TypeAttr":$acc_type),
[{
buildTransConvOpWithQuantInfo($_builder, $_state, outputType,
input, weight, bias,
- outpad, stride,
- outputShape, acc_type);
+ outpad, stride, acc_type);
}]>;
// The tosa.matmul op is also intended to be generated where a fully_connected
diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
index ddfec2c9bfcd3..a9bf18f4af6b9 100644
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -408,7 +408,6 @@ def Tosa_TransposeConv2DOp : Tosa_ConvOp<"transpose_conv2d"> {
Tosa_IntArrayAttr4:$out_pad,
Tosa_IntArrayAttr2:$stride,
- Tosa_IntArrayAttr4:$out_shape,
TypeAttrOf<Tosa_AccType>:$acc_type,
DefaultValuedOptionalAttr<BoolAttr, "false">:$local_bound
);
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
index 7b50eceb081dd..54f9fa917f2e0 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -569,15 +569,15 @@ static void buildConvOpWithQuantInfo(OpBuilder &builder, OperationState &result,
/// Handles tosa.transpose_conv2d which has outpad and output shape
/// attributes.
-static void buildTransConvOpWithQuantInfo(
- OpBuilder &builder, OperationState &result, Type outputType, Value input,
- Value weight, Value bias, DenseI64ArrayAttr outpad,
- DenseI64ArrayAttr stride, DenseI64ArrayAttr outputShape, TypeAttr accType) {
+static void
+buildTransConvOpWithQuantInfo(OpBuilder &builder, OperationState &result,
+ Type outputType, Value input, Value weight,
+ Value bias, DenseI64ArrayAttr outpad,
+ DenseI64ArrayAttr stride, TypeAttr accType) {
auto zps = createZPsAsConst(builder, input, weight);
result.addOperands({input, weight, bias, zps.first, zps.second});
result.addAttribute("out_pad", outpad);
result.addAttribute("stride", stride);
- result.addAttribute("out_shape", outputShape);
result.addAttribute("acc_type", accType);
Type finalOutputType = outputType;
auto quantAttr = buildConvOpQuantizationAttr(builder, input, weight);
@@ -2327,9 +2327,7 @@ LogicalResult TransposeConv2DOp::inferReturnTypeComponents(
MLIRContext *context, ::std::optional<Location> location,
TransposeConv2DOp::Adaptor adaptor,
SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) {
- // outputShape is mutable.
- llvm::SmallVector<int64_t> outputShape =
- convertToMlirShape(adaptor.getOutShape());
+ llvm::SmallVector<int64_t> outputShape(4, ShapedType::kDynamic);
int64_t inputWidth = ShapedType::kDynamic;
int64_t inputHeight = ShapedType::kDynamic;
diff --git a/mlir/test/Dialect/Tosa/invalid.mlir b/mlir/test/Dialect/Tosa/invalid.mlir
index 123c65e1b4fcd..5b928a2489eea 100644
--- a/mlir/test/Dialect/Tosa/invalid.mlir
+++ b/mlir/test/Dialect/Tosa/invalid.mlir
@@ -168,7 +168,7 @@ func.func @test_depthwise_conv2d_acc_type(%arg0: tensor<1x4x4x4xi8>, %arg1: tens
func.func @test_transpose_conv2d(%arg0: tensor<1x32x32x8xi8>, %arg1: tensor<16x1x1x8xi8>, %arg2: tensor<16xi8>) -> tensor<1x32x32x16xi8> {
%zp = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
// expected-error@+1 {{'tosa.transpose_conv2d' op accumulator type for i8 tensor is not i32}}
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %zp, %zp {acc_type = f16, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: 1, 32, 32, 16>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xi8>, tensor<16x1x1x8xi8>, tensor<16xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %zp, %zp {acc_type = f16, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xi8>, tensor<16x1x1x8xi8>, tensor<16xi8>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x32x32x16xi8>
return %0 : tensor<1x32x32x16xi8>
}
@@ -741,15 +741,6 @@ func.func @test_table_io_shape_mismatch(%arg0: tensor<?x16xi16>, %arg1: tensor<6
// -----
-// CHECK-LABEL: test_transpose_conv2d_invalid_outshape
-func.func @test_transpose_conv2d_invalid_outshape(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x1x1x8xf32>, %arg2: tensor<16xf32>) -> tensor<1x32x32x16xf32> {
- // expected-error@+1 {{'tosa.transpose_conv2d' op attribute 'out_shape' failed to satisfy constraint: i64 dense array attribute with exactly 4 elements}}
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2 {out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: 1, 32, 32>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xf32>, tensor<16x1x1x8xf32>, tensor<16xf32>) -> tensor<1x32x32x16xf32>
- return %0 : tensor<1x32x32x16xf32>
-}
-
-// -----
-
// CHECK-LABEL: test_mul_type_mismatch
func.func @test_mul_type_mismatch(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x1x3xf16>) -> tensor<13x21x3xf32> {
%shift = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
diff --git a/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir b/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
index bb3c16cf52d63..7235c52c5dd05 100644
--- a/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-decompose-transpose-conv.mlir
@@ -30,21 +30,17 @@ func.func @transpose_conv2d_quantized(%arg0: tensor<2x16x14x3xi8>, %arg1: tensor
// -----
-// CHECK-LABEL: @transpose_conv2d_quantized_padded
func.func @transpose_conv2d_quantized_padded(%arg0: tensor<2x16x14x3xi8>, %arg1: tensor<5x3x6x3xi8>, %arg2: tensor<5xi32>) -> (tensor<2x21x26x5xi32>) {
- // CHECK-DAG: %[[INPUT_ZP:.+]] = "tosa.const"() <{value = dense<-22> : tensor<1xi8>}
- // CHECK-DAG: %[[WEIGHT_ZP:.+]] = "tosa.const"() <{value = dense<42> : tensor<1xi8>}
- // CHECK-DAG: %[[REV0:.+]] = tosa.reverse %2 {axis = 2 : i32}
- // CHECK-DAG: %[[REV1:.+]] = tosa.reverse %arg1 {axis = 1 : i32}
- // CHECK: tosa.conv2d %arg0, %3, %arg2, %[[INPUT_ZP]], %[[WEIGHT_ZP]]
- // CHECK-SAME: dilation = array<i64: 1, 1>, pad = array<i64: 3, 4, 8, 9>,
- // CHECK-SAME: stride = array<i64: 1, 1>}
- %input_zp = "tosa.const"() {value = dense<-22> : tensor<1xi8>} : () -> tensor<1xi8>
- %weight_zp = "tosa.const"() {value = dense<42> : tensor<1xi8>} : () -> tensor<1xi8>
+ // CHECK-DAG: %[[INPUT_ZP:.+]] = "tosa.const"() <{value = dense<-22> : tensor<1xi8>}> : () -> tensor<1xi8>
+ // CHECK-DAG: %[[WEIGHT_ZP:.+]] = "tosa.const"() <{value = dense<42> : tensor<1xi8>}> : () -> tensor<1xi8>
+ // CHECK-DAG: %[[REV0:.+]] = tosa.reverse %arg1 {axis = 1 : i32}
+ // CHECK-DAG: %[[REV1:.+]] = tosa.reverse %[[REV0]] {axis = 2 : i32}
+ // CHECK: tosa.conv2d %arg0, %[[REV1]], %arg2, %[[INPUT_ZP]], %[[WEIGHT_ZP]] {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 3, 4, 8, 9>, stride = array<i64: 1, 1>}
+ %input_zp = "tosa.const"() <{value = dense<-22> : tensor<1xi8>}> : () -> tensor<1xi8>
+ %weight_zp = "tosa.const"() <{value = dense<42> : tensor<1xi8>}> : () -> tensor<1xi8>
%0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %input_zp, %weight_zp {
acc_type = i32,
out_pad = array<i64: 1, 2, 3, 4>,
- out_shape = array<i64: -1, -1, -1, -1>,
stride = array<i64: 1, 1>} : (tensor<2x16x14x3xi8>, tensor<5x3x6x3xi8>, tensor<5xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<2x21x26x5xi32>
return %0 : tensor<2x21x26x5xi32>
}
@@ -160,12 +156,11 @@ func.func @transpose_conv2d_strided_overpad(%arg0 : tensor<1x16x1x1xi8>, %arg1 :
// CHECK: %[[PAD_RESULT:.+]] = tosa.pad %[[RESHAPE_RESULT_1]], %[[RESULT_PAD]]
// CHECK: %[[RESHAPE_ARG2:.+]] = tosa.reshape %arg2, %[[CONST10]]
// CHECK: %[[ADD:.+]] = tosa.add %[[PAD_RESULT]], %[[RESHAPE_ARG2]]
- %input_zp = "tosa.const"() {value = dense<-103> : tensor<1xi8>} : () -> tensor<1xi8>
- %weight_zp = "tosa.const"() {value = dense<93> : tensor<1xi8>} : () -> tensor<1xi8>
+ %input_zp = "tosa.const"() <{value = dense<-103> : tensor<1xi8>}> : () -> tensor<1xi8>
+ %weight_zp = "tosa.const"() <{value = dense<93> : tensor<1xi8>}> : () -> tensor<1xi8>
%2 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %input_zp, %weight_zp {
acc_type = i32,
out_pad = array<i64: 2, 0, 0, 1>,
- out_shape = array<i64: 1, -1, -1, 1>,
stride = array<i64: 1, 2>} :
(tensor<1x16x1x1xi8>, tensor<1x2x1x1xi8>, tensor<1xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x19x2x1xi32>
"func.return" (%2) : (tensor<1x19x2x1xi32>) -> ()
diff --git a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
index b87e9a78bf144..8a3dbfe17d686 100644
--- a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -907,7 +907,7 @@ func.func @depthwise_conv2d_strided(%arg0: tensor<1x13x14x1xf32>, %arg1: tensor<
// CHECK-LABEL: @transpose_conv2d_out_shape
func.func @transpose_conv2d_out_shape(%arg0: tensor<2x?x?x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x8x9x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, 8, 9, -1>, stride = array<i64: 1, 1>} : (tensor<2x?x?x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x8x9x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<2x?x?x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x8x9x5xf32>
return
}
@@ -916,7 +916,7 @@ func.func @transpose_conv2d_out_shape(%arg0: tensor<2x?x?x3xf32>, %arg1: tensor<
// CHECK-LABEL: @transpose_conv2d_static
func.func @transpose_conv2d_static(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x18x19x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x?x?x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x?x?x5xf32>
return
}
@@ -925,7 +925,7 @@ func.func @transpose_conv2d_static(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5
// CHECK-LABEL: @transpose_conv2d_static_strided
func.func @transpose_conv2d_static_strided(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x33x45x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 2, 3>} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x?x?x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 2, 3>} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x?x?x5xf32>
return
}
@@ -934,7 +934,7 @@ func.func @transpose_conv2d_static_strided(%arg0: tensor<2x16x14x3xf32>, %arg1:
// CHECK-LABEL: @transpose_conv2d_dynamic_input
func.func @transpose_conv2d_dynamic_input(%arg0: tensor<?x?x?x?xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<?x?x?x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<?x?x?x?xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<?x?x?x?xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x5xf32>
return
}
@@ -943,7 +943,7 @@ func.func @transpose_conv2d_dynamic_input(%arg0: tensor<?x?x?x?xf32>, %arg1: ten
// CHECK-LABEL: @transpose_conv2d_dynamic_weights
func.func @transpose_conv2d_dynamic_weights(%arg0: tensor<2x6x4x3xf32>, %arg1: tensor<?x?x?x?xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x?x?x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<2x6x4x3xf32>, tensor<?x?x?x?xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x?x?x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<2x6x4x3xf32>, tensor<?x?x?x?xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x?x?x5xf32>
return
}
@@ -952,7 +952,7 @@ func.func @transpose_conv2d_dynamic_weights(%arg0: tensor<2x6x4x3xf32>, %arg1: t
// CHECK-LABEL: @transpose_conv2d_dynamic_bias
func.func @transpose_conv2d_dynamic_bias(%arg0: tensor<2x6x4x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<?xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x8x9x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<2x6x4x3xf32>, tensor<5x3x6x3xf32>, tensor<?xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x8x9x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<2x6x4x3xf32>, tensor<5x3x6x3xf32>, tensor<?xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x8x9x5xf32>
return
}
@@ -961,14 +961,14 @@ func.func @transpose_conv2d_dynamic_bias(%arg0: tensor<2x6x4x3xf32>, %arg1: tens
// CHECK-LABEL: @transpose_conv2d_padded
func.func @transpose_conv2d_padded(%arg0: tensor<2x9x11x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x10x13x5xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 1, 0, 3, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<2x9x11x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x10x13x5xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 1, 0, 3, 0>, stride = array<i64: 1, 1>} : (tensor<2x9x11x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<2x10x13x5xf32>
return
}
// CHECK-LABEL: @transpose_conv2d_strided
func.func @transpose_conv2d_strided(%arg0: tensor<1x5x7x1xf32>, %arg1: tensor<1x1x1x1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<1x13x13x1xf32>
- %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 3, 2>} : (tensor<1x5x7x1xf32>, tensor<1x1x1x1xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x13x13x1xf32>
+ %0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 3, 2>} : (tensor<1x5x7x1xf32>, tensor<1x1x1x1xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x13x13x1xf32>
return
}
|
GeorgeARM
reviewed
Feb 28, 2025
Signed-off-by: Suraj Sudhir <[email protected]> Change-Id: I654a2489572859dafc0d0928cad8b4086ef1ba30
Jerry-Ge
force-pushed
the
remove_outshape
branch
from
9bad506 to
afbe504
Compare
GeorgeARM
approved these changes
Feb 28, 2025
cheezeburglar
pushed a commit
to cheezeburglar/llvm-project
that referenced
this pull request
Feb 28, 2025
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
5 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Removed out_shape from transpose_conv2d to match the latest TOSA v1.0 specification (https://www.mlplatform.org/tosa/tosa_spec.html#_transpose_conv2d).