|
| 1 | +// RUN: mlir-opt %s -transform-interpreter -split-input-file -verify-diagnostics |
| 2 | + |
| 3 | +func.func @conv1d_nwc_wcf_dyn_ch_dim(%input: memref<4x6x?xf32>, %filter: memref<1x?x8xf32>, %output: memref<4x2x8xf32>) { |
| 4 | + // expected-error @+1 {{Attempted to vectorize, but failed}} |
| 5 | + linalg.conv_1d_nwc_wcf |
| 6 | + {dilations = dense<1> : tensor<1xi64>, strides = dense<3> : tensor<1xi64>} |
| 7 | + ins(%input, %filter : memref<4x6x?xf32>, memref<1x?x8xf32>) |
| 8 | + outs(%output : memref<4x2x8xf32>) |
| 9 | + return |
| 10 | +} |
| 11 | + |
| 12 | +module attributes {transform.with_named_sequence} { |
| 13 | + transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { |
| 14 | + %0 = transform.structured.match ops{["linalg.conv_1d_nwc_wcf"]} in %arg1 : (!transform.any_op) -> !transform.any_op |
| 15 | + transform.structured.vectorize %0 : !transform.any_op |
| 16 | + transform.yield |
| 17 | + } |
| 18 | +} |
| 19 | + |
| 20 | +// ----- |
| 21 | + |
| 22 | +func.func @depthwise_conv1d_nwc_wc_dyn_ch_dim(%input: memref<3x5x?xf32>, %filter: memref<2x?xf32>, %output: memref<3x2x?xf32>) { |
| 23 | + // expected-error @+1 {{Attempted to vectorize, but failed}} |
| 24 | + linalg.depthwise_conv_1d_nwc_wc |
| 25 | + {dilations = dense<2> : tensor<1xi64>, strides = dense<1> : tensor<1xi64>} |
| 26 | + ins(%input, %filter : memref<3x5x?xf32>, memref<2x?xf32>) |
| 27 | + outs(%output : memref<3x2x?xf32>) |
| 28 | + return |
| 29 | +} |
| 30 | + |
| 31 | +module attributes {transform.with_named_sequence} { |
| 32 | + transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { |
| 33 | + %0 = transform.structured.match ops{["linalg.depthwise_conv_1d_nwc_wc"]} in %arg1 : (!transform.any_op) -> !transform.any_op |
| 34 | + transform.structured.vectorize %0 : !transform.any_op |
| 35 | + transform.yield |
| 36 | + } |
| 37 | +} |
| 38 | + |
| 39 | +// ----- |
| 40 | + |
| 41 | +func.func @depthwise_conv1d_nwc_wc_dyn_w_dim(%input: memref<3x?x3xf32>, %filter: memref<2x3xf32>, %output: memref<3x?x3xf32>) { |
| 42 | + // expected-error @+1 {{Attempted to vectorize, but failed}} |
| 43 | + linalg.depthwise_conv_1d_nwc_wc |
| 44 | + {dilations = dense<2> : tensor<1xi64>, strides = dense<1> : tensor<1xi64>} |
| 45 | + ins(%input, %filter : memref<3x?x3xf32>, memref<2x3xf32>) |
| 46 | + outs(%output : memref<3x?x3xf32>) |
| 47 | + return |
| 48 | +} |
| 49 | + |
| 50 | +module attributes {transform.with_named_sequence} { |
| 51 | + transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { |
| 52 | + %0 = transform.structured.match ops{["linalg.depthwise_conv_1d_nwc_wc"]} in %arg1 : (!transform.any_op) -> !transform.any_op |
| 53 | + transform.structured.vectorize %0 : !transform.any_op |
| 54 | + transform.yield |
| 55 | + } |
| 56 | +} |
| 57 | + |
| 58 | +// ----- |
| 59 | + |
| 60 | +func.func @conv1d_dyn_w_dim(%input: tensor<?xf32>, %filter: tensor<4xf32>, %output: tensor<?xf32>) -> tensor<?xf32> { |
| 61 | + // expected-error @+1 {{Attempted to vectorize, but failed}} |
| 62 | + %0 = linalg.conv_1d ins(%input, %filter : tensor<?xf32>, tensor<4xf32>) |
| 63 | + outs(%output : tensor<?xf32>) -> tensor<?xf32> |
| 64 | + return %0 : tensor<?xf32> |
| 65 | +} |
| 66 | + |
| 67 | +module attributes {transform.with_named_sequence} { |
| 68 | + transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) { |
| 69 | + %0 = transform.structured.match ops{["linalg.conv_1d"]} in %arg1 : (!transform.any_op) -> !transform.any_op |
| 70 | + transform.structured.vectorize %0 : !transform.any_op |
| 71 | + transform.yield |
| 72 | + } |
| 73 | +} |
0 commit comments