[mlir][linalg] Document ops not supported by the vectoriser (nfc) (#81500)

Adds a test to help document Linalg Ops that are currently not supported
by the vectoriser (i.e. the logic to vectorise these is missing). The
list is not exhaustive.

1 files changed, 73 insertions, 0 deletions

diff --git a/mlir/test/Dialect/Linalg/vectorization-unsupported.mlir b/mlir/test/Dialect/Linalg/vectorization-unsupported.mlir
new file mode 100644
index 0000000..a1a5239
--- /dev/null
+++ b/mlir/test/Dialect/Linalg/vectorization-unsupported.mlir
@@ -0,0 +1,73 @@
+// RUN: mlir-opt %s -transform-interpreter -split-input-file -verify-diagnostics
+
+func.func @conv1d_nwc_wcf_dyn_ch_dim(%input: memref<4x6x?xf32>, %filter: memref<1x?x8xf32>, %output: memref<4x2x8xf32>) {
+  // expected-error @+1 {{Attempted to vectorize, but failed}}
+  linalg.conv_1d_nwc_wcf
+    {dilations = dense<1> : tensor<1xi64>, strides = dense<3> : tensor<1xi64>}
+    ins(%input, %filter : memref<4x6x?xf32>, memref<1x?x8xf32>)
+    outs(%output : memref<4x2x8xf32>)
+  return
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.conv_1d_nwc_wcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    transform.structured.vectorize %0 : !transform.any_op
+    transform.yield
+  }
+}
+
+// -----
+
+func.func @depthwise_conv1d_nwc_wc_dyn_ch_dim(%input: memref<3x5x?xf32>, %filter: memref<2x?xf32>, %output: memref<3x2x?xf32>) {
+  // expected-error @+1 {{Attempted to vectorize, but failed}}
+  linalg.depthwise_conv_1d_nwc_wc
+    {dilations = dense<2> : tensor<1xi64>, strides = dense<1> : tensor<1xi64>}
+    ins(%input, %filter : memref<3x5x?xf32>, memref<2x?xf32>)
+    outs(%output : memref<3x2x?xf32>)
+  return
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.depthwise_conv_1d_nwc_wc"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    transform.structured.vectorize %0 : !transform.any_op
+    transform.yield
+  }
+}
+
+// -----
+
+func.func @depthwise_conv1d_nwc_wc_dyn_w_dim(%input: memref<3x?x3xf32>, %filter: memref<2x3xf32>, %output: memref<3x?x3xf32>) {
+  // expected-error @+1 {{Attempted to vectorize, but failed}}
+  linalg.depthwise_conv_1d_nwc_wc
+    {dilations = dense<2> : tensor<1xi64>, strides = dense<1> : tensor<1xi64>}
+    ins(%input, %filter : memref<3x?x3xf32>, memref<2x3xf32>)
+    outs(%output : memref<3x?x3xf32>)
+  return
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.depthwise_conv_1d_nwc_wc"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    transform.structured.vectorize %0 : !transform.any_op
+    transform.yield
+  }
+}
+
+// -----
+
+func.func @conv1d_dyn_w_dim(%input: tensor<?xf32>, %filter: tensor<4xf32>, %output: tensor<?xf32>) -> tensor<?xf32> {
+  // expected-error @+1 {{Attempted to vectorize, but failed}}
+  %0 = linalg.conv_1d ins(%input, %filter : tensor<?xf32>, tensor<4xf32>)
+                     outs(%output : tensor<?xf32>) -> tensor<?xf32>
+  return %0 : tensor<?xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.conv_1d"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    transform.structured.vectorize %0 : !transform.any_op
+    transform.yield
+  }
+}