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[StableHLO][NFC] Add e2e scatter tests (iree-org#13781)
These are based on the equivalent IREE tests for MHLO. Issue: iree-org#12678
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,238 @@ | ||
| func.func @scatter_update_scalar_1D() { | ||
| %arg0 = util.unfoldable_constant dense<0> : tensor<8xi32> | ||
| %arg1 = util.unfoldable_constant dense<[[1], [3], [4], [7]]> : tensor<4x1xi32> | ||
| %arg2 = util.unfoldable_constant dense<[9, 10, 11, 12]> : tensor<4xi32> | ||
| %0 = "stablehlo.scatter"(%arg0, %arg1, %arg2) ( { | ||
| ^bb0(%arg3: tensor<i32>, %arg4: tensor<i32>): // no predecessors | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<8xi32>, tensor<4x1xi32>, tensor<4xi32>) -> tensor<8xi32> | ||
| check.expect_eq_const(%0, dense<[0, 9, 0, 10, 11, 0, 0, 12]> : tensor<8xi32>) : tensor<8xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_repeated_update_scalar_1D() { | ||
| %arg0 = util.unfoldable_constant dense<0> : tensor<8xi32> | ||
| %arg1 = util.unfoldable_constant dense<[[1], [1], [7], [7]]> : tensor<4x1xi32> | ||
| %arg2 = util.unfoldable_constant dense<[9, 10, 11, 12]> : tensor<4xi32> | ||
| %0 = "stablehlo.scatter"(%arg0, %arg1, %arg2) ( { | ||
| ^bb0(%arg3: tensor<i32>, %arg4: tensor<i32>): // no predecessors | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = false | ||
| } : (tensor<8xi32>, tensor<4x1xi32>, tensor<4xi32>) -> tensor<8xi32> | ||
| check.expect_eq_const(%0, dense<[0, 10, 0, 0, 0, 0, 0, 12]> : tensor<8xi32>) : tensor<8xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_update_scalar_2D() { | ||
| %arg0 = util.unfoldable_constant dense<0> : tensor<4x3xi32> | ||
| %arg1 = util.unfoldable_constant dense<[[0, 0], [1, 1], [2, 2]]> : tensor<3x2xi32> | ||
| %arg2 = util.unfoldable_constant dense<[1, 2, 3]> : tensor<3xi32> | ||
| %0 = "stablehlo.scatter"(%arg0, %arg1, %arg2) ( { | ||
| ^bb0(%arg3: tensor<i32>, %arg4: tensor<i32>): // no predecessors | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) {indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| inserted_window_dims = [0, 1], | ||
| scatter_dims_to_operand_dims = [0, 1], | ||
| index_vector_dim = 1 | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<4x3xi32>, tensor<3x2xi32>, tensor<3xi32>) -> tensor<4x3xi32> | ||
| check.expect_eq_const(%0, dense<[[1, 0, 0], | ||
| [0, 2, 0], | ||
| [0, 0, 3], | ||
| [0, 0, 0]]> : tensor<4x3xi32>) : tensor<4x3xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_update_slice_2D() { | ||
| %arg0 = util.unfoldable_constant dense<0> : tensor<6x3xi32> | ||
| %arg1 = util.unfoldable_constant dense<[[2], [4]]> : tensor<2x1xi32> | ||
| %arg2 = util.unfoldable_constant dense<[[1, 2, 3], | ||
| [4, 5, 6]]> : tensor<2x3xi32> | ||
| %0 = "stablehlo.scatter"(%arg0, %arg1, %arg2) ( { | ||
| ^bb0(%arg3: tensor<i32>, %arg4: tensor<i32>): // no predecessors | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| update_window_dims = [1], | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<6x3xi32>, tensor<2x1xi32>, tensor<2x3xi32>) -> tensor<6x3xi32> | ||
| check.expect_eq_const(%0, dense<[[0, 0, 0], | ||
| [0, 0, 0], | ||
| [1, 2, 3], | ||
| [0, 0, 0], | ||
| [4, 5, 6], | ||
| [0, 0, 0]]> : tensor<6x3xi32>) : tensor<6x3xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_update_slice_partial_2D() { | ||
| %arg0 = util.unfoldable_constant dense<0> : tensor<6x3xi32> | ||
| %arg1 = util.unfoldable_constant dense<[[2], [4]]> : tensor<2x1xi32> | ||
| %arg2 = util.unfoldable_constant dense<[[1, 2], | ||
| [4, 5]]> : tensor<2x2xi32> | ||
| %0 = "stablehlo.scatter"(%arg0, %arg1, %arg2) ( { | ||
| ^bb0(%arg3: tensor<i32>, %arg4: tensor<i32>): // no predecessors | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| update_window_dims = [1], | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<6x3xi32>, tensor<2x1xi32>, tensor<2x2xi32>) -> tensor<6x3xi32> | ||
| check.expect_eq_const(%0, dense<[[0, 0, 0], | ||
| [0, 0, 0], | ||
| [1, 2, 0], | ||
| [0, 0, 0], | ||
| [4, 5, 0], | ||
| [0, 0, 0]]> : tensor<6x3xi32>) : tensor<6x3xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_add_slice_2D() { | ||
| %arg0 = util.unfoldable_constant dense<1> : tensor<6x3xi32> | ||
| %arg1 = util.unfoldable_constant dense<[[2], [4]]> : tensor<2x1xi32> | ||
| %arg2 = util.unfoldable_constant dense<[[1, 2, 3], | ||
| [4, 5, 6]]> : tensor<2x3xi32> | ||
| %0 = "stablehlo.scatter"(%arg0, %arg1, %arg2) ( { | ||
| ^bb0(%arg3: tensor<i32>, %arg4: tensor<i32>): // no predecessors | ||
| %1 = stablehlo.add %arg3, %arg4 : tensor<i32> | ||
| "stablehlo.return"(%1) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| update_window_dims = [1], | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<6x3xi32>, tensor<2x1xi32>, tensor<2x3xi32>) -> tensor<6x3xi32> | ||
| check.expect_eq_const(%0, dense<[[1, 1, 1], | ||
| [1, 1, 1], | ||
| [2, 3, 4], | ||
| [1, 1, 1], | ||
| [5, 6, 7], | ||
| [1, 1, 1]]> : tensor<6x3xi32>) : tensor<6x3xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_1D_large() { | ||
| %original = util.unfoldable_constant dense<1> : tensor<1400xi32> | ||
| %update = util.unfoldable_constant dense<2> : tensor<1400xi32> | ||
| %init = tensor.empty() : tensor<1400xi32> | ||
| %indices = linalg.generic { | ||
| indexing_maps = [affine_map<(d0) -> (d0)>], | ||
| iterator_types = ["parallel"]} | ||
| outs(%init : tensor<1400xi32>) { | ||
| ^bb0(%arg0: i32): | ||
| %0 = linalg.index 0 : index | ||
| %1 = arith.index_cast %0 : index to i32 | ||
| linalg.yield %1 : i32 | ||
| } -> tensor<1400xi32> | ||
| %indices_reshaped = tensor.expand_shape %indices [[0, 1]] : | ||
| tensor<1400xi32> into tensor<1400x1xi32> | ||
| %result = "stablehlo.scatter"(%original, %indices_reshaped, %update)({ | ||
| ^bb0(%arg3 : tensor<i32>, %arg4 : tensor<i32>): | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<1400xi32>, tensor<1400x1xi32>, tensor<1400xi32>) -> tensor<1400xi32> | ||
| check.expect_eq_const(%result, dense<2> : tensor<1400xi32>) : tensor<1400xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_2D_large() { | ||
| %original = util.unfoldable_constant dense<1> : tensor<200x300xi32> | ||
| %update = util.unfoldable_constant dense<2> : tensor<200x300xi32> | ||
| %init = tensor.empty() : tensor<200xi32> | ||
| %indices = linalg.generic { | ||
| indexing_maps = [affine_map<(d0) -> (d0)>], | ||
| iterator_types = ["parallel"]} | ||
| outs(%init : tensor<200xi32>) { | ||
| ^bb0(%arg0: i32): | ||
| %0 = linalg.index 0 : index | ||
| %1 = arith.index_cast %0 : index to i32 | ||
| linalg.yield %1 : i32 | ||
| } -> tensor<200xi32> | ||
| %indices_reshaped = tensor.expand_shape %indices [[0, 1]] : | ||
| tensor<200xi32> into tensor<200x1xi32> | ||
| %result = "stablehlo.scatter"(%original, %indices_reshaped, %update)({ | ||
| ^bb0(%arg3 : tensor<i32>, %arg4 : tensor<i32>): | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| update_window_dims = [1], | ||
| inserted_window_dims = [0], | ||
| scatter_dims_to_operand_dims = [0], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<200x300xi32>, tensor<200x1xi32>, tensor<200x300xi32>) -> tensor<200x300xi32> | ||
| check.expect_eq_const(%result, dense<2> : tensor<200x300xi32>) : tensor<200x300xi32> | ||
| return | ||
| } | ||
|
|
||
| func.func @scatter_2D_large_permuted() { | ||
| %original = util.unfoldable_constant dense<1> : tensor<200x300xi32> | ||
| %update = util.unfoldable_constant dense<2> : tensor<300x200xi32> | ||
| %init = tensor.empty() : tensor<300xi32> | ||
| %indices = linalg.generic { | ||
| indexing_maps = [affine_map<(d0) -> (d0)>], | ||
| iterator_types = ["parallel"]} | ||
| outs(%init : tensor<300xi32>) { | ||
| ^bb0(%arg0: i32): | ||
| %0 = linalg.index 0 : index | ||
| %1 = arith.index_cast %0 : index to i32 | ||
| linalg.yield %1 : i32 | ||
| } -> tensor<300xi32> | ||
| %indices_reshaped = tensor.expand_shape %indices [[0, 1]] : | ||
| tensor<300xi32> into tensor<300x1xi32> | ||
| %result = "stablehlo.scatter"(%original, %indices_reshaped, %update)({ | ||
| ^bb0(%arg3 : tensor<i32>, %arg4 : tensor<i32>): | ||
| "stablehlo.return"(%arg4) : (tensor<i32>) -> () | ||
| }) { | ||
| indices_are_sorted = false, | ||
| scatter_dimension_numbers = #stablehlo.scatter< | ||
| update_window_dims = [1], | ||
| inserted_window_dims = [1], | ||
| scatter_dims_to_operand_dims = [1], | ||
| index_vector_dim = 1, | ||
| >, | ||
| unique_indices = true | ||
| } : (tensor<200x300xi32>, tensor<300x1xi32>, tensor<300x200xi32>) -> tensor<200x300xi32> | ||
| check.expect_eq_const(%result, dense<2> : tensor<200x300xi32>) : tensor<200x300xi32> | ||
| return | ||
| } |