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/external/python/cpython3/Lib/test/decimaltestdata/
Dreduce.decTest2 -- reduce.decTest -- remove trailing zeros --
30 redx001 reduce '1' -> '1'
31 redx002 reduce '-1' -> '-1'
32 redx003 reduce '1.00' -> '1'
33 redx004 reduce '-1.00' -> '-1'
34 redx005 reduce '0' -> '0'
35 redx006 reduce '0.00' -> '0'
36 redx007 reduce '00.0' -> '0'
37 redx008 reduce '00.00' -> '0'
38 redx009 reduce '00' -> '0'
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DdqReduce.decTest30 dqred001 reduce '1' -> '1'
31 dqred002 reduce '-1' -> '-1'
32 dqred003 reduce '1.00' -> '1'
33 dqred004 reduce '-1.00' -> '-1'
34 dqred005 reduce '0' -> '0'
35 dqred006 reduce '0.00' -> '0'
36 dqred007 reduce '00.0' -> '0'
37 dqred008 reduce '00.00' -> '0'
38 dqred009 reduce '00' -> '0'
39 dqred010 reduce '0E+1' -> '0'
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DddReduce.decTest29 ddred001 reduce '1' -> '1'
30 ddred002 reduce '-1' -> '-1'
31 ddred003 reduce '1.00' -> '1'
32 ddred004 reduce '-1.00' -> '-1'
33 ddred005 reduce '0' -> '0'
34 ddred006 reduce '0.00' -> '0'
35 ddred007 reduce '00.0' -> '0'
36 ddred008 reduce '00.00' -> '0'
37 ddred009 reduce '00' -> '0'
38 ddred010 reduce '0E+1' -> '0'
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/external/google-fruit/extras/scripts/
Dparser.out128 $end reduce using rule 3 (optional_balanced_string -> .)
129 COMMA reduce using rule 3 (optional_balanced_string -> .)
130 GREATER_THAN reduce using rule 3 (optional_balanced_string -> .)
131 RBRACKET reduce using rule 3 (optional_balanced_string -> .)
132 RPAREN reduce using rule 3 (optional_balanced_string -> .)
133 RBRACE reduce using rule 3 (optional_balanced_string -> .)
164 $end reduce using rule 3 (optional_balanced_string -> .)
165 COMMA reduce using rule 3 (optional_balanced_string -> .)
166 GREATER_THAN reduce using rule 3 (optional_balanced_string -> .)
167 RBRACKET reduce using rule 3 (optional_balanced_string -> .)
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/external/tensorflow/tensorflow/compiler/xla/service/gpu/
Dreduction_splitter.cc30 Status HandleReduce(HloInstruction *reduce) override { in HandleReduce() argument
31 VLOG(4) << "Input: " << reduce->ToString(); in HandleReduce()
35 if (IsReductionFromOrToContiguousDimensions(*reduce)) { in HandleReduce()
38 if (reduce->dimensions().size() < 2) { in HandleReduce()
41 if (!reduce->shape().IsArray()) { in HandleReduce()
46 HloInstruction *operand = reduce->mutable_operand(0); in HandleReduce()
52 for (int64_t i = 0; i < reduce->dimensions().size(); ++i) { in HandleReduce()
53 for (int64_t j = i + 1; j < reduce->dimensions().size(); ++j) { in HandleReduce()
54 CHECK(abs(reduce->dimensions(i) - reduce->dimensions(j)) > 1) in HandleReduce()
59 // The reduce op has non-contiguous dimensions. Look for the dimension with in HandleReduce()
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Dgpu_fusible_test.cc42 ROOT reduce = f32[2,2]{1,0} reduce(exp, c0), dimensions={2}, to_apply=scalar_add in TEST_F()
67 ROOT reduce = f32[1024]{0} reduce(convert, c0.2), dimensions={0,2,3}, to_apply=scalar_add in TEST_F()
100 ROOT reduce = f32[1]{0} reduce(convert, c0.2), dimensions={0,2,3}, to_apply=scalar_add in TEST_F()
122 ROOT reduce = f32[1024]{0} reduce(p0.1, c0.1), dimensions={0,2,3}, to_apply=scalar_add in TEST_F()
142 ROOT reduce = f32[1024]{0} reduce(p0.1, c0.1), dimensions={1,2,3}, to_apply=scalar_add in TEST_F()
172 ROOT reduce = f32[1024]{0} reduce(convert, c0.2), dimensions={0,2,3}, to_apply=scalar_add in TEST_F()
203 ROOT reduce = f32[1024]{0} reduce(loop_fusion, c0.2), dimensions={0,2,3}, to_apply=scalar_add in TEST_F()
219 ROOT reduce = f32[512]{0} reduce(p1, c0), dimensions={0,2,3}, to_apply=scalar_add in TEST_F()
223 const HloInstruction* reduce = in TEST_F() local
225 ASSERT_EQ(reduce->opcode(), HloOpcode::kReduce); in TEST_F()
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Dreduction_layout_normalizer.cc39 auto reduce = Cast<HloReduceInstruction>(hlo); in HandleReduce() local
40 VLOG(5) << "Input: " << reduce->ToString(); in HandleReduce()
48 const Shape &first_instruction_shape = reduce->inputs()[0]->shape(); in HandleReduce()
50 for (HloInstruction *operand : reduce->inputs()) { in HandleReduce()
56 reduce->parent()->AddInstruction(HloInstruction::CreateUnary( in HandleReduce()
73 reduce->shape().IsTuple() ? reduce->shape().tuple_shapes(operand_idx) in HandleReduce()
74 : reduce->shape(); in HandleReduce()
89 absl::c_count_if(reduce->dimensions(), [&](int64_t dim) { in HandleReduce()
106 if (absl::c_linear_search(reduce->dimensions(), logical_dim)) { in HandleReduce()
126 if (new_operand_shape == operand_shape && reduce->inputs().size() == 1) { in HandleReduce()
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Dmulti_output_fusion_test.cc61 // Fusion with reduce instruction root and a sibling reduce instruction in TEST_F()
68 …ROOT reduce.1 = f32[512]{0} reduce(mul, const.1), dimensions={0,2,3}, to_apply=scalar_add_computat… in TEST_F()
76reduce.2 = f32[512]{0} reduce(p1, const.2), dimensions={0,2,3}, to_apply=scalar_add_computation in TEST_F()
77 ROOT root = (f32[512]{0}, f32[512]{0}) tuple(fusion, reduce.2) in TEST_F()
86 op::Tuple(op::Reduce(), op::Reduce())); in TEST_F()
95 ROOT reduce.1 = f32[] reduce(mul, const.1), dimensions={0}, to_apply=scalar_add_computation in TEST_F()
102 ROOT reduce.2 = f32[] reduce(r1, const.2), dimensions={1,0}, to_apply=scalar_mul_computation in TEST_F()
122 ROOT reduce.1 = f32[] reduce(mul, const.1), dimensions={0,1}, to_apply=scalar_add_computation in TEST_F()
128 … ROOT reduce.2 = f32[10]{0} reduce(p1.2, const.2), dimensions={0}, to_apply=scalar_mul_computation in TEST_F()
144 // Two sibling fusions with reduce instruction roots sharing the same input in TEST_F()
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/external/tensorflow/tensorflow/compiler/xla/service/
Dreduce_decomposer.cc37 auto reduce = Cast<HloReduceInstruction>(hlo); in HandleReduce() local
40 for (HloInstruction* input : reduce->inputs()) { in HandleReduce()
41 auto first_input = reduce->inputs()[0]; in HandleReduce()
59 MakeReduceHlo(new_inputs, reduce->init_values(), reduce->dimensions(), in HandleReduce()
60 reduce->called_computations()[0])); in HandleReduce()
61 TF_RETURN_IF_ERROR(ReplaceInstruction(reduce, new_reduce)); in HandleReduce()
74 auto reduce = Cast<HloReduceInstruction>(hlo); in HandleReduce() local
75 auto shape = reduce->shape(); in HandleReduce()
76 if (custom_layout_allowed_ && custom_layout_allowed_(reduce)) { in HandleReduce()
80 std::vector<Shape> expected_shapes(reduce->input_count()); in HandleReduce()
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Dar_crs_combiner_test.cc415 %all-reduce.ar.1 = bf16[] in TEST_F()
416 all-reduce(%p), in TEST_F()
422 convert(%all-reduce.ar.1), in TEST_F()
424 %all-reduce.1 = f32[] in TEST_F()
425 all-reduce(%convert.1), in TEST_F()
430 %all-reduce.ar.2 = bf16[] in TEST_F()
431 all-reduce(%constant.bf16), in TEST_F()
437 convert(%all-reduce.ar.2), in TEST_F()
439 %all-reduce.2 = f32[] in TEST_F()
440 all-reduce(%convert.2), in TEST_F()
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Dall_reduce_simplifier_test.cc73 all-reduce = f32[8,16] all-reduce(p0), replica_groups={}, to_apply=sum in TEST_F()
74 all-reduce.1 = f32[8,16] all-reduce(p0), replica_groups={}, to_apply=max in TEST_F()
75 all-reduce.2 = f32[8,16] all-reduce(p1), replica_groups={}, to_apply=min in TEST_F()
76 all-reduce.3 = f32[] all-reduce(p2), replica_groups={}, to_apply=sum.1 in TEST_F()
77 …= (f32[8,16], f32[8,16], f32[8,16], f32[]) tuple(all-reduce, all-reduce.1, all-reduce.2, all-reduc… in TEST_F()
112 all-reduce = f32[8,16] all-reduce(p0), replica_groups={}, to_apply=max in TEST_F()
113 ROOT all-reduce.1 = f32[8,16] all-reduce(all-reduce), replica_groups={}, to_apply=sum in TEST_F()
151 all-reduce = f32[8,16] all-reduce(p0), replica_groups={{0,1,2,3},{4,5,6,7}}, to_apply=sum in TEST_F()
152 all-reduce.1 = f32[8,16] all-reduce(p0), replica_groups={{0,1,2,3},{4,5,6,7}}, to_apply=max in TEST_F()
153 all-reduce.2 = f32[8,16] all-reduce(p1), replica_groups={{0,1,2,3},{4,5,6,7}}, to_apply=min in TEST_F()
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Dall_reduce_reassociate_test.cc62 ar0 = f32[8] all-reduce(p0), replica_groups={}, to_apply=sum in TEST_F()
63 ar1 = f32[8] all-reduce(p1), replica_groups={}, to_apply=sum in TEST_F()
87 ar0 = f32[8] all-reduce(p0), channel_id=1, replica_groups={}, to_apply=sum in TEST_F()
88 ar1 = f32[8] all-reduce(p1), channel_id=1, replica_groups={}, to_apply=sum in TEST_F()
116 ar0 = f32[8] all-reduce(p0), replica_groups={}, to_apply=sum in TEST_F()
117 ar1 = f32[8] all-reduce(p1), replica_groups={}, to_apply=sum in TEST_F()
118 ar2 = f32[8] all-reduce(p2), replica_groups={}, to_apply=sum in TEST_F()
119 ar3 = f32[8] all-reduce(p3), replica_groups={}, to_apply=sum in TEST_F()
151 ar0 = f32[8] all-reduce(p0), replica_groups={}, to_apply=sum in TEST_F()
152 ar1 = f32[8] all-reduce(p1), replica_groups={}, to_apply=sum in TEST_F()
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/external/pytorch/aten/src/ATen/native/
DReductionType.h9 inline ReductionType get_reduction_enum(const c10::string_view& reduce) { in get_reduction_enum() argument
10 if (reduce == "max" || reduce == "amax") { in get_reduction_enum()
12 } else if (reduce == "mean") { in get_reduction_enum()
14 } else if (reduce == "min" || reduce == "amin") { in get_reduction_enum()
16 } else if (reduce == "sum") { in get_reduction_enum()
18 } else if (reduce == "prod") { in get_reduction_enum()
21 … TORCH_CHECK(false, "reduce argument must be either sum, prod, mean, amax or amin, got ", reduce); in get_reduction_enum()
26 inline ReductionType get_operator_enum(const c10::string_view reduce, bool use_new_options) { in get_operator_enum() argument
28 return get_reduction_enum(reduce); in get_operator_enum()
30 if (reduce == "add") { in get_operator_enum()
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/external/pytorch/aten/src/ATen/native/cpu/
DReduceUtils.h22 static constexpr auto reduce = ReductionType::SUM; \
26 static constexpr auto reduce = ReductionType::MEAN; \
30 static constexpr auto reduce = ReductionType::MIN; \
34 static constexpr auto reduce = ReductionType::MAX; \
38 static constexpr auto reduce = ReductionType::PROD; \
44 template <typename scalar_t, ReductionType reduce>
48 if (reduce == ReductionType::SUM || in init_value()
49 reduce == ReductionType::MEAN) { in init_value()
51 } else if (reduce == ReductionType::PROD) { in init_value()
53 } else if (reduce == ReductionType::MAX) { in init_value()
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/external/angle/third_party/glslang/src/Test/baseResults/
Dspv.shaderBallotAMD.comp.out96 29: 6(int) GroupSMin 28 Reduce 27
102 36: 7(int) GroupUMin 28 Reduce 35
104 38: 7(int) GroupUMin 28 Reduce 37
111 46: 9(float) GroupFMin 28 Reduce 45
113 48: 9(float) GroupFMin 28 Reduce 47
115 50: 9(float) GroupFMin 28 Reduce 49
122 58:11(float64_t) GroupFMin 28 Reduce 57
124 60:11(float64_t) GroupFMin 28 Reduce 59
126 62:11(float64_t) GroupFMin 28 Reduce 61
128 64:11(float64_t) GroupFMin 28 Reduce 63
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/external/deqp-deps/glslang/Test/baseResults/
Dspv.shaderBallotAMD.comp.out96 29: 6(int) GroupSMin 28 Reduce 27
102 36: 7(int) GroupUMin 28 Reduce 35
104 38: 7(int) GroupUMin 28 Reduce 37
111 46: 9(float) GroupFMin 28 Reduce 45
113 48: 9(float) GroupFMin 28 Reduce 47
115 50: 9(float) GroupFMin 28 Reduce 49
122 58:11(float64_t) GroupFMin 28 Reduce 57
124 60:11(float64_t) GroupFMin 28 Reduce 59
126 62:11(float64_t) GroupFMin 28 Reduce 61
128 64:11(float64_t) GroupFMin 28 Reduce 63
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/external/tensorflow/tensorflow/lite/kernels/
Dreduce.cc15 #include "tensorflow/lite/kernels/internal/reference/reduce.h"
31 #include "tensorflow/lite/kernels/internal/optimized/reduce.h"
44 namespace reduce { namespace
201 // mean or temp prod when calculating reduce prod. in InitializeTemporaries()
649 // Apply reduce operation using the 'reducer' function on all of 'input_data'.
650 // and reduce all to single element.
691 // Reduce all data from different workers. in ReduceAllDims()
698 // The underlying logic for Reduce Sum/Prod/Max/Min/Any
863 // Rescaling 8bit reduce sum. in EvalSum()
1001 } // namespace reduce
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/external/tensorflow/tensorflow/lite/delegates/gpu/common/tasks/
Dreduce.h31 class Reduce : public GPUOperation {
33 Reduce() = default;
34 Reduce(const std::map<Axis, int>& axis_to_reduce, OperationType op_type,
45 Reduce(Reduce&& operation);
46 Reduce& operator=(Reduce&& operation);
47 Reduce(const Reduce&) = delete;
48 Reduce& operator=(const Reduce&) = delete;
60 Reduce CreateReduce(const std::set<Axis>& axis_to_reduce, const BHWC& src_shape,
64 Reduce CreateReduce(const std::set<Axis>& axis_to_reduce,
/external/sdv/vsomeip/third_party/boost/algorithm/include/boost/algorithm/cxx17/
Dreduce.hpp8 /// \file reduce.hpp
26 T reduce(InputIterator first, InputIterator last, T init, BinaryOperation bOp) in reduce() function
35 T reduce(InputIterator first, InputIterator last, T init) in reduce() function
38 return boost::algorithm::reduce(first, last, init, std::plus<VT>()); in reduce()
43 reduce(InputIterator first, InputIterator last) in reduce() function
45 return boost::algorithm::reduce(first, last, in reduce()
51 reduce(const Range &r) in reduce() function
53 return boost::algorithm::reduce(boost::begin(r), boost::end(r)); in reduce()
58 T reduce(const Range &r, T init) in reduce() function
60 return boost::algorithm::reduce(boost::begin (r), boost::end (r), init); in reduce()
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/external/tensorflow/tensorflow/core/kernels/
Dreduction_ops_test.cc24 // Creates a Graph which "reduce"s a 3D float tensor of "num" elements
27 static Graph* ToScalar(const string& reduce, int num_x, int num_y) { in ToScalar() argument
34 test::graph::Reduce(g, reduce, test::graph::Constant(g, data), in ToScalar()
39 static Graph* ColReduce(const string& reduce, int num_x, int num_y) { in ColReduce() argument
45 test::graph::Reduce(g, reduce, test::graph::Constant(g, data), in ColReduce()
50 static Graph* RowReduce(const string& reduce, int num_x, int num_y) { in RowReduce() argument
56 test::graph::Reduce(g, reduce, test::graph::Constant(g, data), in RowReduce()
61 static Graph* ThreeDYReduce(const string& reduce, int num_y, int num_z) { in ThreeDYReduce() argument
67 test::graph::Reduce(g, reduce, test::graph::Constant(g, data), in ThreeDYReduce()
72 static Graph* ThreeDXZReduce(const string& reduce, int num_y, int num_z) { in ThreeDXZReduce() argument
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/external/mpdecimal/libmpdec/literature/
Dumodarith.lisp248 ;; dw-reduce is correct
251 (defun dw-reduce (hi lo m base)
256 (defthmd dw-reduce-correct
261 (equal (dw-reduce hi lo m base)
270 (defthmd dw-reduce-aux1
283 (defthm dw-reduce-aux2
290 (defthmd dw-reduce-second-quotient-fits-in-single-word
300 ("Subgoal 1.2" :use ((:instance dw-reduce-aux1
309 (let* ((r (dw-reduce hi lo m base))
328 :hints (("Goal" :in-theory (disable dw-reduce)
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/external/python/cpython3/Modules/_decimal/libmpdec/literature/
Dumodarith.lisp250 ;; dw-reduce is correct
253 (defun dw-reduce (hi lo m base)
258 (defthmd dw-reduce-correct
263 (equal (dw-reduce hi lo m base)
272 (defthmd dw-reduce-aux1
285 (defthm dw-reduce-aux2
292 (defthmd dw-reduce-second-quotient-fits-in-single-word
302 ("Subgoal 1.2" :use ((:instance dw-reduce-aux1
311 (let* ((r (dw-reduce hi lo m base))
330 :hints (("Goal" :in-theory (disable dw-reduce)
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/external/jsilver/src/com/google/clearsilver/jsilver/syntax/parser/
DParser.java30 private final static int REDUCE = 1; field in Parser
166 case REDUCE: in parse()
169 case 0: /* reduce ANone1Grammar */ in parse()
175 case 1: /* reduce AOne1Grammar */ in parse()
181 case 2: /* reduce AMany1Grammar */ in parse()
187 case 3: /* reduce ADataCommand */ in parse()
193 case 4: /* reduce AAcommentcommand1Command */ in parse()
199 case 5: /* reduce AAcommentcommand2Command */ in parse()
205 case 6: /* reduce AVarCommand */ in parse()
211 case 7: /* reduce ALvarCommand */ in parse()
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/external/pytorch/torch/nn/
D_reduction.py27 # In order to support previous versions, accept boolean size_average and reduce
34 reduce: Optional[bool],
37 warning = "size_average and reduce args will be deprecated, please use reduction='{}' instead."
41 if reduce is None:
42 reduce = True
44 if size_average and reduce:
46 elif reduce:
57 reduce: Optional[bool],
60 return get_enum(legacy_get_string(size_average, reduce, emit_warning))
/external/tensorflow/tensorflow/compiler/xla/mlir_hlo/tests/Dialect/mhlo/
Dmhlo_reduce_pretty_print.mlir11 // version of mhlo.reduce op.
13 // The test case is eligible for pretty-printing reduce-op.
16 // CHECK-NEXT: mhlo.reduce(%arg0 init: %arg1) applies mhlo.add across dimensions = [1] : (tenso…
19 %0 = "mhlo.reduce"(%arg0, %arg1) ({
28 // The test case is not eligible for pretty-printing reduce-op. The location of
29 // reduce-op is different.
32 // CHECK-NEXT: mhlo.reduce(%arg0 init: %arg1)
41 %0 = "mhlo.reduce"(%arg0, %arg1) ({
50 // The test case is not eligible for pretty-printing reduce-op. The location of
57 %0 = "mhlo.reduce"(%arg0, %arg1) ({
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