| // RUN: mlir-opt -split-input-file -verify-diagnostics %s |
| |
| func @test_conv_op_not_linalg_op(%arg0 : tensor<?xf32>, %arg1 : tensor<?xf32>, |
| %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{expected a LinalgOp}} |
| %0 = "test.conv_op_not_linalg_op"(%arg0, %arg1, %arg2) |
| : (tensor<?xf32>, tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| // Check for number of operands being >= 2. |
| #map = affine_map<(d0) -> (d0)> |
| func @test_conv_op_wrong_num_operands(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{expected op with 2 inputs and 1 output}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [#map, #map], |
| iterator_types = ["parallel"]} |
| ins(%arg0 : tensor<?xf32>) outs(%arg1 : tensor<?xf32>) { |
| ^bb0(%arg2 : f32, %arg3 : f32): |
| linalg.yield %arg3 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| func @test_conv_op_wrong_input_indexing_map1(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{unexpected input index map for convolution}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1) -> (d0 * 2)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| func @test_conv_op_wrong_input_indexing_map2(%arg0 : tensor<?x?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{unexpected input index map for convolution}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1) -> (d0 + d1, d0)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| func @test_conv_op_filter_index_map_not_projection(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{expected output/filter indexing maps to be projected permutations}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d1 + d0)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| func @test_conv_op_output_index_map_not_projection(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{expected output/filter indexing maps to be projected permutations}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1) -> (d0)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0 + d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| // Convolution op illegal if a loop dimension is used to access |
| // output, filter and is convolved. |
| func @test_conv_op_output_filter_convolved(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{unexpected loop dimension for convolution op}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1) -> (d0 + d1)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| // Convolution op illegal if a loop dimension is used only in the output. |
| func @test_conv_op_output_only_dim(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{unexpected loop dimension for convolution op}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1, d2) -> (d0 + d1)>, |
| affine_map<(d0, d1, d2) -> (d1)>, |
| affine_map<(d0, d1, d2) -> (d0, d2)>], |
| iterator_types = ["parallel", "reduction", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| // Convolution op illegal if a loop dimension is used only in the filter. |
| func @test_conv_op_filter_only_dim(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?x?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{unexpected loop dimension for convolution op}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1, d2) -> (d0 + d1)>, |
| affine_map<(d0, d1, d2) -> (d1, d2)>, |
| affine_map<(d0, d1, d2) -> (d0)>], |
| iterator_types = ["parallel", "reduction", "reduction"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?x?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| // Convolution op illegal if a loop dimension is used only in the input. |
| func @test_conv_op_input_only_dim(%arg0 : tensor<?x?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{unexpected loop dimension for convolution op}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1, d2) -> (d0 + d1, d2)>, |
| affine_map<(d0, d1, d2) -> (d1)>, |
| affine_map<(d0, d1, d2) -> (d0)>], |
| iterator_types = ["parallel", "reduction", "reduction"]} |
| ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| // Convolution op illegal if a loop dimension accessing output is not parallel. |
| func @test_conv_op_non_output_access_loop_parallel(%arg0 : tensor<?xf32>, |
| %arg1 : tensor<?xf32>, %arg2 : tensor<?xf32>) -> tensor<?xf32> { |
| // expected-error @+1 {{expected all iterators not used to access outputs to be reduction}} |
| %0 = test.linalg_conv_op { |
| indexing_maps = [affine_map<(d0, d1) -> (d0 + d1)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%arg2 : tensor<?xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5 : f32): |
| linalg.yield %arg5 : f32 |
| } -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |