| // RUN: mlir-opt %s | mlir-opt | FileCheck %s |
| // RUN: mlir-opt %s --mlir-print-op-generic | mlir-opt | FileCheck %s |
| |
| |
| // ----- |
| // CHECK-LABEL: argmax |
| func.func @test_argmax(%arg0: tensor<14x19xf32>) -> tensor<14xi32> { |
| %0 = "tosa.argmax"(%arg0) {axis = 1 : i64} : (tensor<14x19xf32>) -> tensor<14xi32> |
| return %0 : tensor<14xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: avg_pool2d_f32 |
| func.func @test_avg_pool2d_f32(%arg0: tensor<1x7x7x9xf32>) -> tensor<1x7x7x9xf32> { |
| %0 = "tosa.avg_pool2d"(%arg0) {kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x9xf32>) -> tensor<1x7x7x9xf32> |
| return %0 : tensor<1x7x7x9xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: avg_pool2d_i8 |
| func.func @test_avg_pool2d_i8(%arg0: tensor<1x7x7x9xi8>) -> tensor<1x7x7x9xi8> { |
| %0 = "tosa.avg_pool2d"(%arg0) {kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x9xi8>) -> tensor<1x7x7x9xi8> |
| return %0 : tensor<1x7x7x9xi8> |
| } |
| |
| // ----- |
| // CHECK-LABEL: avg_pool2d_i16 |
| func.func @test_avg_pool2d_i16(%arg0: tensor<1x7x7x9xi16>) -> tensor<1x7x7x9xi16> { |
| %0 = "tosa.avg_pool2d"(%arg0) {kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x9xi16>) -> tensor<1x7x7x9xi16> |
| return %0 : tensor<1x7x7x9xi16> |
| } |
| |
| // ----- |
| // CHECK-LABEL: avg_pool2d_q8 |
| func.func @test_avg_pool2d_q8(%arg0: tensor<1x7x7x9x!quant.uniform<i8:f32, 0.01>>) -> tensor<1x7x7x9x!quant.uniform<i8:f32, 0.01>> { |
| %0 = "tosa.avg_pool2d"(%arg0) {kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x9x!quant.uniform<i8:f32, 0.01>>) -> tensor<1x7x7x9x!quant.uniform<i8:f32, 0.01>> |
| return %0 : tensor<1x7x7x9x!quant.uniform<i8:f32, 0.01>> |
| } |
| |
| // ----- |
| // CHECK-LABEL: conv2d |
| func.func @test_conv2d(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<8x1x1x4xf32>, %arg2: tensor<8xf32>) -> tensor<1x4x4x8xf32> { |
| %0 = "tosa.conv2d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x4xf32>, tensor<8x1x1x4xf32>, tensor<8xf32>) -> tensor<1x4x4x8xf32> |
| return %0 : tensor<1x4x4x8xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: depthwise_conv2d |
| func.func @test_depthwise_conv2d(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<1x1x4x2xf32>, %arg2: tensor<8xf32>) -> tensor<1x4x4x8xf32> { |
| %2 = "tosa.depthwise_conv2d"(%arg0, %arg1, %arg2) {dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x4xf32>, tensor<1x1x4x2xf32>, tensor<8xf32>) -> tensor<1x4x4x8xf32> |
| return %2 : tensor<1x4x4x8xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: fully_connected |
| func.func @test_fully_connected(%arg0: tensor<14x19xf32>, %arg1: tensor<19x28xf32>, %arg2: tensor<28xf32>) -> tensor<14x28xf32> { |
| %0 = "tosa.fully_connected"(%arg0, %arg1, %arg2) : (tensor<14x19xf32>, tensor<19x28xf32>, tensor<28xf32>) -> tensor<14x28xf32> |
| return %0 : tensor<14x28xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: test_matmul |
| func.func @test_matmul(%arg0: tensor<1x14x19xf32>, %arg1: tensor<1x19x28xf32>) -> tensor<1x14x28xf32> { |
| %0 = "tosa.matmul"(%arg0, %arg1) : (tensor<1x14x19xf32>, tensor<1x19x28xf32>) -> tensor<1x14x28xf32> |
| return %0 : tensor<1x14x28xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: max_pool2d |
| func.func @test_max_pool2d(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32> { |
| %0 = "tosa.max_pool2d"(%arg0) {kernel = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32> |
| return %0 : tensor<1x32x32x8xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: rfft2d |
| func.func @test_rfft2d(%arg0: tensor<13x8x16xf32>) -> (tensor<13x8x9xf32>, tensor<13x8x9xf32>) { |
| %0, %1 = "tosa.rfft2d"(%arg0) {} : (tensor<13x8x16xf32>) -> (tensor<13x8x9xf32>, tensor<13x8x9xf32>) |
| return %0, %1 : tensor<13x8x9xf32>, tensor<13x8x9xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: transpose_conv2d |
| func.func @test_transpose_conv2d(%arg0: tensor<1x32x32x8xf32>, %arg1: tensor<16x1x1x8xf32>, %arg2: tensor<16xf32>) -> tensor<1x32x32x16xf32> { |
| %0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: 1, 32, 32, 16>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xf32>, tensor<16x1x1x8xf32>, tensor<16xf32>) -> tensor<1x32x32x16xf32> |
| return %0 : tensor<1x32x32x16xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: clamp |
| func.func @test_clamp(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.clamp"(%arg0) {min_fp = 0.0 : f32, max_fp = 1.0: f32, min_int = 0 : i64, max_int = 1 : i64} : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: sigmoid |
| func.func @test_sigmoid(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.sigmoid"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: tanh |
| func.func @test_tanh(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.tanh"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: add |
| func.func @test_add(%arg0: tensor<13x21x1xf32>, %arg1: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.add"(%arg0, %arg1) : (tensor<13x21x1xf32>, tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: arithmetic_right_shift |
| func.func @test_arithmetic_right_shift(%arg0: tensor<13x21x1xf32>, %arg1: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.arithmetic_right_shift"(%arg0, %arg1) { round = false } : (tensor<13x21x1xf32>, tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: bitwise_and |
| func.func @test_bitwise_and(%arg0: tensor<13x21x3xi32>, %arg1: tensor<13x21x1xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.bitwise_and"(%arg0, %arg1) : (tensor<13x21x3xi32>, tensor<13x21x1xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: bitwise_or |
| func.func @test_bitwise_or(%arg0: tensor<13x21x3xi32>, %arg1: tensor<13x1x3xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.bitwise_or"(%arg0, %arg1) : (tensor<13x21x3xi32>, tensor<13x1x3xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: bitwise_xor |
| func.func @test_bitwise_xor(%arg0: tensor<13x21x1xi32>, %arg1: tensor<13x21x3xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.bitwise_xor"(%arg0, %arg1) : (tensor<13x21x1xi32>, tensor<13x21x3xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: div |
| func.func @test_div(%arg0: tensor<13x21x1xi32>, %arg1: tensor<13x21x3xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.div"(%arg0, %arg1) : (tensor<13x21x1xi32>, tensor<13x21x3xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: logical_and |
| func.func @test_logical_and(%arg0: tensor<13x21x3xi1>, %arg1: tensor<13x21x1xi1>) -> tensor<13x21x3xi1> { |
| %0 = "tosa.logical_and"(%arg0, %arg1) : (tensor<13x21x3xi1>, tensor<13x21x1xi1>) -> tensor<13x21x3xi1> |
| return %0 : tensor<13x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: logical_left_shift |
| func.func @test_logical_left_shift(%arg0: tensor<13x21x3xi32>, %arg1: tensor<13x21x1xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.logical_left_shift"(%arg0, %arg1) : (tensor<13x21x3xi32>, tensor<13x21x1xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: logical_right_shift |
| func.func @test_logical_right_shift(%arg0: tensor<13x21x3xi32>, %arg1: tensor<13x21x1xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.logical_right_shift"(%arg0, %arg1) : (tensor<13x21x3xi32>, tensor<13x21x1xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: logical_or |
| func.func @test_logical_or(%arg0: tensor<13x1x3xi1>, %arg1: tensor<13x21x3xi1>) -> tensor<13x21x3xi1> { |
| %0 = "tosa.logical_or"(%arg0, %arg1) : (tensor<13x1x3xi1>, tensor<13x21x3xi1>) -> tensor<13x21x3xi1> |
| return %0 : tensor<13x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: logical_xor |
| func.func @test_logical_xor(%arg0: tensor<13x1x3xi1>, %arg1: tensor<13x21x3xi1>) -> tensor<13x21x3xi1> { |
| %0 = "tosa.logical_xor"(%arg0, %arg1) : (tensor<13x1x3xi1>, tensor<13x21x3xi1>) -> tensor<13x21x3xi1> |
| return %0 : tensor<13x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: maximum |
| func.func @test_max(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x21x1xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.maximum"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<13x21x1xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: minimum |
| func.func @test_min(%arg0: tensor<13x21x3xf32>, %arg1: tensor<1x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.minimum"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<1x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: mul |
| func.func @test_mul(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x1x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.mul"(%arg0, %arg1) { shift = 1 : i32 } : (tensor<13x21x3xf32>, tensor<13x1x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: pow |
| func.func @test_pow(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x21x1xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.pow"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<13x21x1xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: sub |
| func.func @test_sub(%arg0: tensor<1x21x3xf32>, %arg1: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.sub"(%arg0, %arg1) : (tensor<1x21x3xf32>, tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: table |
| func.func @main(%arg0: tensor<64xi32>, %arg1: tensor<513x!quant.uniform<i16:f32, 1.0:0>>) -> tensor<64x!quant.uniform<i16:f32, 1.0:0>> { |
| %0 = "tosa.table"(%arg0, %arg1) : (tensor<64xi32>, tensor<513x!quant.uniform<i16:f32, 1.0:0>>) -> tensor<64x!quant.uniform<i16:f32, 1.0:0>> |
| return %0 : tensor<64x!quant.uniform<i16:f32, 1.0:0>> |
| } |
| |
| // ----- |
| // CHECK-LABEL: abs |
| func.func @test_abs(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.abs"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: bitwise_not |
| func.func @test_bitwise_not(%arg0: tensor<13x21x1xi32>) -> tensor<13x21x1xi32> { |
| %0 = "tosa.bitwise_not"(%arg0) : (tensor<13x21x1xi32>) -> tensor<13x21x1xi32> |
| return %0 : tensor<13x21x1xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: ceil |
| func.func @test_ceil(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.ceil"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: clz |
| func.func @test_clz(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.clz"(%arg0) : (tensor<13x21x3xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: exp |
| func.func @test_exp(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.exp"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: floor |
| func.func @test_floor(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.floor"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: log |
| func.func @test_log(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.log"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: logical_not |
| func.func @test_logical_not(%arg0: tensor<1x21x3xi1>) -> tensor<1x21x3xi1> { |
| %0 = "tosa.logical_not"(%arg0) : (tensor<1x21x3xi1>) -> tensor<1x21x3xi1> |
| return %0 : tensor<1x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: negate |
| func.func @test_negate(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.negate"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reciprocal |
| func.func @test_reciprocal(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.reciprocal"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: rsqrt |
| func.func @test_rsqrt(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.rsqrt"(%arg0) : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: select |
| func.func @test_select(%arg0: tensor<1x1x1xi1>, %arg1: tensor<13x21x3xf32>, %arg2: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.select"(%arg0, %arg1, %arg2) : (tensor<1x1x1xi1>, tensor<13x21x3xf32>, tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| |
| // ----- |
| // CHECK-LABEL: equal |
| func.func @test_equal(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x1x3xf32>) -> tensor<13x21x3xi1> { |
| %0 = "tosa.equal"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<13x1x3xf32>) -> tensor<13x21x3xi1> |
| return %0 : tensor<13x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: greater |
| func.func @test_greater(%arg0: tensor<13x21x1xf32>, %arg1: tensor<13x21x3xf32>) -> tensor<13x21x3xi1> { |
| %0 = "tosa.greater"(%arg0, %arg1) : (tensor<13x21x1xf32>, tensor<13x21x3xf32>) -> tensor<13x21x3xi1> |
| return %0 : tensor<13x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: greater_equal |
| func.func @test_greater_equal(%arg0: tensor<13x1x3xf32>, %arg1: tensor<13x21x3xf32>) -> tensor<13x21x3xi1> { |
| %0 = "tosa.greater_equal"(%arg0, %arg1) : (tensor<13x1x3xf32>, tensor<13x21x3xf32>) -> tensor<13x21x3xi1> |
| return %0 : tensor<13x21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reduce_all |
| func.func @test_reduce_all(%arg0: tensor<13x21x3xi1>) -> tensor<21x3xi1> { |
| %0 = "tosa.reduce_all"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xi1>) -> tensor<1x21x3xi1> |
| %1 = "tosa.reshape"(%0) {new_shape = array<i64: 21, 3>} : (tensor<1x21x3xi1>) -> tensor<21x3xi1> |
| return %1 : tensor<21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reduce_any |
| func.func @test_reduce_any(%arg0: tensor<13x21x3xi1>) -> tensor<21x3xi1> { |
| %0 = "tosa.reduce_any"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xi1>) -> tensor<1x21x3xi1> |
| %1 = "tosa.reshape"(%0) {new_shape = array<i64: 21, 3>} : (tensor<1x21x3xi1>) -> tensor<21x3xi1> |
| return %1 : tensor<21x3xi1> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reduce_max |
| func.func @test_reduce_max(%arg0: tensor<13x21x3xf32>) -> tensor<21x3xf32> { |
| %0 = "tosa.reduce_max"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xf32>) -> tensor<1x21x3xf32> |
| %1 = "tosa.reshape"(%0) {new_shape = array<i64: 21, 3>} : (tensor<1x21x3xf32>) -> tensor<21x3xf32> |
| return %1 : tensor<21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reduce_min |
| func.func @test_reduce_min(%arg0: tensor<13x21x3xf32>) -> tensor<21x3xf32> { |
| %0 = "tosa.reduce_min"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xf32>) -> tensor<1x21x3xf32> |
| %1 = "tosa.reshape"(%0) {new_shape = array<i64: 21, 3>} : (tensor<1x21x3xf32>) -> tensor<21x3xf32> |
| return %1 : tensor<21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reduce_product |
| func.func @test_reduce_product(%arg0: tensor<13x21x3xf32>) -> tensor<21x3xf32> { |
| %0 = "tosa.reduce_prod"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xf32>) -> tensor<1x21x3xf32> |
| %1 = "tosa.reshape"(%0) {new_shape = array<i64: 21, 3>} : (tensor<1x21x3xf32>) -> tensor<21x3xf32> |
| return %1 : tensor<21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reduce_sum |
| func.func @test_reduce_sum(%arg0: tensor<13x21x3xf32>) -> tensor<21x3xf32> { |
| %0 = "tosa.reduce_sum"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xf32>) -> tensor<1x21x3xf32> |
| %1 = "tosa.reshape"(%0) {new_shape = array<i64: 21, 3>} : (tensor<1x21x3xf32>) -> tensor<21x3xf32> |
| return %1 : tensor<21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: concat |
| func.func @test_concat(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x21x3xf32>) -> tensor<26x21x3xf32> { |
| %0 = "tosa.concat"(%arg0, %arg1) {axis = 0 : i64} : (tensor<13x21x3xf32>, tensor<13x21x3xf32>) -> tensor<26x21x3xf32> |
| return %0 : tensor<26x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: pad |
| func.func @test_pad(%arg0: tensor<13x21x3xf32>, %arg1: tensor<3x2xi32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.pad"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<3x2xi32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: pad_explicit_value |
| func.func @test_pad_explicit_value(%arg0: tensor<13x21x3xf32>, %arg1: tensor<3x2xi32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.const"() {value = dense<3.14> : tensor<f32>} : () -> tensor<f32> |
| %1 = "tosa.pad"(%arg0, %arg1, %0) : (tensor<13x21x3xf32>, tensor<3x2xi32>, tensor<f32>) -> tensor<13x21x3xf32> |
| return %1 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reshape |
| func.func @test_reshape(%arg0: tensor<13x21x3xf32>) -> tensor<1x819xf32> { |
| %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 1, 819>} : (tensor<13x21x3xf32>) -> tensor<1x819xf32> |
| return %0 : tensor<1x819xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: reverse |
| func.func @test_reverse(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.reverse"(%arg0) {axis = 0 : i64} : (tensor<13x21x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: slice |
| func.func @test_slice(%arg0: tensor<13x21x3xf32>) -> tensor<4x11x1xf32> { |
| %0 = "tosa.slice"(%arg0) {start = array<i64: 6, 8, 0>, size = array<i64: 4, 11, 1>} : (tensor<13x21x3xf32>) -> tensor<4x11x1xf32> |
| return %0 : tensor<4x11x1xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: tile |
| func.func @test_tile(%arg0: tensor<13x21x3xf32>) -> tensor<39x21x6xf32> { |
| %0 = "tosa.tile"(%arg0) {multiples = array<i64: 3, 1, 2>} : (tensor<13x21x3xf32>) -> tensor<39x21x6xf32> |
| return %0 : tensor<39x21x6xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: transpose |
| func.func @test_transpose(%arg0: tensor<13x21x3xf32>) -> tensor<3x13x21xf32> { |
| %0 = "tosa.const"() {value = dense<[2, 0, 1]> : tensor<3xi32>} : () -> tensor<3xi32> |
| %1 = "tosa.transpose"(%arg0, %0) : (tensor<13x21x3xf32>, tensor<3xi32>) -> tensor<3x13x21xf32> |
| return %1 : tensor<3x13x21xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: gather |
| func.func @test_gather(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>) -> tensor<13x26x3xf32> { |
| %0 = "tosa.gather"(%arg0, %arg1) : (tensor<13x21x3xf32>, tensor<13x26xi32>) -> tensor<13x26x3xf32> |
| return %0 : tensor<13x26x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: scatter |
| func.func @test_scatter(%arg0: tensor<13x21x3xf32>, %arg1: tensor<13x26xi32>, %arg2: tensor<13x26x3xf32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.scatter"(%arg0, %arg1, %arg2) : (tensor<13x21x3xf32>, tensor<13x26xi32>, tensor<13x26x3xf32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: resize |
| func.func @test_resize(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x64x64x8xf32> { |
| %1 = "tosa.resize"(%arg0) { scale = array<i64: 4, 2, 4, 2>, offset = array<i64: -1, -1>, border = array<i64: 1, 1>, mode = "BILINEAR"} : (tensor<1x32x32x8xf32>) -> tensor<1x64x64x8xf32> |
| return %1 : tensor<1x64x64x8xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: cast |
| func.func @test_cast1(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3xf32> { |
| %0 = "tosa.cast"(%arg0) : (tensor<13x21x3xi32>) -> tensor<13x21x3xf32> |
| return %0 : tensor<13x21x3xf32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: cast2 |
| func.func @test_cast2(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3x!quant.uniform<u8:f32, 0.078431375324726104:128>> { |
| %0 = "tosa.cast"(%arg0) : (tensor<13x21x3xi32>) -> tensor<13x21x3x!quant.uniform<u8:f32, 0.078431375324726104:128>> |
| return %0 : tensor<13x21x3x!quant.uniform<u8:f32, 0.078431375324726104:128>> |
| } |
| |
| // ----- |
| // CHECK-LABEL: cast3 |
| func.func @test_cast3(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3x!quant.uniform<i16:f32, 0.078431375324726104:128>> { |
| %0 = "tosa.cast"(%arg0) : (tensor<13x21x3xi32>) -> tensor<13x21x3x!quant.uniform<i16:f32, 0.078431375324726104:128>> |
| return %0 : tensor<13x21x3x!quant.uniform<i16:f32, 0.078431375324726104:128>> |
| } |
| |
| // ----- |
| // CHECK-LABEL: rescale |
| func.func @test_rescale(%arg0: tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>> { |
| %0 = "tosa.rescale"(%arg0) {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i32: 30>} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>> |
| return %0 : tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>> |
| } |
| |
| // ----- |
| // CHECK-LABEL: const |
| func.func @test_const(%arg0 : index) -> tensor<4xi32> { |
| %0 = "tosa.const"() {value = dense<[3, 0, 1, 2]> : tensor<4xi32>} : () -> tensor<4xi32> |
| return %0 : tensor<4xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: identity |
| func.func @test_identity(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3xi32> { |
| %0 = "tosa.identity"(%arg0) : (tensor<13x21x3xi32>) -> tensor<13x21x3xi32> |
| return %0 : tensor<13x21x3xi32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: cond_if |
| func.func @test_cond_if(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<i1>) -> tensor<f32> { |
| %0 = "tosa.cond_if"(%arg2, %arg0, %arg1) ({ |
| ^bb0(%arg3: tensor<f32>, %arg4: tensor<f32>): |
| %1 = "tosa.add"(%arg3, %arg4) : (tensor<f32>, tensor<f32>) -> tensor<f32> |
| "tosa.yield"(%1) : (tensor<f32>) -> () |
| }, { |
| ^bb0(%arg3: tensor<f32>, %arg4: tensor<f32>): |
| %1 = "tosa.sub"(%arg3, %arg4) : (tensor<f32>, tensor<f32>) -> tensor<f32> |
| "tosa.yield"(%1) : (tensor<f32>) -> () |
| }) : (tensor<i1>, tensor<f32>, tensor<f32>) -> tensor<f32> |
| return %0 : tensor<f32> |
| } |
| |
| // ----- |
| // CHECK-LABEL: while_loop |
| func.func @test_while_loop(%arg0: tensor<10xi32>, %arg1: tensor<i32>) { |
| %0 = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32> |
| %1:3 = "tosa.while_loop"(%0, %0, %arg0) ({ |
| ^bb0(%arg2: tensor<i32>, %arg3: tensor<i32>, %arg4: tensor<10xi32>): |
| %2 = "tosa.greater_equal"(%arg3, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i1> |
| %3 = "tosa.logical_not"(%2) : (tensor<i1>) -> tensor<i1> |
| "tosa.yield"(%3) : (tensor<i1>) -> () |
| }, { |
| ^bb0(%arg2: tensor<i32>, %arg3: tensor<i32>, %arg4: tensor<10xi32>): |
| %2 = "tosa.const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32> |
| %3 = "tosa.add"(%arg3, %2) : (tensor<i32>, tensor<i32>) -> tensor<i32> |
| %4 = "tosa.reshape"(%2) {new_shape = array<i64: 1>} : (tensor<i32>) -> tensor<1xi32> |
| %5 = "tosa.add"(%arg4, %4) : (tensor<10xi32>, tensor<1xi32>) -> tensor<10xi32> |
| %6 = "tosa.add"(%arg2, %2) : (tensor<i32>, tensor<i32>) -> tensor<i32> |
| "tosa.yield"(%6, %3, %5) : (tensor<i32>, tensor<i32>, tensor<10xi32>) -> () |
| }) : (tensor<i32>, tensor<i32>, tensor<10xi32>) -> (tensor<i32>, tensor<i32>, tensor<10xi32>) |
| return |
| } |
| |
| // ----- |
| // CHECK-LABEL: custom |
| func.func @test_custom(%arg0: tensor<10xi32>) -> tensor<10xi32> { |
| %0 = "tosa.custom"(%arg0) {identifier="custom_test", config="tosa_mlir_test", implementation_attrs=""} : (tensor<10xi32>) -> (tensor<10xi32>) |
| return %0 : tensor<10xi32> |
| } |