================
@@ -1824,27 +1825,47 @@ func.func @unpack_invalid_outer_dims_perm(%source:
tensor<128x256xf32>, %dest: t
// -----
+func.func @pack_with_artificial_padding(%input: tensor<9xf32>, %output:
tensor<3x8xf32>) -> tensor<3x8xf32> {
+ %cst = arith.constant 0.0 : f32
+ // expected-error@+1 {{expected 'tensor<2x8xf32>' for the unpacked domain
value, got 'tensor<3x8xf32>'}}
+ %0 = linalg.pack %input padding_value(%cst : f32) inner_dims_pos = [0]
+ inner_tiles = [8] into %output
+ : tensor<9xf32> -> tensor<3x8xf32>
+ return %0 : tensor<3x8xf32>
+}
+
+// -----
+
// The outer dims in the output tensor are incorrectly/unexpectedly transposed.
// This could be fixed by adding `outer_dims_perm = [1, 0]` (the default value
assumes no transpose).
func.func @pack_invalid_result_shape(%input: tensor<256x128xf32>, %output:
tensor<4x16x32x16xf32>) -> tensor<4x16x32x16xf32> {
- // expected-error@+1 {{the shape of output is not large enough to hold the
packed data. Expected at least 'tensor<16x4x32x16xf32>', got
'tensor<4x16x32x16xf32>'}}
+ // expected-error@+1 {{expected 'tensor<16x4x32x16xf32>' for the unpacked
domain value, got 'tensor<4x16x32x16xf32>'}}
%0 = linalg.pack %input inner_dims_pos = [1, 0] inner_tiles = [32, 16] into
%output : tensor<256x128xf32> -> tensor<4x16x32x16xf32>
return %0 : tensor<4x16x32x16xf32>
}
// -----
-func.func @pack_invalid(%input: tensor<256x128xf32>, %output:
tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> {
- // expected-error@+1 {{the shape of output is not large enough to hold the
packed data. Expected at least 'tensor<8x8x16x32xf32>', got
'tensor<8x8x32x16xf32>'}}
- %0 = linalg.pack %input inner_dims_pos = [1, 0] inner_tiles = [16, 32] into
%output : tensor<256x128xf32> -> tensor<8x8x32x16xf32>
- return %0 : tensor<8x8x32x16xf32>
+func.func @pack_invalid(%input: tensor<256x128xf32>, %output:
tensor<8x7x16x32xf32>) -> tensor<8x7x16x32xf32> {
+ // expected-error@+1 {{expected 'tensor<8x8x16x32xf32>' for the unpacked
domain value, got 'tensor<8x7x16x32xf32>'}}
+ %0 = linalg.pack %input inner_dims_pos = [1, 0] inner_tiles = [16, 32] into
%output : tensor<256x128xf32> -> tensor<8x7x16x32xf32>
+ return %0 : tensor<8x7x16x32xf32>
+}
+
+// -----
+
+func.func @unpack_with_slicing_tiles(%input: tensor<3x8xf32>, %output:
tensor<9xf32>) -> tensor<9xf32> {
----------------
hanhanW wrote:
SG, let's use `artificial` for consistency.
https://github.com/llvm/llvm-project/pull/149624
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