derek.holloway
7502bf64a4
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443 lines
20 KiB
MLIR
443 lines
20 KiB
MLIR
// RUN: mlir-opt %s -split-input-file -verify-diagnostics -tosa-attach-target="specification_version=1.1.draft profiles=pro_int,pro_fp extensions=int16,int4,bf16,fp8e4m3,fp8e5m2,fft,variable,controlflow,doubleround,inexactround,mxfp,int64,mxfp_conv,shape" -tosa-validate="strict-op-spec-alignment" | FileCheck %s
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// -----
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// CHECK-LABEL: test_matmul_fp8_mixed_precision_operands
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func.func @test_matmul_fp8_mixed_precision_operands(%arg0: tensor<1x14x19xf8E4M3FN>, %arg1: tensor<1x19x28xf8E5M2>) -> tensor<1x14x28xf16> {
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%azp0 = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E4M3FN>}> : () -> tensor<1xf8E4M3FN>
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%bzp0 = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%0 = tosa.matmul %arg0, %arg1, %azp0, %bzp0 : (tensor<1x14x19xf8E4M3FN>, tensor<1x19x28xf8E5M2>, tensor<1xf8E4M3FN>, tensor<1xf8E5M2>) -> tensor<1x14x28xf16>
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return %0 : tensor<1x14x28xf16>
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}
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// -----
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// CHECK-LABEL: test_matmul_fp8_input_fp32_acc_type
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func.func @test_matmul_fp8_input_fp32_acc_type(%arg0: tensor<1x14x19xf8E4M3FN>, %arg1: tensor<1x19x28xf8E4M3FN>) -> tensor<1x14x28xf32> {
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%azp0 = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E4M3FN>}> : () -> tensor<1xf8E4M3FN>
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%bzp0 = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E4M3FN>}> : () -> tensor<1xf8E4M3FN>
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%0 = tosa.matmul %arg0, %arg1, %azp0, %bzp0 : (tensor<1x14x19xf8E4M3FN>, tensor<1x19x28xf8E4M3FN>, tensor<1xf8E4M3FN>, tensor<1xf8E4M3FN>) -> tensor<1x14x28xf32>
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return %0 : tensor<1x14x28xf32>
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}
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// -----
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// CHECK-LABEL: test_conv2d_fp8_acc32
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func.func @test_conv2d_fp8_acc32(%arg0: tensor<1x4x4x4xf8E5M2>, %arg1: tensor<8x1x1x4xf8E5M2>, %arg2: tensor<8xf32>) -> tensor<1x4x4x8xf32> {
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%input_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%weight_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%0 = tosa.conv2d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x4xf8E5M2>, tensor<8x1x1x4xf8E5M2>, tensor<8xf32>, tensor<1xf8E5M2>, tensor<1xf8E5M2>) -> tensor<1x4x4x8xf32>
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return %0 : tensor<1x4x4x8xf32>
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}
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// -----
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// CHECK-LABEL: test_conv3d_fp8_acc32
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func.func @test_conv3d_fp8_acc32(%arg0: tensor<1x4x8x21x17xf8E5M2>, %arg1: tensor<34x1x1x1x17xf8E5M2>, %arg2: tensor<34xf32>) -> tensor<1x4x8x21x34xf32> {
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%input_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%weight_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%0 = tosa.conv3d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1, 1>, pad = array<i64: 0, 0, 0, 0, 0, 0>, stride = array<i64: 1, 1, 1>} : (tensor<1x4x8x21x17xf8E5M2>, tensor<34x1x1x1x17xf8E5M2>, tensor<34xf32>, tensor<1xf8E5M2>, tensor<1xf8E5M2>) -> tensor<1x4x8x21x34xf32>
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return %0 : tensor<1x4x8x21x34xf32>
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}
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// -----
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// CHECK-LABEL: test_depthwise_conv2d_fp8_acc32
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func.func @test_depthwise_conv2d_fp8_acc32(%arg0: tensor<1x4x4x4xf8E5M2>, %arg1: tensor<1x1x4x2xf8E5M2>, %arg2: tensor<8xf32>) -> tensor<1x4x4x8xf32> {
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%input_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%weight_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%0 = tosa.depthwise_conv2d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = f32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x4x4x4xf8E5M2>, tensor<1x1x4x2xf8E5M2>, tensor<8xf32>, tensor<1xf8E5M2>, tensor<1xf8E5M2>) -> tensor<1x4x4x8xf32>
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return %0 : tensor<1x4x4x8xf32>
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}
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// -----
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// CHECK-LABEL: test_transpose_conv2d_fp8_acc32
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func.func @test_transpose_conv2d_fp8_acc32(%arg0: tensor<1x32x32x8xf8E5M2>, %arg1: tensor<16x1x1x8xf8E5M2>, %arg2: tensor<16xf32>) -> tensor<1x32x32x16xf32> {
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%input_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%weight_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf8E5M2>}> : () -> tensor<1xf8E5M2>
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%0 = tosa.transpose_conv2d %arg0, %arg1, %arg2, %input_zp, %weight_zp {acc_type = f32, out_pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xf8E5M2>, tensor<16x1x1x8xf8E5M2>, tensor<16xf32>, tensor<1xf8E5M2>, tensor<1xf8E5M2>) -> tensor<1x32x32x16xf32>
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return %0 : tensor<1x32x32x16xf32>
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}
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// -----
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// CHECK-LABEL: test_matmul_t_block_scaled_fp6e2m3
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func.func @test_matmul_t_block_scaled_fp6e2m3(%arg0: tensor<4x8x32xf6E2M3FN>, %arg1: tensor<4x8x1xf8E8M0FNU>, %arg2: tensor<4x16x32xf6E2M3FN>, %arg3: tensor<4x16x1xf8E8M0FNU>) -> tensor<4x8x16xf32> {
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%0 = tosa.matmul_t_block_scaled %arg0, %arg1, %arg2, %arg3 {block_size = BLOCK_SIZE_32} : (tensor<4x8x32xf6E2M3FN>, tensor<4x8x1xf8E8M0FNU>, tensor<4x16x32xf6E2M3FN>, tensor<4x16x1xf8E8M0FNU>) -> tensor<4x8x16xf32>
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return %0 : tensor<4x8x16xf32>
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}
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// -----
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// CHECK-LABEL: test_argmax_int64
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func.func @test_argmax_int64(%arg0: tensor<1x13x13x5xf32>) -> tensor<1x13x13xi64> {
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%0 = tosa.argmax %arg0 {axis = 3 : i32} : (tensor<1x13x13x5xf32>) -> tensor<1x13x13xi64>
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return %0 : tensor<1x13x13xi64>
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}
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// -----
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// CHECK-LABEL: test_const_i64
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func.func @test_const_i64() -> tensor<4xi64> {
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%0 = "tosa.const"() {values = dense<[3, 0, 1, 2]> : tensor<4xi64>} : () -> tensor<4xi64>
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return %0 : tensor<4xi64>
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}
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// -----
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// CHECK-LABEL: test_const_fp6e3m2
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func.func @test_const_fp6e3m2() -> tensor<4xf6E3M2FN> {
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%0 = "tosa.const"() {values = dense<[0.0, 0.0, 0.0, 0.0]> : tensor<4xf6E3M2FN>} : () -> tensor<4xf6E3M2FN>
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return %0 : tensor<4xf6E3M2FN>
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}
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// -----
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// CHECK-LABEL: test_cast_from_block_scaled_fp8e5m2_fp32
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func.func @test_cast_from_block_scaled_fp8e5m2_fp32(%arg0: tensor<4x32xf8E5M2>, %arg1: tensor<4x1xf8E8M0FNU>) -> tensor<4x32xf32> {
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%0 = tosa.cast_from_block_scaled %arg0, %arg1 {block_size = #tosa.block_size<BLOCK_SIZE_32> : i32} : (tensor<4x32xf8E5M2>, tensor<4x1xf8E8M0FNU>) -> tensor<4x32xf32>
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return %0 : tensor<4x32xf32>
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}
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// -----
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// CHECK-LABEL: test_cast_from_block_scaled_fp8e5m2_bf16
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func.func @test_cast_from_block_scaled_fp8e5m2_bf16(%arg0: tensor<4x32xf8E5M2>, %arg1: tensor<4x1xf8E8M0FNU>) -> tensor<4x32xbf16> {
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%0 = tosa.cast_from_block_scaled %arg0, %arg1 {block_size = #tosa.block_size<BLOCK_SIZE_32> : i32} : (tensor<4x32xf8E5M2>, tensor<4x1xf8E8M0FNU>) -> tensor<4x32xbf16>
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return %0 : tensor<4x32xbf16>
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}
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// -----
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// CHECK-LABEL: test_cast_to_block_scaled_static
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func.func @test_cast_to_block_scaled_static(%arg0: tensor<4x32xf32>) -> (tensor<4x32xf6E3M2FN>, tensor<4x1xf8E8M0FNU>) {
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%0:2 = tosa.cast_to_block_scaled %arg0 {block_size = #tosa.block_size<BLOCK_SIZE_32>} : (tensor<4x32xf32>) -> (tensor<4x32xf6E3M2FN>, tensor<4x1xf8E8M0FNU>)
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return %0#0, %0#1 : tensor<4x32xf6E3M2FN>, tensor<4x1xf8E8M0FNU>
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}
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// -----
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// CHECK-LABEL: test_cast_to_block_scaled_mxint8
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func.func @test_cast_to_block_scaled_mxint8(%arg0: tensor<4x32xf32>) -> (tensor<4x32x!tosa.mxint8>, tensor<4x1xf8E8M0FNU>) {
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%0:2 = tosa.cast_to_block_scaled %arg0 {block_size = #tosa.block_size<BLOCK_SIZE_32> : i32, stochastic_round = false} : (tensor<4x32xf32>) -> (tensor<4x32x!tosa.mxint8>, tensor<4x1xf8E8M0FNU>)
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return %0#0, %0#1 : tensor<4x32x!tosa.mxint8>, tensor<4x1xf8E8M0FNU>
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}
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// -----
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// CHECK-LABEL: test_const_fp6e3m2
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func.func @test_const_fp6e3m2() -> tensor<4xf6E3M2FN> {
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%0 = "tosa.const"() {values = dense<[0.0, 0.0, 0.0, 0.0]> : tensor<4xf6E3M2FN>} : () -> tensor<4xf6E3M2FN>
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return %0 : tensor<4xf6E3M2FN>
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}
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// -----
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// CHECK-LABEL: test_const_mxint8
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func.func @test_const_mxint8() -> tensor<2x!tosa.mxint8> {
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%0 = "tosa.const"() {values = dense<["0x00", "0x7F"]> : tensor<2x!tosa.mxint8>} : () -> tensor<2x!tosa.mxint8>
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return %0 : tensor<2x!tosa.mxint8>
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}
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// -----
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// CHECK-LABEL: test_matmul_t_block_scaled_mxint8
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func.func @test_matmul_t_block_scaled_mxint8(%arg0: tensor<4x8x32x!tosa.mxint8>, %arg1: tensor<4x8x1xf8E8M0FNU>, %arg2: tensor<4x16x32x!tosa.mxint8>, %arg3: tensor<4x16x1xf8E8M0FNU>) -> tensor<4x8x16xf32> {
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%0 = tosa.matmul_t_block_scaled %arg0, %arg1, %arg2, %arg3 {block_size = #tosa.block_size<BLOCK_SIZE_32>} : (tensor<4x8x32x!tosa.mxint8>, tensor<4x8x1xf8E8M0FNU>, tensor<4x16x32x!tosa.mxint8>, tensor<4x16x1xf8E8M0FNU>) -> tensor<4x8x16xf32>
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return %0 : tensor<4x8x16xf32>
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}
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// -----
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// CHECK-LABEL: test_cast_to_block_scaled_mxint8
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func.func @test_cast_to_block_scaled_mxint8(%arg0: tensor<4x32xf32>) -> (tensor<4x32x!tosa.mxint8>, tensor<4x1xf8E8M0FNU>) {
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%0:2 = tosa.cast_to_block_scaled %arg0 {block_size = #tosa.block_size<BLOCK_SIZE_32> : i32, stochastic_round = false} : (tensor<4x32xf32>) -> (tensor<4x32x!tosa.mxint8>, tensor<4x1xf8E8M0FNU>)
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return %0#0, %0#1 : tensor<4x32x!tosa.mxint8>, tensor<4x1xf8E8M0FNU>
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}
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// -----
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// CHECK-LABEL: test_argmax_fp8_i64
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func.func @test_argmax_fp8_i64(%arg0: tensor<12x8x16xf8E5M2>) -> tensor<12x16xi64> {
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%0 = tosa.argmax %arg0 { axis = 1 : i32 } : (tensor<12x8x16xf8E5M2>) -> tensor<12x16xi64>
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return %0 : tensor<12x16xi64>
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}
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// -----
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// CHECK-LABEL: test_argmax_bf16_i64
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func.func @test_argmax_bf16_i64(%arg0: tensor<12x8x16xbf16>) -> tensor<12x16xi64> {
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%0 = tosa.argmax %arg0 { axis = 1 : i32 } : (tensor<12x8x16xbf16>) -> tensor<12x16xi64>
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return %0 : tensor<12x16xi64>
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}
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// -----
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// CHECK-LABEL: test_scatter_const_indices_int64
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func.func @test_scatter_const_indices_int64(%arg0: tensor<2x52x3xf32>, %arg2: tensor<2x12x3xf32>) -> tensor<2x52x3xf32> {
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%indices = "tosa.const"() { values = dense<[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]> : tensor<2x12xi64> } : () -> tensor<2x12xi64>
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%0 = tosa.scatter %arg0, %indices, %arg2 : (tensor<2x52x3xf32>, tensor<2x12xi64>, tensor<2x12x3xf32>) -> tensor<2x52x3xf32>
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return %0 : tensor<2x52x3xf32>
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}
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// -----
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// CHECK-LABEL: test_gather_bool_i64
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func.func @test_gather_bool_i64(%arg0: tensor<13x21x3xi1>, %arg1: tensor<13x26xi64>) -> tensor<13x26x3xi1> {
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%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi1>, tensor<13x26xi64>) -> tensor<13x26x3xi1>
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return %0 : tensor<13x26x3xi1>
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}
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// -----
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// CHECK-LABEL: test_gather_bool_i32
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func.func @test_gather_bool_i32(%arg0: tensor<13x21x3xi1>, %arg1: tensor<13x26xi32>) -> tensor<13x26x3xi1> {
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%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi1>, tensor<13x26xi32>) -> tensor<13x26x3xi1>
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return %0 : tensor<13x26x3xi1>
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}
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// -----
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// CHECK-LABEL: test_scatter_bool_i64
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func.func @test_scatter_bool_i64(%arg0: tensor<13x52x3xi1>, %arg1: tensor<13x26xi64>, %arg2: tensor<13x26x3xi1>) -> tensor<13x52x3xi1> {
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%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x52x3xi1>, tensor<13x26xi64>, tensor<13x26x3xi1>) -> tensor<13x52x3xi1>
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return %0 : tensor<13x52x3xi1>
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}
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// -----
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// CHECK-LABEL: test_scatter_bool_i32
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func.func @test_scatter_bool_i32(%arg0: tensor<13x52x3xi1>, %arg1: tensor<13x26xi32>, %arg2: tensor<13x26x3xi1>) -> tensor<13x52x3xi1> {
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%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x52x3xi1>, tensor<13x26xi32>, tensor<13x26x3xi1>) -> tensor<13x52x3xi1>
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return %0 : tensor<13x52x3xi1>
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}
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// -----
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// CHECK-LABEL: test_gather_i8_i32_indices
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func.func @test_gather_i8_i32_indices(%arg0: tensor<13x21x3xi8>, %arg1: tensor<13x26xi32>) -> tensor<13x26x3xi8> {
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%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi8>, tensor<13x26xi32>) -> tensor<13x26x3xi8>
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return %0 : tensor<13x26x3xi8>
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}
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// -----
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// CHECK-LABEL: test_row_gather_block_scaled_i8_i32_indices
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func.func @test_row_gather_block_scaled_i8_i32_indices(%arg0: tensor<13x21x3xi8>, %arg1: tensor<13x26xi32>) -> tensor<13x52x3xi8> {
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%row_count = "tosa.const"() {values = dense<2> : tensor<1xi32>} : () -> tensor<1xi32>
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%0 = tosa.row_gather_block_scaled %arg0, %arg1, %row_count {block_size = #tosa.block_size<BLOCK_SIZE_1>} : (tensor<13x21x3xi8>, tensor<13x26xi32>, tensor<1xi32>) -> (tensor<13x52x3xi8>)
|
|
return %0 : tensor<13x52x3xi8>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_scatter_i8_i32_indices
|
|
func.func @test_scatter_i8_i32_indices(%arg0: tensor<13x27x3xi8>, %arg1: tensor<13x26xi32>, %arg2: tensor<13x26x3xi8>) -> tensor<13x27x3xi8> {
|
|
%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x27x3xi8>, tensor<13x26xi32>, tensor<13x26x3xi8>) -> tensor<13x27x3xi8>
|
|
return %0 : tensor<13x27x3xi8>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_gather_i16_i32_indices
|
|
func.func @test_gather_i16_i32_indices(%arg0: tensor<13x21x3xi16>, %arg1: tensor<13x26xi32>) -> tensor<13x26x3xi16> {
|
|
%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi16>, tensor<13x26xi32>) -> tensor<13x26x3xi16>
|
|
return %0 : tensor<13x26x3xi16>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_scatter_i16_i32_indices
|
|
func.func @test_scatter_i16_i32_indices(%arg0: tensor<13x27x3xi16>, %arg1: tensor<13x26xi32>, %arg2: tensor<13x26x3xi16>) -> tensor<13x27x3xi16> {
|
|
%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x27x3xi16>, tensor<13x26xi32>, tensor<13x26x3xi16>) -> tensor<13x27x3xi16>
|
|
return %0 : tensor<13x27x3xi16>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_gather_i32_i32_indices
|
|
func.func @test_gather_i32_i32_indices(%arg0: tensor<13x21x3xi32>, %arg1: tensor<13x26xi32>) -> tensor<13x26x3xi32> {
|
|
%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi32>, tensor<13x26xi32>) -> tensor<13x26x3xi32>
|
|
return %0 : tensor<13x26x3xi32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_scatter_i32_i32_indices
|
|
func.func @test_scatter_i32_i32_indices(%arg0: tensor<13x27x3xi32>, %arg1: tensor<13x26xi32>, %arg2: tensor<13x26x3xi32>) -> tensor<13x27x3xi32> {
|
|
%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x27x3xi32>, tensor<13x26xi32>, tensor<13x26x3xi32>) -> tensor<13x27x3xi32>
|
|
return %0 : tensor<13x27x3xi32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_gather_i8_i64_indices
|
|
func.func @test_gather_i8_i64_indices(%arg0: tensor<13x21x3xi8>, %arg1: tensor<13x26xi64>) -> tensor<13x26x3xi8> {
|
|
%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi8>, tensor<13x26xi64>) -> tensor<13x26x3xi8>
|
|
return %0 : tensor<13x26x3xi8>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_scatter_i8_i64_indices
|
|
func.func @test_scatter_i8_i64_indices(%arg0: tensor<13x27x3xi8>, %arg1: tensor<13x26xi64>, %arg2: tensor<13x26x3xi8>) -> tensor<13x27x3xi8> {
|
|
%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x27x3xi8>, tensor<13x26xi64>, tensor<13x26x3xi8>) -> tensor<13x27x3xi8>
|
|
return %0 : tensor<13x27x3xi8>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_gather_i16_i64_indices
|
|
func.func @test_gather_i16_i64_indices(%arg0: tensor<13x21x3xi16>, %arg1: tensor<13x26xi64>) -> tensor<13x26x3xi16> {
|
|
%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi16>, tensor<13x26xi64>) -> tensor<13x26x3xi16>
|
|
return %0 : tensor<13x26x3xi16>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_scatter_i16_i64_indices
|
|
func.func @test_scatter_i16_i64_indices(%arg0: tensor<13x27x3xi16>, %arg1: tensor<13x26xi64>, %arg2: tensor<13x26x3xi16>) -> tensor<13x27x3xi16> {
|
|
%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x27x3xi16>, tensor<13x26xi64>, tensor<13x26x3xi16>) -> tensor<13x27x3xi16>
|
|
return %0 : tensor<13x27x3xi16>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_gather_i32_i64_indices
|
|
func.func @test_gather_i32_i64_indices(%arg0: tensor<13x21x3xi32>, %arg1: tensor<13x26xi64>) -> tensor<13x26x3xi32> {
|
|
%0 = tosa.gather %arg0, %arg1 : (tensor<13x21x3xi32>, tensor<13x26xi64>) -> tensor<13x26x3xi32>
|
|
return %0 : tensor<13x26x3xi32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_scatter_i32_i64_indices
|
|
func.func @test_scatter_i32_i64_indices(%arg0: tensor<13x27x3xi32>, %arg1: tensor<13x26xi64>, %arg2: tensor<13x26x3xi32>) -> tensor<13x27x3xi32> {
|
|
%0 = tosa.scatter %arg0, %arg1, %arg2 : (tensor<13x27x3xi32>, tensor<13x26xi64>, tensor<13x26x3xi32>) -> tensor<13x27x3xi32>
|
|
return %0 : tensor<13x27x3xi32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_cast_bool_fp32
|
|
func.func @test_cast_bool_fp32(%arg0: tensor<13x21x3xi1>) -> tensor<13x21x3xf32> {
|
|
%0 = tosa.cast %arg0 : (tensor<13x21x3xi1>) -> tensor<13x21x3xf32>
|
|
return %0 : tensor<13x21x3xf32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_cast_bool_i64
|
|
func.func @test_cast_bool_i64(%arg0: tensor<13x21x3xi1>) -> tensor<13x21x3xi64> {
|
|
%0 = tosa.cast %arg0 : (tensor<13x21x3xi1>) -> tensor<13x21x3xi64>
|
|
return %0 : tensor<13x21x3xi64>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_cast_fp32_bool
|
|
func.func @test_cast_fp32_bool(%arg0: tensor<13x21x3xf32>) -> tensor<13x21x3xi1> {
|
|
%0 = tosa.cast %arg0 : (tensor<13x21x3xf32>) -> tensor<13x21x3xi1>
|
|
return %0 : tensor<13x21x3xi1>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_cast_i64_bool
|
|
func.func @test_cast_i64_bool(%arg0: tensor<13x21x3xi64>) -> tensor<13x21x3xi1> {
|
|
%0 = tosa.cast %arg0 : (tensor<13x21x3xi64>) -> tensor<13x21x3xi1>
|
|
return %0 : tensor<13x21x3xi1>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_dynamic_dims
|
|
func.func @test_dynamic_dims(%arg0: tensor<?x8x16xi8>) -> tensor<?x16xi32> {
|
|
%0 = tosa.argmax %arg0 { axis = 1 : i32 } : (tensor<?x8x16xi8>) -> tensor<?x16xi32>
|
|
return %0 : tensor<?x16xi32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_add_shape
|
|
func.func @test_add_shape() {
|
|
%a = tosa.const_shape {values = dense<[1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
|
|
%b = tosa.const_shape {values = dense<[5, 6, 7, 8]> : tensor<4xindex>} : () -> !tosa.shape<4>
|
|
%c = tosa.add_shape %a, %b : (!tosa.shape<4>, !tosa.shape<4>) -> !tosa.shape<4>
|
|
return
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_dim
|
|
func.func @test_dim(%arg0: tensor<1x2x3x4xi32>) {
|
|
%0 = tosa.dim %arg0 {axis = 2 : i32} : (tensor<1x2x3x4xi32>) -> !tosa.shape<1>
|
|
return
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_dim_bf16
|
|
func.func @test_dim_bf16(%0: tensor<6x4x6x9xbf16>) {
|
|
%1 = tosa.dim %0 {axis = 1 : i32} : (tensor<6x4x6x9xbf16>) -> !tosa.shape<1>
|
|
return
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: test_exp2_shape
|
|
func.func @test_exp2_shape() {
|
|
%a = tosa.const_shape {values = dense<[5, 7, 10, 1]> : tensor<4xindex>} : () -> !tosa.shape<4>
|
|
%b = tosa.exp2_shape %a : (!tosa.shape<4>) -> !tosa.shape<4>
|
|
return
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: test_log2_ceil_shape
|
|
func.func @test_log2_ceil_shape() {
|
|
%a = tosa.const_shape {values = dense<[5, 7, 10, 1]> : tensor<4xindex>} : () -> !tosa.shape<4>
|
|
%b = tosa.log2_ceil_shape %a : (!tosa.shape<4>) -> !tosa.shape<4>
|
|
return
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_mod_shape
|
|
func.func @test_mod_shape() {
|
|
%a = tosa.const_shape {values = dense<[10, 11, 12]> : tensor<3xindex>} : () -> !tosa.shape<3>
|
|
%b = tosa.const_shape {values = dense<[3, 5, 2]> : tensor<3xindex>} : () -> !tosa.shape<3>
|
|
%c = tosa.mod_shape %a, %b : (!tosa.shape<3>, !tosa.shape<3>) -> !tosa.shape<3>
|
|
return
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_conv2d_block_scaled
|
|
func.func @test_conv2d_block_scaled(%arg0: tensor<1x4x4x64xf4E2M1FN>, %arg1: tensor<1x4x4x2xf8E8M0FNU>, %arg2: tensor<8x1x1x64xf4E2M1FN>, %arg3: tensor<8x1x1x2xf8E8M0FNU>, %arg4: tensor<1xf32>) -> tensor<1x4x4x8xf32> {
|
|
%pad = tosa.const_shape {values = dense<[0, 0, 0, 0]> : tensor<4xindex>} : () -> !tosa.shape<4>
|
|
%stride = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
|
|
%dilation = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
|
|
%0 = tosa.conv2d_block_scaled %arg0, %arg1, %arg2, %arg3, %arg4, %pad, %stride, %dilation {block_size = BLOCK_SIZE_32} : (tensor<1x4x4x64xf4E2M1FN>, tensor<1x4x4x2xf8E8M0FNU>, tensor<8x1x1x64xf4E2M1FN>, tensor<8x1x1x2xf8E8M0FNU>, tensor<1xf32>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<1x4x4x8xf32>
|
|
return %0 : tensor<1x4x4x8xf32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: test_assert_equal_shape
|
|
func.func @test_assert_equal_shape() {
|
|
%0 = tosa.const_shape {values = dense<[10, 15]> : tensor<2xindex>} : () -> !tosa.shape<2>
|
|
%1 = tosa.const_shape {values = dense<[5, 2]> : tensor<2xindex>} : () -> !tosa.shape<2>
|
|
tosa.assert_equal_shape %0, %1 {allow_broadcast = true} : (!tosa.shape<2>, !tosa.shape<2>) -> ()
|
|
return
|
|
}
|
|
|
|
// -----
|
|
func.func @test_maxpool2d_adaptive(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32> {
|
|
%kernel = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
|
|
%stride = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
|
|
%pad = tosa.const_shape {values = dense<[0, 0, 0, 0]> : tensor<4xindex>} : () -> !tosa.shape<4>
|
|
%0 = tosa.max_pool2d_adaptive %arg0, %kernel, %stride, %pad :
|
|
(tensor<1x32x32x8xf32>, !tosa.shape<2>, !tosa.shape<2>, !tosa.shape<4>) -> tensor<1x32x32x8xf32>
|
|
return %0 : tensor<1x32x32x8xf32>
|
|
}
|