| /external/mesa3d/src/compiler/glsl/ |
| ast_expr.cpp | 29 static const char *const operators[] = { local
75 assert((unsigned int)op < sizeof(operators) / sizeof(operators[0]));
77 return operators[op];
|
| /external/tensorflow/tensorflow/contrib/lite/toco/tflite/ |
| export_test.cc | 31 // conversions multiple times, and the conversion of operators is tested by
39 input_model_.operators.emplace_back(op);
41 input_model_.operators.emplace_back(new AddOperator);
45 input_model_.operators.emplace_back(op);
49 input_model_.operators.emplace_back(new SubOperator);
67 details::OperatorsMap operators; local
68 details::LoadOperatorsMap(input_model_, &operators);
69 EXPECT_EQ(0, operators[details::OperatorKey(OperatorType::kAdd, "")]);
70 EXPECT_EQ(1, operators[details::OperatorKey(OperatorType::kConv, "")]);
71 EXPECT_EQ(2, operators[details::OperatorKey(OperatorType::kSub, "")])
98 auto operators = (*model->subgraphs())[0]->operators(); local
[all...] |
| /external/jsilver/src/com/google/clearsilver/jsilver/functions/bundles/ |
| CoreOperators.java | 20 import com.google.clearsilver.jsilver.functions.operators.AddFunction;
21 import com.google.clearsilver.jsilver.functions.operators.AndFunction;
22 import com.google.clearsilver.jsilver.functions.operators.DivideFunction;
23 import com.google.clearsilver.jsilver.functions.operators.EqualFunction;
24 import com.google.clearsilver.jsilver.functions.operators.ExistsFunction;
25 import com.google.clearsilver.jsilver.functions.operators.GreaterFunction;
26 import com.google.clearsilver.jsilver.functions.operators.GreaterOrEqualFunction;
27 import com.google.clearsilver.jsilver.functions.operators.LessFunction;
28 import com.google.clearsilver.jsilver.functions.operators.LessOrEqualFunction;
29 import com.google.clearsilver.jsilver.functions.operators.ModuloFunction
[all...] |
| /external/python/cpython2/Lib/plat-irix5/ |
| panelparser.py | 13 operators = '()\'' variable
14 separators = operators + whitespace + ';' + '"'
38 elif c in operators:
|
| /external/python/cpython2/Lib/plat-irix6/ |
| panelparser.py | 13 operators = '()\'' variable
14 separators = operators + whitespace + ';' + '"'
38 elif c in operators:
|
| /external/tensorflow/tensorflow/python/ops/linalg/ |
| linear_operator_composition.py | 37 This operator composes one or more linear operators `[op1,...,opJ]`,
53 the defining operators' methods.
56 # Create a 2 x 2 linear operator composed of two 2 x 2 operators.
75 # Create a [2, 3] batch of 4 x 5 linear operators.
79 # Create a [2, 3] batch of 5 x 6 linear operators.
83 # Compose to create a [2, 3] batch of 4 x 6 operators.
95 the sum of the individual operators' operations.
114 operators,
122 `LinearOperatorComposition` is initialized with a list of operators
128 operators: Iterable of `LinearOperator` objects, each wit
189 def operators(self): member in class:LinearOperatorComposition
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| resolve_tensorflow_matmul.cc | 28 auto matmul_it = model->operators.begin() + op_index;
49 model->operators.emplace(matmul_it, transpose_op);
52 matmul_it = model->operators.begin();
53 for (; matmul_it != model->operators.end(); ++matmul_it) {
64 auto previous_op_it = model->operators.begin();
66 for (; previous_op_it != model->operators.end(); ++previous_op_it) {
84 model->operators.emplace(matmul_it, fc_op) + 1;
87 matmul_it = model->operators.begin();
88 for (; matmul_it != model->operators.end(); ++matmul_it) {
116 model->operators.erase(previous_op_it)
[all...] |
| identify_l2_pool.cc | 31 auto it = model->operators.begin();
32 for (; it != model->operators.end(); ++it) {
42 const auto sqrt_it = model->operators.begin() + op_index;
90 model->operators.emplace(sqrt_it, l2pool_op);
98 // Erase three operators being replaced.
99 model->operators.erase(FindOperator(model, square_op));
100 model->operators.erase(FindOperator(model, avpool_op));
101 model->operators.erase(FindOperator(model, sqrt_op));
|
| unroll_batch_matmul.cc | 40 auto batch_op_it = model->operators.begin() + op_index;
65 const auto matmul_op_it = model->operators.emplace(batch_op_it, matmul_op);
68 model->operators.erase(batch_op_it);
97 tail_it = model->operators.emplace(tail_it, slice_a_op) + 1;
110 tail_it = model->operators.emplace(tail_it, slice_a_reshape_op) + 1;
124 tail_it = model->operators.emplace(tail_it, slice_b_op) + 1;
137 tail_it = model->operators.emplace(tail_it, slice_b_reshape_op) + 1;
146 tail_it = model->operators.emplace(tail_it, matmul_op) + 1;
157 model->operators.emplace(tail_it, stack_op);
160 batch_op_it = model->operators.begin()
[all...] |
| convert_trivial_addn_to_add.cc | 24 auto addn_it = model->operators.begin() + op_index;
44 const auto add_it = model->operators.emplace(addn_it, add_op);
47 model->operators.erase(addn_it);
|
| graph_transformations.cc | 39 LOG(INFO) << label << ": " << model.operators.size() << " operators, "
67 for (const auto& op : model->operators) {
97 // Erase operators that do not produce a useful output array.
98 for (auto it = model->operators.begin(); it != model->operators.end();) {
107 it = model->operators.erase(it);
134 if (model->operators.empty()) {
138 int op_index = increment == 1 ? 0 : model->operators.size() - 1;
153 << model->operators.size() - 1
[all...] |
| resolve_tensorflow_merge.cc | 28 const auto merge_it = model->operators.begin() + op_index;
48 for (const auto& other_op : model->operators) {
59 model->operators.erase(merge_it);
|
| remove_tensorflow_assert.cc | 27 const auto assert_it = model->operators.begin() + op_index;
35 for (const auto& op : model->operators) {
|
| remove_tensorflow_identity.cc | 29 const auto passthru_it = model->operators.begin() + op_index;
|
| remove_trivial_concatenation.cc | 29 const auto concat_it = model->operators.begin() + op_index;
|
| resolve_tensorflow_tile.cc | 37 auto tile_it = model->operators.begin();
38 for (; tile_it != model->operators.end(); ++tile_it) {
43 CHECK(tile_it != model->operators.end());
45 model->operators.erase(tile_it);
57 const auto binary_it = model->operators.begin() + op_index;
|
| identify_l2_normalization.cc | 32 auto it = model->operators.begin();
33 for (; it != model->operators.end(); ++it) {
43 const auto div_it = model->operators.begin() + op_index;
147 model->operators.emplace(div_it, l2norm_op);
152 model->operators.erase(FindOperator(model, square_op));
157 model->operators.erase(FindOperator(model, sum_op));
161 model->operators.erase(FindOperator(model, add_op));
164 model->operators.erase(FindOperator(model, sqrt_or_rsqrt_op));
166 model->operators.erase(FindOperator(model, div_or_mul_op));
|
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava2/rxjava/2.0.6/ |
| rxjava-2.0.6.jar | |
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava/1.2.3/ |
| rxjava-1.2.3.jar | |
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava/1.1.4/ |
| rxjava-1.1.4.jar | |
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava/1.1.5/ |
| rxjava-1.1.5.jar | |
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava/1.1.6/ |
| rxjava-1.1.6.jar | |
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava/1.1.3/ |
| rxjava-1.1.3.jar | |
| /external/tensorflow/tensorflow/contrib/linalg/python/ops/ |
| linear_operator_addition.py | 37 def add_operators(operators,
41 """Efficiently add one or more linear operators.
43 Given operators `[A1, A2,...]`, this `Op` returns a possibly shorter list of
44 operators `[B1, B2,...]` such that
48 The operators `Bk` result by adding some of the `Ak`, as allowed by
51 Example of efficient adding of diagonal operators.
80 operators: Iterable of `LinearOperator` objects with same `dtype`, domain
94 ValueError: If `operators` argument is empty.
102 check_ops.assert_proper_iterable(operators)
103 operators = list(reversed(operators)
[all...] |
| /prebuilts/tools/common/m2/repository/io/reactivex/rxjava/1.1.0/ |
| rxjava-1.1.0.jar | |
