| /external/tensorflow/tensorflow/python/ops/linalg/ |
| D | linear_operator_composition.py | 114 operators, argument
148 check_ops.assert_proper_iterable(operators)
149 operators = list(operators)
150 if not operators:
152 "Expected a non-empty list of operators. Found: %s" % operators)
153 self._operators = operators
156 dtype = operators[0].dtype
157 for operator in operators:
159 name_type = (str((o.name, o.dtype)) for o in operators)
165 if all(operator.is_non_singular for operator in operators):
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| /external/jsilver/src/com/google/clearsilver/jsilver/functions/bundles/ |
| D | 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;
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| /external/tensorflow/tensorflow/contrib/lite/toco/tflite/ |
| D | export_test.cc | 39 input_model_.operators.emplace_back(op); in BuildTestModel()
41 input_model_.operators.emplace_back(new AddOperator); in BuildTestModel()
45 input_model_.operators.emplace_back(op); in BuildTestModel()
49 input_model_.operators.emplace_back(new SubOperator); in BuildTestModel()
67 details::OperatorsMap operators; in TEST_F() local
68 details::LoadOperatorsMap(input_model_, &operators); in TEST_F()
69 EXPECT_EQ(0, operators[details::OperatorKey(OperatorType::kAdd, "")]); in TEST_F()
70 EXPECT_EQ(1, operators[details::OperatorKey(OperatorType::kConv, "")]); in TEST_F()
71 EXPECT_EQ(2, operators[details::OperatorKey(OperatorType::kSub, "")]); in TEST_F()
72 EXPECT_EQ(3, operators[details::OperatorKey( in TEST_F()
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| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| D | resolve_tensorflow_matmul.cc | 28 auto matmul_it = model->operators.begin() + op_index; in Run()
49 model->operators.emplace(matmul_it, transpose_op); in Run()
52 matmul_it = model->operators.begin(); in Run()
53 for (; matmul_it != model->operators.end(); ++matmul_it) { in Run()
64 auto previous_op_it = model->operators.begin(); in Run()
66 for (; previous_op_it != model->operators.end(); ++previous_op_it) { in Run()
84 model->operators.emplace(matmul_it, fc_op) + 1; in Run()
87 matmul_it = model->operators.begin(); in Run()
88 for (; matmul_it != model->operators.end(); ++matmul_it) { in Run()
116 model->operators.erase(previous_op_it); in Run()
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| D | unroll_batch_matmul.cc | 40 auto batch_op_it = model->operators.begin() + op_index; in Run()
65 const auto matmul_op_it = model->operators.emplace(batch_op_it, matmul_op); in Run()
68 model->operators.erase(batch_op_it); in Run()
97 tail_it = model->operators.emplace(tail_it, slice_a_op) + 1; in Run()
110 tail_it = model->operators.emplace(tail_it, slice_a_reshape_op) + 1; in Run()
124 tail_it = model->operators.emplace(tail_it, slice_b_op) + 1; in Run()
137 tail_it = model->operators.emplace(tail_it, slice_b_reshape_op) + 1; in Run()
146 tail_it = model->operators.emplace(tail_it, matmul_op) + 1; in Run()
157 model->operators.emplace(tail_it, stack_op); in Run()
160 batch_op_it = model->operators.begin(); in Run()
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| D | graph_transformations.cc | 39 LOG(INFO) << label << ": " << model.operators.size() << " operators, " in PrintModelStats()
67 for (const auto& op : model->operators) { in DiscardUselessConnectedComponentsAndRNNBackEdges()
98 for (auto it = model->operators.begin(); it != model->operators.end();) { in DiscardUselessConnectedComponentsAndRNNBackEdges()
107 it = model->operators.erase(it); in DiscardUselessConnectedComponentsAndRNNBackEdges()
134 if (model->operators.empty()) { in GraphTransformationsPass()
138 int op_index = increment == 1 ? 0 : model->operators.size() - 1; in GraphTransformationsPass()
153 << model->operators.size() - 1; in GraphTransformationsPass()
158 << model->operators.size() - 1 << ": " << message; in GraphTransformationsPass()
163 if (model->operators.empty()) return true; in GraphTransformationsPass()
164 op_index = std::min<int>(op_index, model->operators.size() - 1); in GraphTransformationsPass()
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| D | identify_lstm.cc | 29 auto it = model->operators.begin(); in FindOperator()
30 for (; it != model->operators.end(); ++it) { in FindOperator()
214 auto op_it = model->operators.begin() + op_index; in Run()
325 model->operators.emplace(op_it, lstm_cell_op); in Run()
348 model->operators.erase(FindOperator(model, *final_output_mul)); in Run()
351 model->operators.erase(FindOperator(model, *state_output_tanh)); in Run()
352 model->operators.erase(FindOperator(model, *fc_output_sig)); in Run()
353 model->operators.erase(FindOperator(model, *state_combine_add)); in Run()
356 model->operators.erase(FindOperator(model, *state_forget_mul)); in Run()
357 model->operators.erase(FindOperator(model, *state_remember_mul)); in Run()
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| D | identify_l2_normalization.cc | 32 auto it = model->operators.begin(); in FindOperator()
33 for (; it != model->operators.end(); ++it) { in FindOperator()
43 const auto div_it = model->operators.begin() + op_index; in Run()
147 model->operators.emplace(div_it, l2norm_op); in Run()
152 model->operators.erase(FindOperator(model, square_op)); in Run()
157 model->operators.erase(FindOperator(model, sum_op)); in Run()
161 model->operators.erase(FindOperator(model, add_op)); in Run()
164 model->operators.erase(FindOperator(model, sqrt_or_rsqrt_op)); in Run()
166 model->operators.erase(FindOperator(model, div_or_mul_op)); in Run()
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| D | identify_l2_pool.cc | 31 auto it = model->operators.begin(); in FindOperator()
32 for (; it != model->operators.end(); ++it) { in FindOperator()
42 const auto sqrt_it = model->operators.begin() + op_index; in Run()
90 model->operators.emplace(sqrt_it, l2pool_op); in Run()
99 model->operators.erase(FindOperator(model, square_op)); in Run()
100 model->operators.erase(FindOperator(model, avpool_op)); in Run()
101 model->operators.erase(FindOperator(model, sqrt_op)); in Run()
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| D | identify_relu1.cc | 31 auto it = model->operators.begin(); in FindOperator()
32 for (; it != model->operators.end(); ++it) { in FindOperator()
61 const auto op_it = model->operators.begin() + op_index; in Run()
103 model->operators.emplace(op_it, relu1_op); in Run()
112 model->operators.erase(FindOperator(model, op_0)); in Run()
113 model->operators.erase(FindOperator(model, op_1)); in Run()
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| D | resolve_tensorflow_tile.cc | 37 auto tile_it = model->operators.begin(); in RemoveTileOperator()
38 for (; tile_it != model->operators.end(); ++tile_it) { in RemoveTileOperator()
43 CHECK(tile_it != model->operators.end()); in RemoveTileOperator()
45 model->operators.erase(tile_it); in RemoveTileOperator()
57 const auto binary_it = model->operators.begin() + op_index; in Run()
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| D | dequantize.cc | 45 for (auto it = model->operators.begin(); it != model->operators.end(); ++it) { in FindFirstOpWithInput()
52 return model->operators.end(); in FindFirstOpWithInput()
153 model->operators.emplace(FindFirstOpWithInput(model, array_name), in DequantizeArray()
163 for (const auto& op : model->operators) { in DequantizeArray()
173 for (const auto& op : model->operators) { in DequantizeArray()
189 const auto op_it = model->operators.begin() + op_index; in Run()
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| D | make_initial_dequantize_operator.cc | 66 for (auto& other_op : model->operators) { in AddDequantizeOperatorToInput()
79 model->operators.emplace(model->operators.begin(), image_input_op); in AddDequantizeOperatorToInput()
103 const auto it = model->operators.begin() + op_index; in Run()
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| D | resolve_tensorflow_switch.cc | 28 const auto switch_it = model->operators.begin() + op_index; in Run()
73 for (const auto& other_op : model->operators) { in Run()
89 for (const auto& other_op : model->operators) { in Run()
119 model->operators.erase(switch_it); in Run()
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| D | resolve_tensorflow_merge.cc | 28 const auto merge_it = model->operators.begin() + op_index; in Run()
48 for (const auto& other_op : model->operators) { in Run()
59 model->operators.erase(merge_it); in Run()
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| D | remove_trivial_passthrough.cc | 34 for (const auto& op : model->operators) { in RerouteEdges()
52 const auto passthru_it = model->operators.begin() + op_index; in RemoveTrivialPassthroughOp()
109 model->operators.erase(passthru_it); in RemoveTrivialPassthroughOp()
114 for (const auto& op : model->operators) { in RemoveTrivialPassthroughOp()
|
| /external/tensorflow/tensorflow/contrib/linalg/python/ops/ |
| D | linear_operator_addition.py | 37 def add_operators(operators, argument
102 check_ops.assert_proper_iterable(operators)
103 operators = list(reversed(operators))
104 if len(operators) < 1:
107 "Found: %s" % operators)
109 isinstance(op, linear_operator.LinearOperator) for op in operators):
112 "Found: %s" % operators)
113 _static_check_for_same_dimensions(operators)
114 _static_check_for_broadcastable_batch_shape(operators)
117 for operator in operators:
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| /external/tensorflow/tensorflow/contrib/lite/toco/ |
| D | import_tensorflow.cc | 391 model->operators.emplace_back(reorder); in ConvertConvOperator()
410 model->operators.emplace_back(conv); in ConvertConvOperator()
444 model->operators.emplace_back(reorder); in ConvertDepthwiseConvOperator()
463 model->operators.emplace_back(conv); in ConvertDepthwiseConvOperator()
478 model->operators.emplace_back(op); in ConvertDepthToSpaceOperator()
493 model->operators.emplace_back(op); in ConvertSpaceToDepthOperator()
509 model->operators.emplace_back(biasadd); in ConvertBiasAddOperator()
521 model->operators.emplace_back(relu); in ConvertReluOperator()
534 model->operators.emplace_back(op); in ConvertRelu6Operator()
547 model->operators.emplace_back(op); in ConvertLogisticOperator()
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| D | tooling_util.cc | 103 for (const auto& op : model.operators) { in CountOpsWithInput()
133 for (auto it = model.operators.begin(); it != model.operators.end(); ++it) { in FindOpWithOutput()
140 return model.operators.end(); in FindOpWithOutput()
145 for (auto it = model.operators.begin(); it != model.operators.end(); ++it) { in FindOpWithOutput()
152 return model.operators.end(); in FindOpWithOutput()
157 return it == model.operators.end() ? nullptr : it->get(); in GetOpWithOutput()
163 for (auto it = model.operators.begin(); it != model.operators.end(); ++it) { in FindOpWithInput()
170 return model.operators.end(); in FindOpWithInput()
175 for (auto it = model.operators.begin(); it != model.operators.end(); ++it) { in FindOpWithInput()
182 return model.operators.end(); in FindOpWithInput()
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| /external/mesa3d/src/compiler/glsl/ |
| D | ast_expr.cpp | 29 static const char *const operators[] = { in operator_string() local
75 assert((unsigned int)op < sizeof(operators) / sizeof(operators[0])); in operator_string()
77 return operators[op]; in operator_string()
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| /external/llvm/docs/tutorial/ |
| D | LangImpl06.rst | 15 doesn't have many useful operators (like division, logical negation, or
19 user-defined operators to the simple and beautiful Kaleidoscope
35 redefine existing operators: you can't programatically change the
36 grammar, introduce new operators, change precedence levels, etc. In this
38 user round out the set of operators that are supported.
40 The point of going into user-defined operators in a tutorial like this
46 the programmer to introduce new operators into the grammar: the grammar
49 The two specific features we'll add are programmable unary operators
50 (right now, Kaleidoscope has no unary operators at all) as well as
51 binary operators. An example of this is:
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| /external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
| D | linear_operator_composition_test.py | 128 operators = [
133 linalg.LinearOperatorComposition(operators)
199 operators = [
203 operator = linalg.LinearOperatorComposition(operators)
207 operators = [
211 operator = linalg.LinearOperatorComposition(operators)
222 operators = [
226 operator = linalg.LinearOperatorComposition(operators)
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| /external/tensorflow/tensorflow/docs_src/performance/xla/ |
| D | jit.md | 9 can fuse multiple operators (kernel fusion) into a small number of compiled
10 kernels. Fusing operators can reduce memory bandwidth requirements and improve
11 performance compared to executing operators one-at-a-time, as the TensorFlow
17 JIT-compiling operators placed on a CPU or GPU device, or by placing operators
18 on the `XLA_CPU` or `XLA_GPU` TensorFlow devices. Placing operators directly on
37 operators being greedily compiled into XLA computations. Each XLA computation
40 Subject to a few constraints, if there are two adjacent operators in the graph
63 JIT compilation can also be turned on manually for one or more operators. This
64 is done by tagging the operators to compile with the attribute
82 ### Placing operators on XLA devices
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| /external/tensorflow/tensorflow/contrib/lite/schema/ |
| D | schema_v0.fbs | 43 // target device is little-endian. In addition, all builtin operators assume
51 // A list of builtin operators. Builtin operators a slighlty faster than custom
52 // ones, but not by much. Moreover, while custom operators accept an opaque
82 // Options for the builtin operators.
239 // kept in order because operators carry an index into this
243 // All operators, in execution order.
244 operators:[Operator];
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| D | schema_v2.fbs | 18 // Version 2: Rename operators to conform to NN API.
49 // target device is little-endian. In addition, all builtin operators assume
57 // A list of builtin operators. Builtin operators a slighlty faster than custom
58 // ones, but not by much. Moreover, while custom operators accept an opaque
99 // Options for the builtin operators.
279 // All operators, in execution order.
280 operators:[Operator];
291 // kept in order because operators carry an index into this
|