| // RUN: iree-dialects-opt --split-input-file --verify-diagnostics %s |
| |
| func.func @sort_invalid_dimension(%arg0: tensor<128xi32>) -> tensor<128xi32> { |
| // expected-error @+1 {{dimension must be within (0, 1]}} |
| %0 = iree_linalg_ext.sort dimension(1) |
| outs(%arg0 : tensor<128xi32>) { |
| ^bb0(%arg1: i32, %arg2: i32): // no predecessors |
| %1 = arith.cmpi sgt, %arg1, %arg2 : i32 |
| iree_linalg_ext.yield %1 : i1 |
| } -> tensor<128xi32> |
| return %0 : tensor<128xi32> |
| } |
| |
| // ----- |
| |
| func.func @sort_mismatch_rank(%arg0: tensor<?x?xi32>, %arg1: tensor<?xf32>) |
| -> (tensor<?x?xi32>, tensor<?xf32>) { |
| // expected-error @+1 {{expected operand 1 to be rank 2, same as other operands}} |
| %0:2 = iree_linalg_ext.sort dimension(0) |
| outs(%arg0, %arg1 : tensor<?x?xi32>, tensor<?xf32>) { |
| ^bb0(%arg2: i32, %arg3: i32, %arg4 : f32, %arg5 : f32): // no predecessors |
| %1 = arith.cmpf ogt, %arg4, %arg5 : f32 |
| iree_linalg_ext.yield %1 : i1 |
| } -> tensor<?x?xi32>, tensor<?xf32> |
| return %0#0, %0#1 : tensor<?x?xi32>, tensor<?xf32> |
| } |
| |
| // ----- |
| |
| func.func @sort_mismatch_shape(%arg0: tensor<?xi32>, %arg1: tensor<42xf32>) |
| -> (tensor<?xi32>, tensor<42xf32>) { |
| // expected-error @+1 {{expected operand 1 to have same shape as other operands}} |
| %0:2 = iree_linalg_ext.sort dimension(0) |
| outs(%arg0, %arg1 : tensor<?xi32>, tensor<42xf32>) { |
| ^bb0(%arg2: i32, %arg3: i32, %arg4 : f32, %arg5 : f32): // no predecessors |
| %1 = arith.cmpf ogt, %arg4, %arg5 : f32 |
| iree_linalg_ext.yield %1 : i1 |
| } -> tensor<?xi32>, tensor<42xf32> |
| return %0#0, %0#1 : tensor<?xi32>, tensor<42xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_extra_outputs( |
| %update : tensor<?x?xf32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xf32>) -> (tensor<?x?xf32>, tensor<?x?xf32>) { |
| // expected-error @+1 {{expected the number of tensor results (2) to be equal to the number of output tensors (1)}} |
| %0, %1 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xf32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32>, tensor<?x?xf32> |
| return %0, %1 : tensor<?x?xf32>, tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_mistmatch_dim_map_entries( |
| %update : tensor<?x?xf32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{invalid number of dimension map entries}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0, 1] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xf32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_duplicate_dim_map_entries( |
| %update : tensor<?x?xf32>, %indices : tensor<?x2xi32>, |
| %original : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{dimension map is invalid}} |
| %0 = iree_linalg_ext.scatter dimension_map = [1, 1] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xf32>, tensor<?x2xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_invalid_dim_map_entries( |
| %update : tensor<?x?xf32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{dimension map is invalid}} |
| %0 = iree_linalg_ext.scatter dimension_map = [2] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xf32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_output_type_mismatch( |
| %update : tensor<?x?xf32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xf32>) -> tensor<4x?xf32> { |
| // expected-error @+1 {{expected type of operand #2 ('tensor<?x?xf32>') to match type of corresponding result ('tensor<4x?xf32>')}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xf32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<4x?xf32> |
| return %0 : tensor<4x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_dim_mismatch( |
| %update : tensor<?x?xf32>, %indices : tensor<48x1xi32>, |
| %original : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{mismatch in shape of indices and update value at dim#0}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xf32>, tensor<48x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_dim_mismatch( |
| %update : tensor<64x?xf32>, %indices : tensor<48x1xi32>, |
| %original : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{mismatch in shape of indices and update value at dim#0}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<64x?xf32>, tensor<48x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_dim_mismatch( |
| %update : tensor<?x?x?x?xf32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{op update value rank exceeds the rank of the original value}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?x?x?xf32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_dim_mismatch( |
| %update : tensor<?x4xf32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x3xf32>) -> tensor<?x3xf32> { |
| // expected-error @+1 {{op shape of update value dim#1 exceeds original value at dim#1}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x4xf32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x3xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32): |
| %1 = arith.addf %arg1, %arg2 : f32 |
| iree_linalg_ext.yield %1 : f32 |
| } -> tensor<?x3xf32> |
| return %0 : tensor<?x3xf32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_region_type_mismatch( |
| %update : tensor<?x?xi32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi32>) -> tensor<?x?xi32> { |
| // expected-error @+1 {{expected region to have scalar argument of integer or float types}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi32>) { |
| ^bb0(%arg1: index, %arg2: index): |
| %1 = arith.addi %arg1, %arg2 : index |
| %2 = arith.index_cast %1 : index to i32 |
| iree_linalg_ext.yield %2 : i32 |
| } -> tensor<?x?xi32> |
| return %0 : tensor<?x?xi32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_region_type_mismatch( |
| %update : tensor<?x?xi32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi32>) -> tensor<?x?xi32> { |
| // expected-error @+1 {{mismatch in argument 0 of region 'i64' and element type of update value 'i32'}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi32>) { |
| ^bb0(%arg1: i64, %arg2: i32): |
| %1 = arith.trunci %arg1 : i64 to i32 |
| %2 = arith.addi %1, %arg2 : i32 |
| iree_linalg_ext.yield %2 : i32 |
| } -> tensor<?x?xi32> |
| return %0 : tensor<?x?xi32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_region_type_mismatch( |
| %update : tensor<?x?xi32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi32>) -> tensor<?x?xi32> { |
| // expected-error @+1 {{mismatch in argument 1 of region 'i64' and element type of original value 'i32'}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi32>) { |
| ^bb0(%arg1: i32, %arg2: i64): |
| %1 = arith.trunci %arg2 : i64 to i32 |
| %2 = arith.addi %1, %arg1 : i32 |
| iree_linalg_ext.yield %2 : i32 |
| } -> tensor<?x?xi32> |
| return %0 : tensor<?x?xi32> |
| } |
| |
| // ----- |
| |
| func.func @scatter_region_type_mismatch( |
| %update : tensor<?x?xi32>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi64>) -> tensor<?x?xi64> { |
| // expected-error @+1 {{mismatch in region argument types 'i32' and 'i64'}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi32>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi64>) { |
| ^bb0(%arg1: i32, %arg2: i64): |
| %1 = arith.extsi %arg1 : i32 to i64 |
| %2 = arith.addi %1, %arg2 : i64 |
| iree_linalg_ext.yield %2 : i64 |
| } -> tensor<?x?xi64> |
| return %0 : tensor<?x?xi64> |
| } |
| |
| // ----- |
| |
| func.func @scatter_region_type_mismatch( |
| %update : tensor<?x?xi64>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi64>) -> tensor<?x?xi64> { |
| // expected-error @+1 {{expected region to have two arguments}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi64>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi64>) { |
| ^bb0(%arg1: i64, %arg2: i64, %arg3 : i64): |
| %1 = arith.addi %arg1, %arg2 : i64 |
| iree_linalg_ext.yield %1 : i64 |
| } -> tensor<?x?xi64> |
| return %0 : tensor<?x?xi64> |
| } |
| |
| |
| // ----- |
| |
| func.func @scatter_yield_mismatch( |
| %update : tensor<?x?xi64>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi64>) -> tensor<?x?xi64> { |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi64>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi64>) { |
| ^bb0(%arg1: i64, %arg2: i64): |
| %1 = arith.addi %arg1, %arg2 : i64 |
| %2 = arith.trunci %1 : i64 to i32 |
| // expected-error @+1 {{mismatch in type of yielded value 'i32' and argument of the region 'i64'}} |
| iree_linalg_ext.yield %2 : i32 |
| } -> tensor<?x?xi64> |
| return %0 : tensor<?x?xi64> |
| } |
| |
| // ----- |
| |
| func.func @scatter_yield_mismatch( |
| %update : tensor<?x?xi64>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi64>) -> tensor<?x?xi64> { |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi64>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi64>) { |
| ^bb0(%arg1: i64, %arg2: i64): |
| %1 = arith.addi %arg1, %arg2 : i64 |
| %2 = arith.trunci %1 : i64 to i32 |
| // expected-error @+1 {{expected region to yield a single value}} |
| iree_linalg_ext.yield %1, %2 : i64, i32 |
| } -> tensor<?x?xi64> |
| return %0 : tensor<?x?xi64> |
| } |
| |
| // ----- |
| |
| func.func @scatter_index_depth_dynamic( |
| %update : tensor<?x?xi64>, %indices : tensor<?x?xi32>, |
| %original : tensor<?x?xi64>) -> tensor<?x?xi64> { |
| // expected-error @+1 {{expected index depth is static}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?x?xi64>, tensor<?x?xi32>) |
| outs(%original : tensor<?x?xi64>) { |
| ^bb0(%arg1: i64, %arg2: i64): |
| %1 = arith.addi %arg1, %arg2 : i64 |
| %2 = arith.trunci %1 : i64 to i32 |
| iree_linalg_ext.yield %1, %2 : i64, i32 |
| } -> tensor<?x?xi64> |
| return %0 : tensor<?x?xi64> |
| } |
| |
| // ----- |
| |
| func.func @scatter_original_rank_mismatch( |
| %update : tensor<?xi64>, %indices : tensor<?x1xi32>, |
| %original : tensor<?x?xi64>) -> tensor<?x?xi64> { |
| // expected-error @+1 {{op index depth and update value does not cover rank of original value}} |
| %0 = iree_linalg_ext.scatter dimension_map = [0] unique_indices(true) |
| ins(%update, %indices : tensor<?xi64>, tensor<?x1xi32>) |
| outs(%original : tensor<?x?xi64>) { |
| ^bb0(%arg1: i64, %arg2: i64): |
| %1 = arith.addi %arg1, %arg2 : i64 |
| %2 = arith.trunci %1 : i64 to i32 |
| iree_linalg_ext.yield %1, %2 : i64, i32 |
| } -> tensor<?x?xi64> |
| return %0 : tensor<?x?xi64> |
| } |
| |
| // ----- |
| |
| func.func @reverse_diff_element_type(%arg0: tensor<3x5xi32>) -> tensor<3x5xf32> { |
| %init = tensor.empty() : tensor<3x5xf32> |
| // expected-error @+1 {{expected input/output element types to be identical}} |
| %0 = iree_linalg_ext.reverse |
| dimensions(dense<0> : tensor<1xi64>) |
| ins(%arg0 : tensor<3x5xi32>) |
| outs(%init : tensor<3x5xf32>) : tensor<3x5xf32> |
| return %0 : tensor<3x5xf32> |
| } |
| |
| // ----- |
| |
| func.func @reverse_diff_shape(%arg0: tensor<3x5xi32>) -> tensor<3x6xi32> { |
| %init = tensor.empty() : tensor<3x6xi32> |
| // expected-error @+1 {{incompatible input/output shapes}} |
| %0 = iree_linalg_ext.reverse |
| dimensions(dense<0> : tensor<1xi64>) |
| ins(%arg0 : tensor<3x5xi32>) |
| outs(%init : tensor<3x6xi32>) : tensor<3x6xi32> |
| return %0 : tensor<3x6xi32> |
| } |
| |
| // ----- |
| |
| func.func @reverse_dup_dims(%arg0: tensor<3x5xi32>) -> tensor<3x5xi32> { |
| %init = tensor.empty() : tensor<3x5xi32> |
| // expected-error @+1 {{expected dimensions numbers are all unique}} |
| %0 = iree_linalg_ext.reverse |
| dimensions(dense<[0, 0]> : tensor<2xi64>) |
| ins(%arg0 : tensor<3x5xi32>) |
| outs(%init : tensor<3x5xi32>) : tensor<3x5xi32> |
| return %0 : tensor<3x5xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<2x10xf32>, %input_indices: tensor<2x10xi32>, %out_values : tensor<2x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<2x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{expected one or two input operands}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_indices, %input_indices, %input_indices : tensor<2x10xi32>, tensor<2x10xi32>, tensor<2x10xi32>) |
| outs(%out_values, %out_indices : tensor<2x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<2x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<2x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<2x10xi32>, %input_indices: tensor<2x10xi32>, %out_values : tensor<2x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<2x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{expected input/output value types to be identical}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_values, %input_indices : tensor<2x10xi32> , tensor<2x10xi32>) |
| outs(%out_values, %out_indices : tensor<2x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<2x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<2x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<2x10xf32>, %input_indices: tensor<2x10xf32>, %out_values : tensor<2x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<2x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{expected input/output indices types to be int}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_values, %input_indices : tensor<2x10xf32> , tensor<2x10xf32>) |
| outs(%out_values, %out_indices : tensor<2x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<2x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<2x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<10x2x10xf32>, %input_indices: tensor<10x2x10xi32>, %out_values : tensor<2x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<2x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{expected input/output to have the same rank}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_values, %input_indices : tensor<10x2x10xf32> , tensor<10x2x10xi32>) |
| outs(%out_values, %out_indices : tensor<2x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<2x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<2x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<3x10xf32>, %input_indices: tensor<2x10xi32>, %out_values : tensor<2x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<2x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{input indices/values shape must match}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_values, %input_indices : tensor<3x10xf32> , tensor<2x10xi32>) |
| outs(%out_values, %out_indices : tensor<2x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<2x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<2x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<2x10xf32>, %input_indices: tensor<2x10xi32>, %out_values : tensor<3x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<3x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{output indices/values shape must match}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_values, %input_indices : tensor<2x10xf32> , tensor<2x10xi32>) |
| outs(%out_values, %out_indices : tensor<3x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<3x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<3x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| func.func @topk_invalid(%input_values: tensor<3x10xf32>, %input_indices: tensor<3x10xi32>, %out_values : tensor<2x3xf32>, %out_indices: tensor<2x3xi32>) -> (tensor<2x3xf32>, tensor<2x3xi32>) { |
| // expected-error@+1 {{incompatible input/output shapes}} |
| %0:2 = iree_linalg_ext.topk |
| dimension(1) |
| ins(%input_values, %input_indices : tensor<3x10xf32> , tensor<3x10xi32>) |
| outs(%out_values, %out_indices : tensor<2x3xf32>, tensor<2x3xi32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %0 = arith.cmpf ogt, %arg0, %arg1 : f32 |
| iree_linalg_ext.yield %0 : i1 |
| } -> tensor<2x3xf32>, tensor<2x3xi32> |
| return %0#0, %0#1 : tensor<2x3xf32>, tensor<2x3xi32> |
| } |
| |
| // ----- |
| |
| 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 = iree_linalg_ext.pack %input inner_dims_pos = [1, 0] inner_tiles = [16, 32] into %output : (tensor<256x128xf32> tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> |
| return %0 : tensor<8x8x32x16xf32> |
| } |
| |
| // ----- |
| |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x16x33xf32>) -> tensor<8x8x16x33xf32> { |
| // expected-error@+1 {{invalid tile factor provided. Only full tiles are supported when padding_value is not set}} |
| %0 = iree_linalg_ext.pack %input inner_dims_pos = [1, 0] inner_tiles = [16, 33] into %output : (tensor<256x128xf32> tensor<8x8x16x33xf32>) -> tensor<8x8x16x33xf32> |
| return %0 : tensor<8x8x16x33xf32> |
| } |
| |
| // ----- |
| |
| func.func @pad_and_pack_invalid_type(%input: tensor<13x15xf32>, %output: tensor<2x8x8x2xf32>, %pad: i32) -> tensor<2x8x8x2xf32> { |
| // expected-error@+1 {{expected padding_value has 'f32' but got: 'i32'}} |
| %0 = iree_linalg_ext.pack %input padding_value(%pad: i32) inner_dims_pos = [0, 1] inner_tiles = [8, 2] into %output : (tensor<13x15xf32> tensor<2x8x8x2xf32>) -> tensor<2x8x8x2xf32> |
| return %0 : tensor<2x8x8x2xf32> |
| } |
| |
| // ----- |
| |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> { |
| // expected-error@+1 {{invalid inner_dims_pos vector}} |
| %0 = iree_linalg_ext.pack %input inner_dims_pos = [2, 0] inner_tiles = [2, 2] into %output : (tensor<256x128xf32> tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> |
| return %0 : tensor<8x8x32x16xf32> |
| } |
| |
| // ----- |
| |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> { |
| // expected-error@+1 {{invalid tile factor}} |
| %0 = iree_linalg_ext.pack %input inner_dims_pos = [1, 0] inner_tiles = [0, 2] into %output : (tensor<256x128xf32> tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> |
| return %0 : tensor<8x8x32x16xf32> |
| } |
| |
| // ----- |
| |
| // duplicate element in `inner_dims_pos`, fail. |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> { |
| // expected-error@+1 {{invalid inner_dims_pos vector}} |
| %0 = iree_linalg_ext.pack %input inner_dims_pos = [1, 1] inner_tiles = [2, 2] into %output : (tensor<256x128xf32> tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> |
| return %0 : tensor<8x8x32x16xf32> |
| } |
| |
| // ----- |
| |
| func.func @unpack_invalid(%output: tensor<256x128xf32>, %input: tensor<8x8x32x16xf32>) -> tensor<256x128xf32> { |
| // expected-error@+1 {{the shape of output is not large enough to hold the packed data. Expected at least 'tensor<8x32x4x32xf32>', got 'tensor<8x8x32x16xf32>'}} |
| %0 = iree_linalg_ext.unpack %input inner_dims_pos = [1, 0] inner_tiles = [4, 32] into %output : (tensor<8x8x32x16xf32> tensor<256x128xf32>) -> tensor<256x128xf32> |
| return %0 : tensor<256x128xf32> |
| } |
| |
| // ----- |
| |
| // duplicate element in `outer_dims_perm`, fail. |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> { |
| // expected-error@+1 {{invalid outer_dims_perm vector}} |
| %0 = iree_linalg_ext.pack %input outer_dims_perm = [1, 1] inner_dims_pos = [0, 1] inner_tiles = [2, 2] into %output : (tensor<256x128xf32> tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> |
| return %0 : tensor<8x8x32x16xf32> |
| } |
| |
| // ----- |
| |
| // duplicate element in `outer_dims_perm`, fail. |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> { |
| // expected-error@+1 {{invalid outer_dims_perm vector}} |
| %0 = iree_linalg_ext.unpack %output outer_dims_perm = [1, 1] inner_dims_pos = [0, 1] inner_tiles = [2, 2] into %input : (tensor<8x8x32x16xf32> tensor<256x128xf32>) -> tensor<256x128xf32> |
| return %0 : tensor<256x128xf32> |
| } |
| |
| // ----- |
| |
| // `outer_dims_perm` is out of bound. |
| func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> { |
| // expected-error@+1 {{invalid outer_dims_perm vector}} |
| %0 = iree_linalg_ext.unpack %output outer_dims_perm = [2, 1] inner_dims_pos = [0, 1] inner_tiles = [2, 2] into %input : (tensor<8x8x32x16xf32> tensor<256x128xf32>) -> tensor<256x128xf32> |
| return %0 : tensor<256x128xf32> |
| } |
| |
| // ----- |
| func.func @pack_mismatch_inner_tile_size_and_output_shape( |
| %input : tensor<?x?xf32>, %output : tensor<?x?x8x8xf32>) -> tensor<?x?x8x8xf32> { |
| // expected-error@+1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}} |
| %0 = iree_linalg_ext.pack %input inner_dims_pos = [0, 1] inner_tiles = [8, 4] into %output |
| : (tensor<?x?xf32> tensor<?x?x8x8xf32>) -> tensor<?x?x8x8xf32> |
| return %0 : tensor<?x?x8x8xf32> |
| } |
| |
| // ----- |
| |
| func.func @unpack_mismatch_inner_tile_size_and_output_shape( |
| %input : tensor<?x?x8x8xf32>, %output : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error@+1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}} |
| %0 = iree_linalg_ext.unpack %input inner_dims_pos = [0, 1] inner_tiles = [8, 4] into %output |
| : (tensor<?x?x8x8xf32> tensor<?x?xf32>) -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_set_encoding_op_with_no_result_encoding(%arg0 : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{result of set_encoding op expected to have a valid tensor encoding}} |
| %0 = iree_linalg_ext.set_encoding %arg0: tensor<?x?xf32> -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_set_encoding_op_with_source_encoding(%arg0 : tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{source of set_encoding op cannot have a tensor encoding}} |
| %0 = iree_linalg_ext.set_encoding %arg0: tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_set_encoding_op_with_unknown_encoding(%arg0 : tensor<?x?xf32>) -> tensor<?x?xf32, "gemm_lhs"> { |
| // expected-error @+1 {{result of set_encoding op expected to have a valid tensor encoding}} |
| %0 = iree_linalg_ext.set_encoding %arg0: tensor<?x?xf32> -> tensor<?x?xf32, "gemm_lhs"> |
| return %0 : tensor<?x?xf32, "gemm_lhs"> |
| } |
| |
| // ----- |
| |
| func.func @illegal_set_encoding_op_with_rank_change(%arg0 : tensor<?x?xf32>) -> tensor<?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> { |
| // expected-error @+1 {{cannot change the rank of the tensor}} |
| %0 = iree_linalg_ext.set_encoding %arg0: tensor<?x?xf32> -> tensor<?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> |
| return %0 : tensor<?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> |
| } |
| |
| // ----- |
| |
| func.func @illegal_set_encoding_op_with_shape_change(%arg0 : tensor<10x20xf32>) -> tensor<20x30xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> { |
| // expected-error @+1 {{expected to preserve the logical shape of the tensor}} |
| %0 = iree_linalg_ext.set_encoding %arg0: tensor<10x20xf32> -> tensor<20x30xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> |
| return %0 : tensor<20x30xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> |
| } |
| |
| // ----- |
| |
| func.func @illegal_unset_encoding_op_with_no_source_encoding(%arg0 : tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // expected-error @+1 {{source of unset_encoding op expected to have a valid tensor encoding}} |
| %0 = iree_linalg_ext.unset_encoding %arg0: tensor<?x?xf32> -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_unset_encoding_op_with_result_encoding(%arg0 : tensor<?x?xf32>) -> tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> { |
| // expected-error @+1 {{result of unset_encoding op cannot have a tensor encoding}} |
| %0 = iree_linalg_ext.unset_encoding %arg0: tensor<?x?xf32> -> tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> |
| return %0 : tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> |
| } |
| |
| // ----- |
| |
| func.func @illegal_unset_encoding_op_with_unknown_encoding(%arg0 : tensor<?x?xf32, "gemm_lhs">) -> tensor<?x?xf32> { |
| // expected-error @+1 {{source of unset_encoding op expected to have a valid tensor encoding}} |
| %0 = iree_linalg_ext.unset_encoding %arg0: tensor<?x?xf32, "gemm_lhs"> -> tensor<?x?xf32> |
| return %0 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_unset_encoding_op_with_rank_change(%arg0 : tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>>) -> tensor<?xf32> { |
| // expected-error @+1 {{cannot change the rank of the tensor}} |
| %0 = iree_linalg_ext.unset_encoding %arg0: tensor<?x?xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> -> tensor<?xf32> |
| return %0 : tensor<?xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_unset_encoding_op_with_shape_change(%arg0 : tensor<20x30xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>>) -> tensor<10x20xf32> { |
| // expected-error @+1 {{expected to preserve the logical shape of the tensor}} |
| %0 = iree_linalg_ext.unset_encoding %arg0: tensor<20x30xf32, #iree_linalg_ext.encoding<user = MATMUL_F32F32F32, role = LHS>> -> tensor<10x20xf32> |
| return %0 : tensor<10x20xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_winograd_input_shape(%arg0: tensor<1x10x10x32xf32>) -> tensor<8x8x1x6x6x32xf32> { |
| %0 = tensor.empty() : tensor<8x8x1x6x6x32xf32> |
| // expected-error @+1 {{incompatible output shape}} |
| %1 = iree_linalg_ext.winograd.input_transform output_tile_size(6) kernel_size(3) image_dimensions([1, 2]) |
| ins(%arg0 : tensor<1x10x10x32xf32>) outs(%0 : tensor<8x8x1x6x6x32xf32>) -> tensor<8x8x1x6x6x32xf32> |
| return %1 : tensor<8x8x1x6x6x32xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_winograd_input_rank(%arg0: tensor<1x10x10x32xf32>) -> tensor<8x8x1x6xf32> { |
| %0 = tensor.empty() : tensor<8x8x1x6xf32> |
| // expected-error @+1 {{expected output rank to be equal to input rank + 2}} |
| %1 = iree_linalg_ext.winograd.input_transform output_tile_size(6) kernel_size(3) image_dimensions([1, 2]) |
| ins(%arg0 : tensor<1x10x10x32xf32>) outs(%0 : tensor<8x8x1x6xf32>) -> tensor<8x8x1x6xf32> |
| return %1 : tensor<8x8x1x6xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_winograd_output_shape(%arg0: tensor<8x8x1x2x2x32xf32>) -> tensor<1x8x8x32xf32> { |
| %0 = tensor.empty() : tensor<1x8x8x32xf32> |
| // expected-error @+1 {{incompatible output shape}} |
| %1 = iree_linalg_ext.winograd.output_transform output_tile_size(6) |
| kernel_size(3) image_dimensions([1, 2]) |
| ins(%arg0 : tensor<8x8x1x2x2x32xf32>) outs(%0 : tensor<1x8x8x32xf32>) -> tensor<1x8x8x32xf32> |
| return %1 : tensor<1x8x8x32xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_winograd_input_shape_nchw(%arg0: tensor<1x32x10x10xf32>) -> tensor<8x8x1x32x6x6xf32> { |
| %0 = tensor.empty() : tensor<8x8x1x32x6x6xf32> |
| // expected-error @+1 {{incompatible output shape}} |
| %1 = iree_linalg_ext.winograd.input_transform output_tile_size(6) kernel_size(3) image_dimensions([2, 3]) |
| ins(%arg0 : tensor<1x32x10x10xf32>) outs(%0 : tensor<8x8x1x32x6x6xf32>) -> tensor<8x8x1x32x6x6xf32> |
| return %1 : tensor<8x8x1x32x6x6xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_winograd_input_image_dimensions(%arg0: tensor<1x1280x10x10xf32>) -> tensor<8x8x1x2x2x1280xf32> { |
| %0 = tensor.empty() : tensor<8x8x1x2x2x1280xf32> |
| // expected-error @+1 {{expect image dimensions to be either [1, 2] or [2, 3]}} |
| %1 = iree_linalg_ext.winograd.input_transform output_tile_size(6) kernel_size(3) image_dimensions([0, 3]) |
| ins(%arg0 : tensor<1x1280x10x10xf32>) outs(%0 : tensor<8x8x1x2x2x1280xf32>) -> tensor<8x8x1x2x2x1280xf32> |
| return %1 : tensor<8x8x1x2x2x1280xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_winograd_output_image_dimensions(%arg0: tensor<8x8x1x2x2x32xf32>) -> tensor<1x32x12x12xf32> { |
| %0 = tensor.empty() : tensor<1x32x12x12xf32> |
| // expected-error @+1 {{expect image dimensions to be either [1, 2] or [2, 3]}} |
| %1 = iree_linalg_ext.winograd.output_transform output_tile_size(6) kernel_size(3) image_dimensions([0, 3]) |
| ins(%arg0 : tensor<8x8x1x2x2x32xf32>) outs(%0 : tensor<1x32x12x12xf32>) -> tensor<1x32x12x12xf32> |
| return %1 : tensor<1x32x12x12xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_softmax_output_shape(%arg0: tensor<2x16x32xf32>) -> tensor<2x16xf32> { |
| %0 = tensor.empty() : tensor<2x16xf32> |
| // expected-error @+1 {{incompatible output shape}} |
| %1 = iree_linalg_ext.softmax dimension(2) ins(%arg0 : tensor<2x16x32xf32>) outs(%0: tensor<2x16xf32>) -> tensor<2x16xf32> |
| return %1 : tensor<2x16xf32> |
| } |
| |
| // ----- |
| |
| func.func @illegal_attention_inputs(%query: tensor<6x12x20x8xf32>, %key: tensor<6x12x20x8xf32>, %value: tensor<6x12x20x8xf32>) { |
| %0 = tensor.empty() : tensor<6x12x20x8xf32> |
| // expected-error @+1 {{failed to verify that query has shaped type of rank 3}} |
| %1 = iree_linalg_ext.attention ins(%query, %key, %value : tensor<6x12x20x8xf32>, tensor<6x12x20x8xf32>, tensor<6x12x20x8xf32>) outs(%0 : tensor<6x12x20x8xf32>) -> tensor<6x12x20x8xf32> |
| return %1 : tensor<6x12x20x8xf32> |
| } |
| |
| // ----- |
