[Mlir-commits] [mlir] [MLIR][TOSA] Fix Conv3D bias dim check (PR #137296)
Thomas Preud'homme
llvmlistbot at llvm.org
Fri Apr 25 04:01:20 PDT 2025
https://github.com/RoboTux updated https://github.com/llvm/llvm-project/pull/137296
>From 56b641334065444db43180ba251dcc440dbc8b90 Mon Sep 17 00:00:00 2001
From: Thomas Preud'homme <thomas.preudhomme at arm.com>
Date: Fri, 25 Apr 2025 09:27:31 +0100
Subject: [PATCH 1/2] [MLIR][TOSA] Fix Conv3D bias dim check
verifyConvOpErrorIf() assumes output channel is the 4th dimension of the
output type but this is wrong for conv3d which now uses that verifier.
Use rank - 1 which works accross the operations using this verifier
(conv2d, conv3d and depthwise_conv3d).
---
mlir/lib/Dialect/Tosa/IR/TosaOps.cpp | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
index 751ae785bda6f..17873444b2d71 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -558,7 +558,8 @@ static LogicalResult verifyConvOpErrorIf(T op) {
return success();
const int64_t biasChannels = biasType.getDimSize(0);
- const int64_t outputChannels = outputType.getDimSize(3);
+ const int64_t outputChannels =
+ outputType.getDimSize(outputType.getRank() - 1);
if (biasChannels == ShapedType::kDynamic ||
outputChannels == ShapedType::kDynamic)
// Skip following checks if biasChannels or outputChannels is dynamic dim
>From cb53639dec50c008109ff5333eace94c725d9bd7 Mon Sep 17 00:00:00 2001
From: Thomas Preud'homme <thomas.preudhomme at arm.com>
Date: Fri, 25 Apr 2025 11:51:11 +0100
Subject: [PATCH 2/2] Update testcases
---
mlir/test/Dialect/Tosa/availability.mlir | 4 ++--
mlir/test/Dialect/Tosa/invalid_extension.mlir | 8 ++++----
mlir/test/Dialect/Tosa/ops.mlir | 16 ++++++++--------
.../Dialect/Tosa/profile_pro_fp_unsupported.mlir | 4 ++--
.../Tosa/profile_pro_int_unsupported.mlir | 4 ++--
mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir | 16 ++++++++--------
6 files changed, 26 insertions(+), 26 deletions(-)
diff --git a/mlir/test/Dialect/Tosa/availability.mlir b/mlir/test/Dialect/Tosa/availability.mlir
index 7374cfd1145b9..75126a11ac504 100644
--- a/mlir/test/Dialect/Tosa/availability.mlir
+++ b/mlir/test/Dialect/Tosa/availability.mlir
@@ -38,12 +38,12 @@ func.func @test_conv2d(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<8x1x1x4xf32>, %
// -----
// CHECK-LABEL: conv3d
-func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>) -> tensor<1x4x8x21x34xf32> {
+func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<34xf32>) -> tensor<1x4x8x21x34xf32> {
// CHECK: profiles: [ [pro_int, pro_fp] ]
// CHECK: extensions: [ [int4, int16, fp8e4m3, fp8e5m2, bf16] ]
%input_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf32>}> : () -> tensor<1xf32>
%weight_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf32>}> : () -> tensor<1xf32>
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<34xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32>
return %0 : tensor<1x4x8x21x34xf32>
}
diff --git a/mlir/test/Dialect/Tosa/invalid_extension.mlir b/mlir/test/Dialect/Tosa/invalid_extension.mlir
index c862ae375f33b..bb0d3b46955a1 100644
--- a/mlir/test/Dialect/Tosa/invalid_extension.mlir
+++ b/mlir/test/Dialect/Tosa/invalid_extension.mlir
@@ -26,9 +26,9 @@ func.func @test_conv2d(%arg0: tensor<1x4x4x4xi8>, %arg1: tensor<8x1x1x4xi4>, %ar
}
// -----
-func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xi16>, %arg1: tensor<34x1x1x1x17xi8>, %arg2: tensor<21xi48>, %arg3: tensor<1xi16>, %arg4: tensor<1xi8>) -> tensor<1x4x8x21x34xi48> {
+func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xi16>, %arg1: tensor<34x1x1x1x17xi8>, %arg2: tensor<34xi48>, %arg3: tensor<1xi16>, %arg4: tensor<1xi8>) -> tensor<1x4x8x21x34xi48> {
// expected-error at +1 {{'tosa.conv3d' op illegal: requires [int16] but not enabled in target}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = i48, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xi16>, tensor<34x1x1x1x17xi8>, tensor<21xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<1x4x8x21x34xi48>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = i48, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xi16>, tensor<34x1x1x1x17xi8>, tensor<34xi48>, tensor<1xi16>, tensor<1xi8>) -> tensor<1x4x8x21x34xi48>
return %0 : tensor<1x4x8x21x34xi48>
}
@@ -445,10 +445,10 @@ func.func @test_conv2d_non_const_input_zp(%arg0: tensor<1x4x4x4xi8>, %arg1: tens
// -----
-func.func @test_conv3d_non_const_weight_zp(%arg0: tensor<1x4x8x21x17xi8>, %arg1: tensor<34x1x1x1x17xi8>, %arg2: tensor<21xi32>, %arg3: tensor<1xi8>) -> tensor<1x4x8x21x34xi32> {
+func.func @test_conv3d_non_const_weight_zp(%arg0: tensor<1x4x8x21x17xi8>, %arg1: tensor<34x1x1x1x17xi8>, %arg2: tensor<34xi32>, %arg3: tensor<1xi8>) -> tensor<1x4x8x21x34xi32> {
%input_zp = "tosa.const"() {values = dense<0> : tensor<1xi8> } : () -> tensor<1xi8>
// expected-error at +1 {{'tosa.conv3d' op expected compile time resolvable constant, but got variable value for operand #4}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %input_zp, %arg3 {acc_type = i32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xi8>, tensor<34x1x1x1x17xi8>, tensor<21xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x8x21x34xi32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %input_zp, %arg3 {acc_type = i32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xi8>, tensor<34x1x1x1x17xi8>, tensor<34xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x8x21x34xi32>
return %0 : tensor<1x4x8x21x34xi32>
}
diff --git a/mlir/test/Dialect/Tosa/ops.mlir b/mlir/test/Dialect/Tosa/ops.mlir
index c1181825f0c97..b64074e412ed1 100644
--- a/mlir/test/Dialect/Tosa/ops.mlir
+++ b/mlir/test/Dialect/Tosa/ops.mlir
@@ -104,15 +104,15 @@ func.func @test_conv2d_q8xi4(%arg0: tensor<1x11x11x3xi8>) -> tensor<1x1x1x3xi8>
// -----
// CHECK-LABEL: conv3d
-func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> {
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32>
+func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<34xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> {
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<34xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32>
return %0 : tensor<1x4x8x21x34xf32>
}
// -----
// CHECK-LABEL: conv3d_with_local_bound
-func.func @test_conv3d_with_local_bound(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<21xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> {
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>, local_bound = true} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<21xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32>
+func.func @test_conv3d_with_local_bound(%arg0: tensor<1x4x8x21x17xf32>, %arg1: tensor<34x1x1x1x17xf32>, %arg2: tensor<34xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) -> tensor<1x4x8x21x34xf32> {
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>, local_bound = true} : (tensor<1x4x8x21x17xf32>, tensor<34x1x1x1x17xf32>, tensor<34xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x4x8x21x34xf32>
return %0 : tensor<1x4x8x21x34xf32>
}
@@ -823,8 +823,8 @@ func.func @test_conv2d_f8E5M2(%arg0: tensor<1x4x4x4xf8E5M2>, %arg1: tensor<8x1x1
// -----
// CHECK-LABEL: conv3d_f8E5M2
-func.func @test_conv3d_f8E5M2(%arg0: tensor<1x4x8x21x17xf8E5M2>, %arg1: tensor<34x1x1x1x17xf8E5M2>, %arg2: tensor<21xf16>, %arg3: tensor<1xf8E5M2>, %arg4: tensor<1xf8E5M2>) -> tensor<1x4x8x21x34xf16> {
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f16, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf8E5M2>, tensor<34x1x1x1x17xf8E5M2>, tensor<21xf16>, tensor<1xf8E5M2>, tensor<1xf8E5M2>) -> tensor<1x4x8x21x34xf16>
+func.func @test_conv3d_f8E5M2(%arg0: tensor<1x4x8x21x17xf8E5M2>, %arg1: tensor<34x1x1x1x17xf8E5M2>, %arg2: tensor<34xf16>, %arg3: tensor<1xf8E5M2>, %arg4: tensor<1xf8E5M2>) -> tensor<1x4x8x21x34xf16> {
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f16, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf8E5M2>, tensor<34x1x1x1x17xf8E5M2>, tensor<34xf16>, tensor<1xf8E5M2>, tensor<1xf8E5M2>) -> tensor<1x4x8x21x34xf16>
return %0 : tensor<1x4x8x21x34xf16>
}
@@ -968,8 +968,8 @@ func.func @test_conv2d_f8E4M3FN(%arg0: tensor<1x4x4x4xf8E4M3FN>, %arg1: tensor<8
// -----
// CHECK-LABEL: conv3d_f8E4M3FN
-func.func @test_conv3d_f8E4M3FN(%arg0: tensor<1x4x8x21x17xf8E4M3FN>, %arg1: tensor<34x1x1x1x17xf8E4M3FN>, %arg2: tensor<21xf16>, %arg3: tensor<1xf8E4M3FN>, %arg4: tensor<1xf8E4M3FN>) -> tensor<1x4x8x21x34xf16> {
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f16, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf8E4M3FN>, tensor<34x1x1x1x17xf8E4M3FN>, tensor<21xf16>, tensor<1xf8E4M3FN>, tensor<1xf8E4M3FN>) -> tensor<1x4x8x21x34xf16>
+func.func @test_conv3d_f8E4M3FN(%arg0: tensor<1x4x8x21x17xf8E4M3FN>, %arg1: tensor<34x1x1x1x17xf8E4M3FN>, %arg2: tensor<34xf16>, %arg3: tensor<1xf8E4M3FN>, %arg4: tensor<1xf8E4M3FN>) -> tensor<1x4x8x21x34xf16> {
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f16, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf8E4M3FN>, tensor<34x1x1x1x17xf8E4M3FN>, tensor<34xf16>, tensor<1xf8E4M3FN>, tensor<1xf8E4M3FN>) -> tensor<1x4x8x21x34xf16>
return %0 : tensor<1x4x8x21x34xf16>
}
diff --git a/mlir/test/Dialect/Tosa/profile_pro_fp_unsupported.mlir b/mlir/test/Dialect/Tosa/profile_pro_fp_unsupported.mlir
index efbb9e9d1843f..72669c62c95ca 100644
--- a/mlir/test/Dialect/Tosa/profile_pro_fp_unsupported.mlir
+++ b/mlir/test/Dialect/Tosa/profile_pro_fp_unsupported.mlir
@@ -33,9 +33,9 @@ func.func @test_conv2d(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<8x1x1x4xf32>, %
}
// -----
-func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xf16>, %arg1: tensor<34x1x1x1x17xf16>, %arg2: tensor<21xf16>, %arg3: tensor<1xf16>, %arg4: tensor<1xf16>) -> tensor<1x4x8x21x34xf16> {
+func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xf16>, %arg1: tensor<34x1x1x1x17xf16>, %arg2: tensor<34xf16>, %arg3: tensor<1xf16>, %arg4: tensor<1xf16>) -> tensor<1x4x8x21x34xf16> {
// expected-error at +1 {{'tosa.conv3d' op illegal: requires [pro_fp] but not enabled in target}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf16>, tensor<34x1x1x1x17xf16>, tensor<21xf16>, tensor<1xf16>, tensor<1xf16>) -> tensor<1x4x8x21x34xf16>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf16>, tensor<34x1x1x1x17xf16>, tensor<34xf16>, tensor<1xf16>, tensor<1xf16>) -> tensor<1x4x8x21x34xf16>
return %0 : tensor<1x4x8x21x34xf16>
}
diff --git a/mlir/test/Dialect/Tosa/profile_pro_int_unsupported.mlir b/mlir/test/Dialect/Tosa/profile_pro_int_unsupported.mlir
index b102eea5699dd..e98b906377b22 100644
--- a/mlir/test/Dialect/Tosa/profile_pro_int_unsupported.mlir
+++ b/mlir/test/Dialect/Tosa/profile_pro_int_unsupported.mlir
@@ -38,9 +38,9 @@ func.func @test_conv2d(%arg0: tensor<1x4x4x4xi8>, %arg1: tensor<8x1x1x4xi8>, %ar
}
// -----
-func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xi8>, %arg1: tensor<34x1x1x1x17xi8>, %arg2: tensor<21xi32>, %arg3: tensor<1xi8>, %arg4: tensor<1xi8>) -> tensor<1x4x8x21x34xi32> {
+func.func @test_conv3d(%arg0: tensor<1x4x8x21x17xi8>, %arg1: tensor<34x1x1x1x17xi8>, %arg2: tensor<34xi32>, %arg3: tensor<1xi8>, %arg4: tensor<1xi8>) -> tensor<1x4x8x21x34xi32> {
// expected-error at +1 {{'tosa.conv3d' op illegal: requires [pro_int] but not enabled in target}}
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = i32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xi8>, tensor<34x1x1x1x17xi8>, tensor<21xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x8x21x34xi32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = i32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xi8>, tensor<34x1x1x1x17xi8>, tensor<34xi32>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x8x21x34xi32>
return %0 : tensor<1x4x8x21x34xi32>
}
diff --git a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
index c6ac8074c0326..1ad1e6c76c294 100644
--- a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -824,18 +824,18 @@ func.func @conv2d_strided(%input: tensor<1x13x15x1xf32>, %weights: tensor<1x1x1x
// -----
// CHECK-LABEL: @conv3d_static
-func.func @conv3d_static(%input: tensor<2x8x9x10x3xf32>, %weights: tensor<5x3x6x4x3xf32>, %bias: tensor<7xf32>, %input_zp: tensor<1xf32>, %weight_zp: tensor<1xf32>) -> () {
+func.func @conv3d_static(%input: tensor<2x8x9x10x3xf32>, %weights: tensor<5x3x6x4x3xf32>, %bias: tensor<5xf32>, %input_zp: tensor<1xf32>, %weight_zp: tensor<1xf32>) -> () {
// CHECK: -> tensor<2x6x4x7x5xf32>
- %0 = tosa.conv3d %input, %weights, %bias, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<7xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = tosa.conv3d %input, %weights, %bias, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
return
}
// -----
// CHECK-LABEL: @conv3d_dynamic_input
-func.func @conv3d_dynamic_input(%arg0: tensor<?x?x?x?x?xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<7xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
+func.func @conv3d_dynamic_input(%arg0: tensor<?x?x?x?x?xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<?x?x?x?x5xf32>
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<?x?x?x?x?xf32>, tensor<5x3x6x4x3xf32>, tensor<7xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<?x?x?x?x?xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
return
}
@@ -860,18 +860,18 @@ func.func @conv3d_dynamic_bias(%arg0: tensor<2x8x9x10x3xf32>, %arg1: tensor<5x3x
// -----
// CHECK-LABEL: @conv3d_padded
-func.func @conv3d_padded(%arg0: tensor<2x8x9x10x3xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<18xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
+func.func @conv3d_padded(%arg0: tensor<2x8x9x10x3xf32>, %arg1: tensor<5x3x6x4x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x9x11x18x5xf32>
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 1, 2, 3, 4, 5, 6>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<18xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 1, 2, 3, 4, 5, 6>, stride = array<i64: 1, 1, 1>} : (tensor<2x8x9x10x3xf32>, tensor<5x3x6x4x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
return
}
// -----
// CHECK-LABEL: @conv3d_dilated
-func.func @conv3d_dilated(%arg0: tensor<2x12x14x16x3xf32>, %arg1: tensor<5x3x6x2x3xf32>, %arg2: tensor<12xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
+func.func @conv3d_dilated(%arg0: tensor<2x12x14x16x3xf32>, %arg1: tensor<5x3x6x2x3xf32>, %arg2: tensor<5xf32>, %arg3: tensor<1xf32>, %arg4: tensor<1xf32>) {
// CHECK: -> tensor<2x6x4x12x5xf32>
- %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 3, 2, 4>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x12x14x16x3xf32>, tensor<5x3x6x2x3xf32>, tensor<12xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
+ %0 = tosa.conv3d %arg0, %arg1, %arg2, %arg3, %arg4 {acc_type = f32, dilation = array<i64: 3, 2, 4>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<2x12x14x16x3xf32>, tensor<5x3x6x2x3xf32>, tensor<5xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<?x?x?x?x?xf32>
return
}
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