| /external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
| shape_partition.cc | 21 std::vector<int64> ShapePartitionAssigner::Run(int64 target_partition_count) {
24 std::vector<int64> outer_dims;
25 int64 outer_dim_size = 1;
29 const int64 dimension = shape_.layout().minor_to_major(i);
46 const int64 target_dim_partition_count = std::pow(
51 std::vector<int64> dimension_partition_counts(outer_dims.size());
52 for (int64 i = 0; i < outer_dims.size(); ++i) {
54 std::min(static_cast<int64>(shape_.dimensions(outer_dims[i])),
66 for (int64 i = 0; i < dimension_partition_counts.size(); ++i)
[all...] |
| parallel_task_assignment.h | 30 virtual int64 GetParallelTaskCount(HloInstruction* instruction) = 0;
40 ParallelTaskAssignment(const int64 max_parallelism,
46 int64 GetTargetParallelTaskCount(HloInstruction* instruction);
65 ParallelTaskAssigner(const int64 max_parallelism,
79 using HloToParallelTasks = std::unordered_map<const HloInstruction*, int64>;
95 int64 max_parallelism_;
|
| /prebuilts/go/darwin-x86/src/cmd/compile/internal/gc/ |
| logic_test.go | 9 values := [...]int64{-1 << 63, 1<<63 - 1, -4, -3, -2, -1, 0, 1, 2, 3, 4}
12 zero := func(x int64) int64 { return 0 }
13 id := func(x int64) int64 { return x }
14 or := func(x, y int64) int64 { return x | y }
15 and := func(x, y int64) int64 { return x & y }
16 y := func(x, y int64) int64 { return y
[all...] |
| /prebuilts/go/linux-x86/src/cmd/compile/internal/gc/ |
| logic_test.go | 9 values := [...]int64{-1 << 63, 1<<63 - 1, -4, -3, -2, -1, 0, 1, 2, 3, 4}
12 zero := func(x int64) int64 { return 0 }
13 id := func(x int64) int64 { return x }
14 or := func(x, y int64) int64 { return x | y }
15 and := func(x, y int64) int64 { return x & y }
16 y := func(x, y int64) int64 { return y
[all...] |
| /prebuilts/go/darwin-x86/src/math/rand/ |
| race_test.go | 27 var seed int64
28 seed += int64(ExpFloat64())
29 seed += int64(Float32())
30 seed += int64(Float64())
31 seed += int64(Intn(Int()))
32 seed += int64(Int31n(Int31()))
33 seed += int64(Int63n(Int63()))
34 seed += int64(NormFloat64())
35 seed += int64(Uint32())
36 seed += int64(Uint64()
[all...] |
| /prebuilts/go/linux-x86/src/math/rand/ |
| race_test.go | 27 var seed int64
28 seed += int64(ExpFloat64())
29 seed += int64(Float32())
30 seed += int64(Float64())
31 seed += int64(Intn(Int()))
32 seed += int64(Int31n(Int31()))
33 seed += int64(Int63n(Int63()))
34 seed += int64(NormFloat64())
35 seed += int64(Uint32())
36 seed += int64(Uint64()
[all...] |
| /external/perf_data_converter/src/ |
| builder.h | 20 typedef int64_t int64; typedef in namespace:perftools::profiles
44 int64 StringId(const char *str);
50 const char *file, int64 start_line);
97 typedef std::tuple<int64, int64, int64, int64> Function;
101 int64 hash = std::get<0>(f);
110 std::unordered_map<string, int64> strings_;
111 std::unordered_map<Function, int64, FunctionHasher> functions_
[all...] |
| /external/stressapptest/src/ |
| finelock_queue.h | 35 FineLockPEQueue(uint64 queuesize, int64 pagesize);
60 bool valid_index(int64 index) {
85 int64 getA(int64 m);
86 int64 getC(int64 m);
91 int64 page_size_; // For calculating array index from offset.
103 int64 a_; // 'a' multiplicative value for progressing
105 int64 c_; // 'c' additive value for prgressing randomly
107 int64 modlength_; // 'm' mod value for linear congruentia
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| deep_conv2d.h | 46 virtual void GetFilterTransformMatrix(const int64 rows, const int64 cols,
49 virtual void GetInputTransformMatrix(const int64 rows, const int64 cols,
52 virtual void GetOutputTransformMatrix(const int64 rows, const int64 cols,
56 Shape(int64 r, int64 c) : rows(r), cols(c) {}
57 int64 rows;
58 int64 cols
[all...] |
| mirror_pad_op_gpu.cu.cc | 34 template struct functor::MirrorPad<GpuDevice, T, int64, 1>; \
35 template struct functor::MirrorPad<GpuDevice, T, int64, 2>; \
36 template struct functor::MirrorPad<GpuDevice, T, int64, 3>; \
37 template struct functor::MirrorPad<GpuDevice, T, int64, 4>; \
38 template struct functor::MirrorPad<GpuDevice, T, int64, 5>; \
44 template struct functor::MirrorPadGrad<GpuDevice, T, int64, 1>; \
45 template struct functor::MirrorPadGrad<GpuDevice, T, int64, 2>; \
46 template struct functor::MirrorPadGrad<GpuDevice, T, int64, 3>; \
47 template struct functor::MirrorPadGrad<GpuDevice, T, int64, 4>; \
48 template struct functor::MirrorPadGrad<GpuDevice, T, int64, 5>
[all...] |
| sparse_cross_op.cc | 42 virtual int64 FeatureCount(int64 batch) const = 0;
45 virtual InternalType Feature(int64 batch, int64 n) const = 0;
54 SparseTensorColumn(const Tensor& values, std::vector<int64> feature_counts,
55 std::vector<int64> feature_start_indices)
62 int64 FeatureCount(int64 batch) const override {
66 InternalType Feature(int64 batch, int64 n) const override
[all...] |
| pooling_ops_3d.h | 67 int64 out_plane;
68 int64 out_height;
69 int64 out_width;
71 int64 pad_planes;
72 int64 pad_cols;
73 int64 pad_rows;
|
| summary_interface.h | 37 virtual Status WriteTensor(int64 global_step, Tensor t, const string& tag,
40 virtual Status WriteScalar(int64 global_step, Tensor t,
43 virtual Status WriteHistogram(int64 global_step, Tensor t,
46 virtual Status WriteImage(int64 global_step, Tensor t, const string& tag,
49 virtual Status WriteAudio(int64 global_step, Tensor t, const string& tag,
52 virtual Status WriteGraph(int64 global_step,
|
| /frameworks/base/core/proto/android/os/ |
| kernelwake.proto | 42 optional int64 active_since = 6;
44 optional int64 total_time = 7;
46 optional int64 max_time = 8;
48 optional int64 last_change = 9;
50 optional int64 prevent_suspend_time = 10;
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/lib/utils/ |
| batch_features_test.cc | 69 auto sparse_float_feature_indices = AsTensor<int64>({0, 0, 1, 0});
71 auto sparse_float_feature_shape = AsTensor<int64>({2, 1});
82 auto sparse_float_feature_indices = AsTensor<int64>({0, 0, 1, 0}, {2, 2});
84 auto sparse_float_feature_shape = AsTensor<int64>({2, 1});
95 auto sparse_float_feature_indices = AsTensor<int64>({0, 0, 1, 0}, {2, 2});
97 auto sparse_float_feature_shape = AsTensor<int64>({2, 1}, {1, 2});
108 auto sparse_float_feature_indices = AsTensor<int64>({0, 0, 1, 0}, {2, 2});
110 auto sparse_float_feature_shape = AsTensor<int64>({2, 1, 9});
121 auto sparse_float_feature_indices = AsTensor<int64>({0, 0, 1, 0}, {2, 2});
123 auto sparse_float_feature_shape = AsTensor<int64>({8, 1})
[all...] |
| /external/tensorflow/tensorflow/core/framework/ |
| common_shape_fns.h | 74 Status GetWindowedOutputSize(int64 input_size, int64 filter_size, int64 stride,
75 Padding padding_type, int64* output_size,
76 int64* padding_size);
99 Status GetWindowedOutputSizeV2(int64 input_size, int64 filter_size,
100 int64 dilation_rate, int64 stride,
101 Padding padding_type, int64* output_size
[all...] |
| log_memory.h | 62 static void RecordStep(int64 step_id, const string& handle);
70 static void RecordTensorAllocation(const string& kernel_name, int64 step_id,
79 static void RecordTensorDeallocation(int64 allocation_id,
83 static void RecordTensorOutput(const string& kernel_name, int64 step_id,
95 static void RecordRawAllocation(const string& operation, int64 step_id,
104 static void RecordRawDeallocation(const string& operation, int64 step_id,
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| index_ops_kernel_argmax_float_1d.cc | 32 int64 input_size = *static_cast<int64*>(data[1]);
38 int64* out_t = static_cast<int64*>(out);
39 TTypes<int64, 0>::Tensor out_eig(out_t, out_eig_sizes);
41 out_eig = in_eig.argmax(0).cast<int64>();
|
| /external/tensorflow/tensorflow/compiler/xla/service/ |
| hlo_profile_printer_data.proto | 39 int64 profile_index = 8;
48 int64 profile_index = 2;
59 int64 profile_counters_size = 2;
|
| /external/tensorflow/tensorflow/core/platform/cloud/ |
| gcs_throttle.h | 36 int64 token_rate = 100000; // Approximately 800 MBits/second bandwidth-only.
42 int64 bucket_size = 10000000; // 10 million tokens total
50 int64 tokens_per_request = 100;
56 int64 initial_tokens = 0;
112 inline int64 available_tokens() {
148 int64 available_tokens_ GUARDED_BY(mu_) = 0;
|
| /external/tensorflow/tensorflow/core/util/ |
| strided_slice_op.h | 50 gtl::InlinedVector<int64, 4>* begin, gtl::InlinedVector<int64, 4>* end,
51 gtl::InlinedVector<int64, 4>* strides);
60 bool* slice_dim0, gtl::InlinedVector<int64, 4>* begin,
61 gtl::InlinedVector<int64, 4>* end, gtl::InlinedVector<int64, 4>* strides);
|
| /external/libvpx/libvpx/third_party/libwebm/mkvmuxer/ |
| mkvwriter.h | 27 virtual int64 Position() const;
28 virtual int32 Position(int64 position);
31 virtual void ElementStartNotify(uint64 element_id, int64 position);
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/common/stats/ |
| feature-split-candidate.h | 35 FeatureSplitCandidate(const int64 fc_slot_id,
44 int64 feature_column_slot_id;
53 static constexpr int64 kInvalidFeatureColumnSlot = -1;
|
| /external/tensorflow/tensorflow/core/distributed_runtime/ |
| recent_request_ids.h | 57 Status TrackUnique(int64 request_id, const string& method_name,
66 std::vector<int64> circular_buffer_ GUARDED_BY(mu_);
67 gtl::FlatSet<int64> set_ GUARDED_BY(mu_);
|
| /prebuilts/go/darwin-x86/test/fixedbugs/ |
| bug366.go | 11 func five(x int64) {
19 five(int64(5 / (5 / 3)))
22 five(int64(byte(5) / (byte(5) / byte(3))))
26 five(int64(a / (a / b)))
31 five(int64(x[2] / (x[2] / x[1])))
36 five(int64(y[1] / (y[1] / y[0])))
|
