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/external/tensorflow/tensorflow/compiler/xla/mlir/transforms/math/tests/
Dmath_optimization.mlir10 %c = arith.constant 1.0 : f32
11 %v = arith.constant dense <1.0> : vector<4xf32>
18 // CHECK: %[[SCALAR:.*]] = arith.mulf %arg0, %arg0
19 // CHECK: %[[VECTOR:.*]] = arith.mulf %arg1, %arg1
21 %c = arith.constant 2.0 : f32
22 %v = arith.constant dense <2.0> : vector<4xf32>
29 // CHECK: %[[TMP_S:.*]] = arith.mulf %arg0, %arg0
30 // CHECK: %[[SCALAR:.*]] = arith.mulf %arg0, %[[TMP_S]]
31 // CHECK: %[[TMP_V:.*]] = arith.mulf %arg1, %arg1
32 // CHECK: %[[VECTOR:.*]] = arith.mulf %arg1, %[[TMP_V]]
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tfrt/tests/jit/
Dtf_jitrt_math_approximation.mlir14 // CHECK-DAG: %[[CST_ONE:.*]] = arith.constant 1.000000e+00 : f32
15 // CHECK-DAG: %[[CST_CEPHES_EXP_P5:.*]] = arith.constant 5.000000e-01 : f32
16 // CHECK-DAG: %[[CST_EXP_HI:.*]] = arith.constant 8.872300e+01 : f32
17 // CHECK-DAG: %[[CST_EXP_LO:.*]] = arith.constant -8.872300e+01 : f32
18 // CHECK-DAG: %[[CST_CEPHES_LOG2E:.*]] = arith.constant 1.44269502 : f32
19 // CHECK-DAG: %[[CST_CEPHES_EXP_P0:.*]] = arith.constant 1.98756912E-4 : f32
20 // CHECK-DAG: %[[CST_CEPHES_EXP_P1:.*]] = arith.constant 0.00139819994 : f32
21 // CHECK-DAG: %[[CST_CEPHES_EXP_P2:.*]] = arith.constant 0.00833345205 : f32
22 // CHECK-DAG: %[[CST_CEPHES_EXP_P3:.*]] = arith.constant 0.0416657962 : f32
23 // CHECK-DAG: %[[CST_CEPHES_EXP_P4:.*]] = arith.constant 0.166666657 : f32
[all …]
Dtf_jitrt_pipeline_vectorized.mlir15 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
16 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
17 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
18 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
19 // CHECK-NOT: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
34 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
35 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
36 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
37 // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
38 // CHECK-NOT: arith.addf %{{.*}}, %{{.*}} : vector<4xf32>
[all …]
Dtf_jitrt_vectorize_tiled_ops.mlir7 %c0 = arith.constant 0 : index
8 %c2 = arith.constant 2 : index
9 %c8 = arith.constant 8 : index
25 %0 = arith.addf %a, %b : f32
36 // CHECK-DAG: %[[CST:.*]] = arith.constant 0.000000e+00 : f32
37 // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
49 // CHECK-NEXT: %[[SUM:.*]] = arith.addf %[[LHS]], %[[RHS]] : vector<2xf32>
57 %c0 = arith.constant 0 : index
58 %c4 = arith.constant 4 : index
59 %c60 = arith.constant 60 : index
[all …]
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/
Dlegalize-trigonometric-to-approximation.mlir15 // CHECK-DAG: %[[C:.*]] = arith.constant -2.76076837E-16 : f32
16 // CHECK-DAG: %[[C0:.*]] = arith.constant 2.00018794E-13 : f32
17 // CHECK-DAG: %[[C1:.*]] = arith.constant -8.60467184E-11 : f32
18 // CHECK-DAG: %[[C2:.*]] = arith.constant 5.12229725E-8 : f32
19 // CHECK-DAG: %[[C3:.*]] = arith.constant 1.48572235E-5 : f32
20 // CHECK-DAG: %[[C4:.*]] = arith.constant 6.37261954E-4 : f32
21 // CHECK-DAG: %[[C5:.*]] = arith.constant 0.00489352457 : f32
22 // CHECK-DAG: %[[C6:.*]] = arith.constant 1.19825836E-6 : f32
23 // CHECK-DAG: %[[C7:.*]] = arith.constant 1.18534706E-4 : f32
24 // CHECK-DAG: %[[C8:.*]] = arith.constant 0.00226843474 : f32
[all …]
Dbufferize.mlir11 // CHECK: %[[C0:.*]] = arith.constant 0 : index
14 %c0 = arith.constant 0 : index
22 // CHECK-DAG: %[[B:.*]] = arith.constant 1.2
23 // CHECK-DAG: %[[C:.*]] = arith.constant 2.3
24 // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
25 // CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
26 // CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
32 %b = arith.constant 1.2 : f32
33 %c = arith.constant 2.3 : f32
35 %c0 = arith.constant 0 : index
[all …]
Dtile_loops.mlir6 %c0 = arith.constant 0 : index
7 %c1 = arith.constant 1 : index
8 %c16 = arith.constant 16 : index
11 // CHECK-DAG: %[[C8:.*]] = arith.constant 8
12 // CHECK-DAG: %[[C4:.*]] = arith.constant 4
28 // CHECK: %[[C4:.*]] = arith.constant 4 : index
29 %c0 = arith.constant 0 : index
30 %c1 = arith.constant 1 : index
31 %c3 = arith.constant 3 : index
32 %c8 = arith.constant 8 : index
[all …]
Dbufferize_one_shot.mlir8 // CHECK: %[[C0:.*]] = arith.constant 0 : index
11 %c0 = arith.constant 0 : index
21 // CHECK-DAG: %[[B:.*]] = arith.constant 1.2
22 // CHECK-DAG: %[[C:.*]] = arith.constant 2.3
23 // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
24 // CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
25 // CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
30 %b = arith.constant 1.2 : f32
31 %c = arith.constant 2.3 : f32
33 %c0 = arith.constant 0 : index
[all …]
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/include/mlir-hlo/Dialect/mhlo/transforms/
Dmap_mhlo_to_scalar_op.h48 using FOp = ::mlir::arith::AddFOp;
49 using IOp = ::mlir::arith::AddIOp;
50 using UOp = ::mlir::arith::AddIOp;
55 using IOp = ::mlir::arith::AndIOp;
56 using UOp = ::mlir::arith::AndIOp;
60 using FOp = ::mlir::arith::CmpFOp;
61 using IOp = ::mlir::arith::CmpIOp;
62 using UOp = ::mlir::arith::CmpIOp;
94 using FOp = ::mlir::arith::MaxFOp;
95 using IOp = ::mlir::arith::MaxSIOp;
[all …]
/external/tensorflow/tensorflow/compiler/mlir/lite/tests/
Dconst-fold.mlir5 %0 = arith.constant dense<4.5> : tensor<f32>
6 %1 = arith.constant dense<1.5> : tensor<f32>
8 %2 = arith.constant dense< 3.5> : tensor<4xf32>
9 %3 = arith.constant dense<-0.5> : tensor<4xf32>
11 // CHECK-DAG: %[[CST:.*]] = arith.constant dense<3.500000e+00> : tensor<4xf32>
12 // CHECK-DAG: %[[CST_0:.*]] = arith.constant dense<-5.000000e-01> : tensor<4xf32>
13 // CHECK-DAG: %[[CST_1:.*]] = arith.constant dense<6.000000e+00> : tensor<f32>
14 // CHECK-DAG: %[[CST_2:.*]] = arith.constant dense<4.000000e+00> : tensor<4xf32>
15 // CHECK-DAG: %[[CST_3:.*]] = arith.constant dense<5.000000e+00> : tensor<4xf32>
16 // CHECK-DAG: %[[CST_4:.*]] = arith.constant dense<3.000000e+00> : tensor<4xf32>
[all …]
Doptimize.mlir51 %cst = arith.constant dense<1.5> : tensor<16xf32>
52 …%cst_0 = arith.constant dense<[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0…
57 …// CHECK-DAG: %cst = arith.constant dense<[2.500000e+00, 3.500000e+00, 4.500000e+00, 5.500000e+00,…
63 %cst = arith.constant dense<0.5> : tensor<16xf32>
64 …%cst_0 = arith.constant dense<[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0…
69 …// CHECK-DAG: %cst = arith.constant dense<[5.000000e-01, 1.500000e+00, 2.500000e+00, 3.500000e+00,…
75 %cst = arith.constant dense<1.5> : tensor<32xf32>
76 …%cst_0 = arith.constant dense<[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0…
77 %cst_1 = arith.constant dense<[1, 64, 84, 32]> : tensor<4xi32>
78 %cst_2 = arith.constant dense<1.0> : tensor<32x4x4x128xf32>
[all …]
Dprepare-tf-fake-quant.mlir8 %arg1 = arith.constant dense<[0.0, -1.0, 1.0, 0.0]> : tensor<4xf32>
9 %arg2 = arith.constant dense<[255.0, 254.0, 256.0, 1.0e-9]> : tensor<4xf32>
22 %arg1 = arith.constant dense<0.0> : tensor<f32>
23 %arg2 = arith.constant dense<255.0> : tensor<f32>
36 %arg1 = arith.constant dense<0.0> : tensor<f32>
37 %arg2 = arith.constant dense<255.0> : tensor<f32>
49 %in = arith.constant dense<0.0> : tensor<8xf32>
50 %min = arith.constant dense<0.0> : tensor<f32>
51 %max = arith.constant dense<255.0> : tensor<f32>
61 // CHECK: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<8xf32>
[all …]
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/Dialect/gml_st/
Dgml_st_to_scf.mlir10 %cst = arith.constant 0.000000e+00 : f32
11 %c24 = arith.constant 24 : index
12 %c16 = arith.constant 16 : index
13 %c0 = arith.constant 0 : index
14 %c192 = arith.constant 192 : index
39 // CHECK-DAG: %[[C24:.*]] = arith.constant 24 : index
40 // CHECK-DAG: %[[C16:.*]] = arith.constant 16 : index
41 // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
42 // CHECK-DAG: %[[C192:.*]] = arith.constant 192 : index
55 %cst = arith.constant 0.000000e+00 : f32
[all …]
Dtiling.mlir11 %c0 = arith.constant 0 : index
12 %c1 = arith.constant 1 : index
22 %generic_scalar = arith.addf %lhs_scalar, %rhs_scalar : f32
34 // CHECK-TILE-DAG: %[[C0:.*]] = arith.constant 0
36 // CHECK-TILE-DAG: %[[C1:.*]] = arith.constant 1
40 // CHECK-TILE-DAG: %[[C0:.*]] = arith.constant 0
42 // CHECK-TILE-DAG: %[[C1:.*]] = arith.constant 1
46 // CHECK-TILE: %[[LB_C0:.*]] = arith.constant 0
48 // CHECK-TILE: %[[C0:.*]] = arith.constant 0
50 // CHECK-TILE: %[[C1:.*]] = arith.constant 1
[all …]
Dcanonicalize.mlir9 %cst = arith.constant 0.000000e+00 : f32
10 %c24 = arith.constant 24 : index
11 %c0 = arith.constant 0 : index
12 %c192 = arith.constant 192 : index
33 %c0 = arith.constant 0 : index
34 %c24 = arith.constant 24 : index
35 %c48 = arith.constant 48 : index
52 // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
53 // CHECK-DAG: %[[C24:.*]] = arith.constant 24 : index
54 // CHECK-DAG: %[[C48:.*]] = arith.constant 48 : index
[all …]
Dnested_tiling.mlir15 // CHECK-PERFECT: %[[C0:.*]] = arith.constant 0
16 // CHECK-PERFECT: %[[C64:.*]] = arith.constant 64
17 // CHECK-PERFECT: %[[C32:.*]] = arith.constant 32
18 // CHECK-PERFECT: %[[C16:.*]] = arith.constant 16
19 // CHECK-PERFECT: %[[C8:.*]] = arith.constant 8
28 // CHECK-PERFECT: %[[C4:.*]] = arith.constant 4
29 // CHECK-PERFECT: %[[C1:.*]] = arith.constant 1
44 // CHECK-IMPERFECT: %[[C0:.*]] = arith.constant 0
45 // CHECK-IMPERFECT: %[[C64:.*]] = arith.constant 64
46 // CHECK-IMPERFECT: %[[C32:.*]] = arith.constant 32
[all …]
/external/cronet/third_party/protobuf/js/binary/
Darith.js40 goog.provide('jspb.arith.Int64');
41 goog.provide('jspb.arith.UInt64');
53 jspb.arith.UInt64 = function(lo, hi) {
70 * @param {!jspb.arith.UInt64} other
73 jspb.arith.UInt64.prototype.cmp = function(other) {
86 * @return {!jspb.arith.UInt64}
88 jspb.arith.UInt64.prototype.rightShift = function() {
91 return new jspb.arith.UInt64(lo >>> 0, hi >>> 0);
97 * @return {!jspb.arith.UInt64}
99 jspb.arith.UInt64.prototype.leftShift = function() {
[all …]
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/lib/Dialect/mhlo/transforms/
Dhlo_legalize_shape_ops_to_standard.cc55 Value negOne = rewriter.create<arith::ConstantIndexOp>(loc, -1); in matchAndRewrite()
66 : rewriter.create<arith::IndexCastOp>( in matchAndRewrite()
82 loc, rewriter.create<arith::MulIOp>(loc, lhs, rhs).getResult()); in matchAndRewrite()
84 Value missingDimVal = rewriter.create<arith::DivUIOp>( in matchAndRewrite()
97 Value useMissingDimVal = b.create<arith::CmpIOp>( in matchAndRewrite()
98 loc, arith::CmpIPredicate::eq, extent, negOne); in matchAndRewrite()
99 Value dimVal = b.create<arith::SelectOp>(loc, useMissingDimVal, in matchAndRewrite()
103 : b.create<arith::IndexCastOp>( in matchAndRewrite()
121 Value negOne = rewriter.create<arith::ConstantIndexOp>(loc, -1); in matchAndRewrite()
122 Value zero = rewriter.create<arith::ConstantIndexOp>(loc, 0); in matchAndRewrite()
[all …]
Dlegalize_trigonometric_to_approximation.cc61 arg = rewriter.create<arith::ExtFOp>(loc, rewriter.getF32Type(), arg); in matchAndRewrite()
75 rewriter.create<arith::TruncFOp>(loc, rewriter.getF16Type(), result); in matchAndRewrite()
105 Value inputSquared = rewriter.create<arith::MulFOp>(loc, input, input); in emitApproximation()
106 Value numerator = rewriter.create<arith::ConstantOp>( in emitApproximation()
109 numerator = rewriter.create<arith::AddFOp>( in emitApproximation()
110 loc, rewriter.create<arith::MulFOp>(loc, inputSquared, numerator), in emitApproximation()
111 rewriter.create<arith::ConstantOp>( in emitApproximation()
114 numerator = rewriter.create<arith::MulFOp>(loc, input, numerator); in emitApproximation()
115 Value denominator = rewriter.create<arith::ConstantOp>( in emitApproximation()
119 denominator = rewriter.create<arith::AddFOp>( in emitApproximation()
[all …]
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/lib/Transforms/
Dbufferize.cc36 struct BufferizeConstantOp : public OpConversionPattern<arith::ConstantOp> {
37 using OpConversionPattern<arith::ConstantOp>::OpConversionPattern;
40 arith::ConstantOp op, OpAdaptor /*adaptor*/, in matchAndRewrite()
53 // arith.constant doesn't handle scalar complex types. in matchAndRewrite()
59 return rewriter.create<arith::ConstantOp>(loc, attr); in matchAndRewrite()
80 Value index = rewriter.create<arith::ConstantIndexOp>(loc, en.index()); in matchAndRewrite()
98 Value zero = lb.create<arith::ConstantIndexOp>(0); in matchAndRewrite()
110 Value rankIsGreater = lb.create<arith::CmpIOp>( in matchAndRewrite()
111 arith::CmpIPredicate::ugt, ranks[i], maxRank); in matchAndRewrite()
112 maxRank = lb.create<arith::SelectOp>(rankIsGreater, ranks[i], maxRank); in matchAndRewrite()
[all …]
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/Dialect/mhlo/
Dhlo-legalize-shape-ops-to-standard.mlir7 // CHECK: %[[N1:.*]] = arith.constant -1 : index
8 // CHECK: %[[IT:.*]] = arith.index_cast %[[TARGET_SHAPE]] : tensor<2xi32> to tensor<2xindex>
12 // CHECK: %[[NEW_RED:.*]] = arith.muli %[[VAL]], %[[REDUCTION]] : index
15 // CHECK: %[[DYNAMIC_EXTENT:.*]] = arith.divui %[[NUM_ELS]], %[[TOTAL]] : index
19 // CHECK: %[[IS_DYNAMIC:.*]] = arith.cmpi eq, %[[EXT1]], %[[N1]] : index
20 // CHECK: %[[EXTENT:.*]] = arith.select %[[IS_DYNAMIC]], %[[DYNAMIC_EXTENT]], %[[EXT1]] : index
21 // CHECK: %[[EXTENT_INT:.*]] = arith.index_cast %[[EXTENT]] : index to i32
32 // CHECK-DAG: %[[N1:.*]] = arith.constant -1 : index
33 // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
34 // CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
[all …]
Dlegalize-to-std.mlir5 // CHECK-NEXT: %0 = arith.addf %arg0, %arg1 : tensor<4xf32>
8 // CHECK-NEXT: %1 = arith.mulf %0, %arg1 : tensor<4xf32>
11 // CHECK-NEXT: %2 = arith.subf %1, %arg1 : tensor<4xf32>
14 // CHECK-NEXT: %3 = arith.divf %2, %arg1 : tensor<4xf32>
17 // CHECK-NEXT: %4 = arith.remf %3, %arg1 : tensor<4xf32>
26 // CHECK-NEXT: %0 = arith.addi %arg0, %arg1 : tensor<4xi32>
29 // CHECK-NEXT: %1 = arith.muli %0, %arg1 : tensor<4xi32>
32 // CHECK-NEXT: %2 = arith.subi %1, %arg1 : tensor<4xi32>
35 // CHECK-NEXT: %3 = arith.divsi %2, %arg1 : tensor<4xi32>
38 // CHECK-NEXT: %4 = arith.remsi %3, %arg1 : tensor<4xi32>
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tfr/python/
Dtfr_gen_test.py269 CHECK-NEXT: %[[n:.*]] = arith.constant 10 : i64
271 CHECK-NEXT: %[[cst:.*]] = arith.constant 0 : index
275 CHECK-NEXT: %[[cst_1:.*]] = arith.constant 1 : i64
277 CHECK-NEXT: %[[begin:.*]] = arith.index_cast %[[cst_1]] : i64 to index
279 CHECK-NEXT: %[[end:.*]] = arith.index_cast %[[n]] : i64 to index
281 CHECK-NEXT: %[[step:.*]] = arith.constant 1 : index
293 CHECK-NEXT: %{{.*}} = arith.constant true
321 CHECK-NEXT: %[[index:.*]] = arith.constant 1 : index
333 CHECK-NEXT: %[[cst:.*]] = arith.constant 0 : i64
334 CHECK-NEXT: %[[cst_1:.*]] = arith.constant 2 : i64
[all …]
/external/tensorflow/tensorflow/compiler/mlir/tfrt/jit/transforms/
Dtf_jitrt_math_approximation.cc42 namespace arith = ::mlir::arith;
109 return builder.create<arith::ConstantOp>(builder.getF32FloatAttr(value)); in f32Cst()
113 return builder.create<arith::ConstantOp>(builder.getI32IntegerAttr(value)); in i32Cst()
121 return builder.create<mlir::arith::SelectOp>( in min()
122 builder.create<arith::CmpFOp>(arith::CmpFPredicate::OLT, a, b), a, b); in min()
126 return builder.create<mlir::arith::SelectOp>( in max()
127 builder.create<arith::CmpFOp>(arith::CmpFPredicate::OGT, a, b), a, b); in max()
154 return builder.create<arith::MulFOp>(a, b); in ldexp()
157 return builder.create<arith::SubIOp>(a, b); in ldexp()
160 return builder.create<arith::ShLIOp>(a, pos); in ldexp()
[all …]
/external/mesa3d/src/gallium/drivers/nouveau/nv30/
Dnvfx_fragprog.c231 #define arith(s,o,d,m,s0,s1,s2) \ macro
244 struct nvfx_insn insn = arith(0, MOV, none.reg, NVFX_FP_MASK_X, src, none, none); in nv40_fp_if()
489 … nvfx_fp_emit(fpc, arith(0, ADD, src[i].reg, NVFX_FP_MASK_ALL, tgsi_src(fpc, fsrc), addend, none)); in nvfx_fragprog_parse_instruction()
495 … nvfx_fp_emit(fpc, arith(0, MOV, src[i].reg, NVFX_FP_MASK_ALL, tgsi_src(fpc, fsrc), none, none)); in nvfx_fragprog_parse_instruction()
505 … nvfx_fp_emit(fpc, arith(0, MOV, src[i].reg, NVFX_FP_MASK_ALL, tgsi_src(fpc, fsrc), none, none)); in nvfx_fragprog_parse_instruction()
515 … nvfx_fp_emit(fpc, arith(0, MOV, src[i].reg, NVFX_FP_MASK_ALL, tgsi_src(fpc, fsrc), none, none)); in nvfx_fragprog_parse_instruction()
538 nvfx_fp_emit(fpc, arith(sat, ADD, dst, mask, src[0], src[1], none)); in nvfx_fragprog_parse_instruction()
542 nvfx_fp_emit(fpc, arith(0, FLR, tmp.reg, mask, neg(src[0]), none, none)); in nvfx_fragprog_parse_instruction()
543 nvfx_fp_emit(fpc, arith(sat, MOV, dst, mask, neg(tmp), none, none)); in nvfx_fragprog_parse_instruction()
546 insn = arith(0, MOV, none.reg, mask, src[0], none, none); in nvfx_fragprog_parse_instruction()
[all …]

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