| /external/tensorflow/tensorflow/lite/tools/optimize/ |
| D | quantization_wrapper_utils_custom_test.cc | 60 model->subgraphs[0]->tensors.push_back(std::move(tensor)); in TEST()
74 EXPECT_EQ(model->subgraphs[0]->tensors.size(), 33); in TEST()
79 EXPECT_EQ(model->subgraphs[0]->tensors[0]->name, "lstm_tensor0"); in TEST()
80 EXPECT_EQ(model->subgraphs[0]->tensors[21]->name, "intermediate_0_0"); in TEST()
81 EXPECT_EQ(model->subgraphs[0]->tensors[22]->name, "intermediate_0_1"); in TEST()
82 EXPECT_EQ(model->subgraphs[0]->tensors[23]->name, "intermediate_0_2"); in TEST()
83 EXPECT_EQ(model->subgraphs[0]->tensors[24]->name, "intermediate_0_3"); in TEST()
84 EXPECT_EQ(model->subgraphs[0]->tensors[25]->name, "intermediate_0_4"); in TEST()
85 EXPECT_EQ(model->subgraphs[0]->tensors[26]->name, "intermediate_0_5"); in TEST()
86 EXPECT_EQ(model->subgraphs[0]->tensors[27]->name, "intermediate_0_6"); in TEST()
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| D | quantize_model_test.cc | 98 ASSERT_EQ(graph->tensors.size(), expected_graph->tensors.size()); in ExpectSameModels()
99 for (size_t i = 0; i < graph->tensors.size(); i++) { in ExpectSameModels()
100 const auto tensor = graph->tensors[i].get(); in ExpectSameModels()
101 const auto expected_tensor = expected_graph->tensors[i].get(); in ExpectSameModels()
171 ASSERT_EQ(quantized_graph->tensors.size(), float_graph->tensors()->size()); in TEST_P()
172 for (size_t i = 0; i < quantized_graph->tensors.size(); i++) { in TEST_P()
173 const auto quant_tensor = quantized_graph->tensors[i].get(); in TEST_P()
174 const auto float_tensor = float_graph->tensors()->Get(i); in TEST_P()
194 ASSERT_EQ(quantized_graph->tensors.size(), float_graph->tensors()->size()); in TEST_P()
195 for (size_t i = 0; i < quantized_graph->tensors.size(); i++) { in TEST_P()
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| D | quantization_wrapper_utils_test.cc | 61 model->subgraphs[0]->tensors.push_back(std::move(tensor)); in TEST()
75 EXPECT_EQ(model->subgraphs[0]->tensors.size(), 26); in TEST()
80 EXPECT_EQ(model->subgraphs[0]->tensors[0]->name, "lstm_tensor0"); in TEST()
81 EXPECT_EQ(model->subgraphs[0]->tensors[21]->name, "intermediate_0_0"); in TEST()
82 EXPECT_EQ(model->subgraphs[0]->tensors[22]->name, "intermediate_0_1"); in TEST()
83 EXPECT_EQ(model->subgraphs[0]->tensors[23]->name, "intermediate_0_2"); in TEST()
84 EXPECT_EQ(model->subgraphs[0]->tensors[24]->name, "intermediate_0_3"); in TEST()
85 EXPECT_EQ(model->subgraphs[0]->tensors[25]->name, "intermediate_0_4"); in TEST()
102 EXPECT_EQ(model->subgraphs[0]->tensors.size(), 26); in TEST()
107 EXPECT_EQ(model->subgraphs[0]->tensors[0]->name, "lstm_tensor0"); in TEST()
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| /external/tensorflow/tensorflow/core/common_runtime/ |
| D | all_to_all_test.cc | 38 std::vector<Tensor> tensors = { in TEST_F() local
45 SchedClosure([this, &tensors, i, &counter]() { in TEST_F()
48 tensors[i].shape()); in TEST_F()
53 &tensors[i], &tensors[i])); in TEST_F()
58 test::ExpectTensorEqual<double>(tensors[0], in TEST_F()
60 test::ExpectTensorEqual<double>(tensors[1], in TEST_F()
62 test::ExpectTensorEqual<double>(tensors[2], in TEST_F()
69 std::vector<Tensor> tensors = { in TEST_F() local
77 SchedClosure([this, &tensors, &device_ranks, i, &counter]() { in TEST_F()
80 tensors[i].shape(), device_ranks); in TEST_F()
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| /external/tensorflow/tensorflow/python/autograph/utils/ |
| D | tensors_test.py | 17 from tensorflow.python.autograph.utils import tensors
39 self.assertTrue(tensors.is_tensor_array(self._simple_tensor_array()))
40 self.assertFalse(tensors.is_tensor_array(self._simple_tensor_list()))
41 self.assertFalse(tensors.is_tensor_array(constant_op.constant(1)))
42 self.assertFalse(tensors.is_tensor_array(self._simple_list_of_tensors()))
43 self.assertFalse(tensors.is_tensor_array(None))
46 self.assertFalse(tensors.is_tensor_list(self._simple_tensor_array()))
47 self.assertTrue(tensors.is_tensor_list(self._simple_tensor_list()))
48 self.assertFalse(tensors.is_tensor_list(constant_op.constant(1)))
49 self.assertFalse(tensors.is_tensor_list(self._simple_list_of_tensors()))
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nccl_ops.py | 29 def all_sum(tensors): argument
43 return _apply_all_reduce('sum', tensors)
76 def all_prod(tensors): argument
90 return _apply_all_reduce('prod', tensors)
93 def all_min(tensors): argument
107 return _apply_all_reduce('min', tensors)
110 def all_max(tensors): argument
124 return _apply_all_reduce('max', tensors)
127 def reduce_sum(tensors): argument
143 return _apply_reduce('sum', tensors)
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| D | nccl_ops_test.py | 29 def _DeviceTensors(tensors, devices): argument
31 for t, d in zip(tensors, devices):
37 def _NcclAllReduce(nccl_fun, tensors, devices): argument
38 return nccl_fun(_DeviceTensors(tensors, devices))
41 def _NcclReduce(nccl_fun, tensors, devices): argument
44 return [nccl_fun(_DeviceTensors(tensors, devices))]
47 def _NcclBroadcast(tensors, devices): argument
50 tensor = array_ops.identity(tensors[0])
80 tensors = []
82 tensors.append(random.astype(dtype))
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| /external/tensorflow/tensorflow/compiler/mlir/lite/quantization/lite/ |
| D | quantize_model_test.cc | 189 return expected_graph.tensors[expected_op->inputs[idx]].get(); in FindMatchingExpectedTensor()
206 const auto& tensor = graph->tensors[op->inputs[idx]]; in ExpectSameModels()
236 auto* input = subgraph->tensors[subgraph->inputs[0]].get(); in QuantizeConvModelTest()
237 auto* output = subgraph->tensors[subgraph->outputs[0]].get(); in QuantizeConvModelTest()
295 for (const auto& tensor : subgraph->tensors) { in TEST_P()
356 EXPECT_EQ(subgraph->tensors.size(), 5); in TEST_F()
358 EXPECT_EQ(subgraph->tensors[input_idx]->type, TensorType_INT8); in TEST_F()
359 EXPECT_EQ(subgraph->tensors[input_idx]->name, "input"); in TEST_F()
360 EXPECT_EQ(subgraph->tensors[input_idx]->quantization->scale.size(), 1); in TEST_F()
361 EXPECT_EQ(subgraph->tensors[input_idx]->quantization->zero_point.size(), 1); in TEST_F()
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| /external/ComputeLibrary/src/dynamic_fusion/sketch/gpu/ |
| D | GpuOperatorGroup.cpp | 36 …d::vector<DependencyGraph::TensorId> get_tensor_ids(const std::vector<const ITensorInfo *> tensors) in get_tensor_ids() argument
40 std::begin(tensors), std::end(tensors), in get_tensor_ids()
51 …r::Operator(OperatorId id, GpuOperatorType operator_type, const ArgumentPack<ITensorInfo> &tensors) in Operator() argument
52 : _id{ id }, _operator_type{ operator_type }, _tensors{ tensors } in Operator()
66 ArgumentPack<ITensorInfo> Operator::tensors() const in tensors() function in arm_compute::experimental::dynamic_fusion::Operator
73 const auto src_tensor_ids = get_tensor_ids(op.tensors().get_const_src_tensors()); in try_add_operator()
74 const auto dst_tensor_ids = get_tensor_ids(op.tensors().get_const_dst_tensors()); in try_add_operator()
96 …if(op.operator_type() != GpuOperatorType::Unfusable && op.tensors().get_const_dst_tensors().size()… in try_add_operator()
103 const auto root_dst_tensors = get_root_operator()->tensors().get_const_dst_tensors(); in try_add_operator()
106 const auto dst_tensors = op.tensors().get_const_dst_tensors(); in try_add_operator()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | tensor_list_util.cc | 51 if (a.tensors().size() != b.tensors().size()) { in TensorListBinaryAdd()
54 a.tensors().size(), " and the other is ", b.tensors().size()); in TensorListBinaryAdd()
56 out->tensors().reserve(a.tensors().size()); in TensorListBinaryAdd()
57 for (int i = 0; i < a.tensors().size(); ++i) { in TensorListBinaryAdd()
58 const Tensor& a_tensor = a.tensors()[i]; in TensorListBinaryAdd()
59 const Tensor& b_tensor = b.tensors()[i]; in TensorListBinaryAdd()
62 out->tensors().push_back(out_tensor); in TensorListBinaryAdd()
74 y->tensors().reserve(x.tensors().size()); in TensorListZerosLike()
75 for (const Tensor& t : x.tensors()) { in TensorListZerosLike()
78 y->tensors().emplace_back(out_tensor); in TensorListZerosLike()
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| D | map_kernels.h | 103 result->scalar<int32>()() = map->tensors().size(); in Compute()
118 ctx, map->tensors().find(key) != map->tensors().end(), in Compute()
123 ctx->set_output(0, map->tensors().find(key)->second); in Compute()
155 ctx, map->tensors().find(key) != map->tensors().end(), in Compute()
163 output_map->tensors().erase(key); in Compute()
178 result->scalar<bool>()() = map->tensors().find(key) != map->tensors().end(); in Compute()
197 auto it = map->tensors().begin(); in Compute()
199 output_shape.InsertDim(0, map->tensors().size()); in Compute()
204 size_t sz = map->tensors().size(); in Compute()
206 while (it != map->tensors().end() && i < sz) { in Compute()
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| /external/armnn/src/armnnTfLiteParser/test/ |
| D | GetInputsOutputs.cpp | 23 "tensors": [ in GetInputsOutputsMainFixture()
73 "tensors": [ in GetInputsOutputsMainFixture()
156 TfLiteParserImpl::TensorRawPtrVector tensors = TfLiteParserImpl::GetInputs(model, 0, 0); variable
157 CHECK_EQ(0, tensors.size());
164 TfLiteParserImpl::TensorRawPtrVector tensors = TfLiteParserImpl::GetOutputs(model, 0, 0); variable
165 CHECK_EQ(0, tensors.size());
172 TfLiteParserImpl::TensorRawPtrVector tensors = TfLiteParserImpl::GetInputs(model, 0, 0); variable
173 CHECK_EQ(1, tensors.size());
174 CheckTensors(tensors[0], 4, { 1, 2, 2, 1 }, tflite::TensorType::TensorType_UINT8, 1,
182 TfLiteParserImpl::TensorRawPtrVector tensors = TfLiteParserImpl::GetOutputs(model, 0, 0); variable
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| /external/armnn/delegate/test/ |
| D | UnidirectionalSequenceLstmTestHelper.hpp | 108 std::vector<flatbuffers::Offset<Tensor>> tensors; in CreateUnidirectionalSequenceLstmTfLiteModel() local
126 tensors.push_back(CreateTensor(flatBufferBuilder, in CreateUnidirectionalSequenceLstmTfLiteModel()
132 operatorInputs.push_back(tensors.size() - 1); in CreateUnidirectionalSequenceLstmTfLiteModel()
141 tensors.push_back(CreateTensor(flatBufferBuilder, in CreateUnidirectionalSequenceLstmTfLiteModel()
148 operatorInputs.push_back(tensors.size() - 1); in CreateUnidirectionalSequenceLstmTfLiteModel()
160 tensors.push_back(CreateTensor(flatBufferBuilder, in CreateUnidirectionalSequenceLstmTfLiteModel()
167 operatorInputs.push_back(tensors.size() - 1); in CreateUnidirectionalSequenceLstmTfLiteModel()
174 tensors.push_back(CreateTensor(flatBufferBuilder, in CreateUnidirectionalSequenceLstmTfLiteModel()
181 operatorInputs.push_back(tensors.size() - 1); in CreateUnidirectionalSequenceLstmTfLiteModel()
188 tensors.push_back(CreateTensor(flatBufferBuilder, in CreateUnidirectionalSequenceLstmTfLiteModel()
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| /external/ComputeLibrary/src/cpu/operators/ |
| D | CpuDepthwiseConv2d.cpp | 147 void CpuDepthwiseConv2d::CpuDepthwiseConv2dOptimizedInternal::run(ITensorPack &tensors) in run() argument
149 ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided"); in run()
150 prepare(tensors); in run()
152 auto bias = tensors.get_const_tensor(TensorType::ACL_SRC_2); in run()
153 auto dst = tensors.get_tensor(TensorType::ACL_DST_0); in run()
154 auto workspace = tensors.get_tensor(TensorType::ACL_INT_3); in run()
155 auto packed_weights = tensors.get_tensor(TensorType::ACL_INT_4); in run()
161 auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0); in run()
162 auto src_perm = tensors.get_tensor(TensorType::ACL_INT_0); in run()
171 auto src_perm = tensors.get_tensor(TensorType::ACL_INT_0); in run()
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| /external/armnn/src/armnnOnnxParser/test/ |
| D | GetInputsOutputs.cpp | 71 std::vector<std::string> tensors = armnnOnnxParser::OnnxParserImpl::GetInputs(model); variable
72 CHECK_EQ(1, tensors.size());
73 CHECK_EQ("Input", tensors[0]);
80 std::vector<std::string> tensors = armnnOnnxParser::OnnxParserImpl::GetOutputs(model); variable
81 CHECK_EQ(1, tensors.size());
82 CHECK_EQ("Output", tensors[0]);
142 std::vector<std::string> tensors = armnnOnnxParser::OnnxParserImpl::GetInputs(model); variable
143 CHECK_EQ(0, tensors.size());
246 std::vector<std::string> tensors = armnnOnnxParser::OnnxParserImpl::GetInputs(model); variable
247 CHECK_EQ(2, tensors.size());
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| /external/tensorflow/tensorflow/lite/tools/versioning/ |
| D | op_signature.cc | 39 return subgraph->tensors()->Get(op->inputs()->Get(idx))->shape()->size(); in GetNumDims()
43 const flatbuffers::Vector<int32_t>* tensors, const SubGraph* subgraph, in GetOpSignatureTensorSpecs() argument
48 for (int32_t i = 0; i < tensors->Length(); ++i) { in GetOpSignatureTensorSpecs()
49 int32_t tensor_no = tensors->Get(i); in GetOpSignatureTensorSpecs()
53 if (subgraph->tensors() && tensor_no < subgraph->tensors()->Length()) { in GetOpSignatureTensorSpecs()
54 auto* fb_tensor = subgraph->tensors()->Get(tensor_no); in GetOpSignatureTensorSpecs()
66 subgraph->tensors()->Get(tensor_no)->shape(); in GetOpSignatureTensorSpecs()
73 subgraph->tensors()->Get(tensor_no)->shape_signature(); in GetOpSignatureTensorSpecs()
91 TfLiteIntArray* tensors, const TfLiteContext* context, in GetOpSignatureTensorSpecs() argument
95 for (int32_t i = 0; i < tensors->size; ++i) { in GetOpSignatureTensorSpecs()
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| /external/tensorflow/tensorflow/lite/delegates/xnnpack/ |
| D | transpose_conv_tester.cc | 128 std::vector<flatbuffers::Offset<Tensor>> tensors; in CreateTfLiteModel() local
143 const int tensor_index_output_shape = tensors.size(); in CreateTfLiteModel()
144 tensors.emplace_back( in CreateTfLiteModel()
167 const int tensor_index_float16_filter = tensors.size(); in CreateTfLiteModel()
168 tensors.emplace_back(CreateTensorDirect(builder, &filter_shape, in CreateTfLiteModel()
184 tensor_index_float16_bias = tensors.size(); in CreateTfLiteModel()
185 tensors.emplace_back(CreateTensorDirect(builder, &bias_shape, in CreateTfLiteModel()
190 const int tensor_index_filter = tensors.size(); in CreateTfLiteModel()
191 tensors.emplace_back(CreateTensorDirect( in CreateTfLiteModel()
201 assert(tensor_index_filter + 1 == tensors.size()); in CreateTfLiteModel()
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| D | xnnpack_delegate.cc | 294 std::vector<int> tensors(context->tensors_size, -1); in Create() local
331 tensors[t] = t; in Create()
339 tensors[t] = t; in Create()
347 tensors[t] = t; in Create()
360 tensors[t] = t; in Create()
367 tensors[t] = t; in Create()
372 tensors.erase(std::remove_if(tensors.begin(), tensors.end(), in Create()
374 tensors.end()); in Create()
375 std::sort(tensors.begin(), tensors.end()); in Create()
378 std::vector<uint32_t> xnnpack_tensors(tensors.back() + 1); in Create()
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| /external/libtextclassifier/native/utils/tflite/ |
| D | token_encoder.cc | 61 &context->tensors[node->outputs->data[kOutputPosition]], context)); in ResizeOutputTensors()
69 &context->tensors[node->outputs->data[kOutputAttr + i]], context)); in ResizeOutputTensors()
77 context->tensors[node->inputs->data[kInputNumTokens]]; in Prepare()
82 context->tensors[node->outputs->data[kOutputLengths]]; in Prepare()
84 context->tensors[node->outputs->data[kOutputPosition]]; in Prepare()
96 TfLiteTensor& input = context->tensors[node->inputs->data[kInputAttr + i]]; in Prepare()
98 context->tensors[node->outputs->data[kOutputAttr + i]]; in Prepare()
103 context->tensors[node->inputs->data[kInputMaxLength]]; in Prepare()
111 context->tensors[node->outputs->data[kOutputAttr + i]]; in Prepare()
121 context->tensors[node->inputs->data[kInputNumTokens]]; in Eval()
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| D | text_encoder3s.cc | 63 context->tensors[node->outputs->data[kOutputEncodedInd]]; in ResizeOutputTensors()
70 context->tensors[node->outputs->data[kOutputPositionInd]]; in ResizeOutputTensors()
80 context->tensors[node->outputs->data[kOutputAttrInd + i]]; in ResizeOutputTensors()
93 context->tensors[node->inputs->data[kInputTextInd]]; in Prepare()
98 context->tensors[node->outputs->data[kOutputLengthsInd]]; in Prepare()
101 context->tensors[node->outputs->data[kOutputEncodedInd]]; in Prepare()
103 context->tensors[node->outputs->data[kOutputPositionInd]]; in Prepare()
120 context->tensors[node->inputs->data[kInputAttrInd + i]]; in Prepare()
122 context->tensors[node->outputs->data[kOutputAttrInd + i]]; in Prepare()
127 context->tensors[node->inputs->data[kMaxLengthInd]]; in Prepare()
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| D | text_encoder.cc | 142 &context->tensors[node->outputs->data[kOutputEncoded]], in ResizeOutputTensors()
149 &context->tensors[node->outputs->data[kOutputPosition]], context)); in ResizeOutputTensors()
157 &context->tensors[node->outputs->data[kOutputAttr + i]], context)); in ResizeOutputTensors()
165 context->tensors[node->inputs->data[kInputTexts]]; in Prepare()
170 context->tensors[node->outputs->data[kOutputLengths]]; in Prepare()
172 context->tensors[node->outputs->data[kOutputEncoded]]; in Prepare()
174 context->tensors[node->outputs->data[kOutputPosition]]; in Prepare()
186 TfLiteTensor& input = context->tensors[node->inputs->data[kInputAttr + i]]; in Prepare()
188 context->tensors[node->outputs->data[kOutputAttr + i]]; in Prepare()
193 context->tensors[node->inputs->data[kInputMaxLength]]; in Prepare()
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| /external/tensorflow/tensorflow/python/data/util/ |
| D | sparse.py | 74 def deserialize_sparse_tensors(tensors, types, shapes, classes): argument
91 nest.flatten(tensors), nest.flatten(types), nest.flatten(shapes),
97 def get_classes(tensors): argument
108 return nest.pack_sequence_as(tensors, [
111 for tensor in nest.flatten(tensors)
115 def serialize_many_sparse_tensors(tensors): argument
125 ret = nest.pack_sequence_as(tensors, [
128 for tensor in nest.flatten(tensors)
133 def serialize_sparse_tensors(tensors): argument
143 ret = nest.pack_sequence_as(tensors, [
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| /external/tensorflow/tensorflow/core/grappler/optimizers/ |
| D | pin_to_host_optimizer_test.cc | 66 auto tensors = EvaluateNodes(item.graph, item.fetch); in TEST_F() local
67 EXPECT_EQ(tensors_expected.size(), tensors.size()); in TEST_F()
68 for (int i = 0; i < tensors.size(); ++i) { in TEST_F()
70 test::ExpectTensorEqual<int32>(tensors[i], tensors_expected[i]); in TEST_F()
72 test::ExpectTensorEqual<tstring>(tensors[i], tensors_expected[i]); in TEST_F()
106 auto tensors = EvaluateNodes(item.graph, item.fetch); in TEST_F() local
107 EXPECT_EQ(tensors_expected.size(), tensors.size()); in TEST_F()
108 for (int i = 0; i < tensors.size(); ++i) { in TEST_F()
109 test::ExpectTensorEqual<float>(tensors[i], tensors_expected[i]); in TEST_F()
146 auto tensors = EvaluateNodes(item.graph, item.fetch); in TEST_F() local
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SaveV2.pbtxt | 7 write the tensors.
13 shape {N}. The names of the tensors to be saved.
19 shape {N}. The slice specs of the tensors to be saved.
20 Empty strings indicate that they are non-partitioned tensors.
24 name: "tensors"
26 `N` tensors to save.
29 summary: "Saves tensors in V2 checkpoint format."
31 By default, saves the named tensors in full. If the caller wishes to save
32 specific slices of full tensors, "shape_and_slices" should be non-empty strings
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| /external/tensorflow/tensorflow/python/framework/ |
| D | subscribe.py | 26 def _recursive_apply(tensors, apply_fn): argument
44 tensors_type = type(tensors)
46 return apply_fn(tensors)
47 elif isinstance(tensors, variables.Variable):
48 return apply_fn(tensors.value())
49 elif isinstance(tensors, (list, tuple)):
50 tensors = [_recursive_apply(t, apply_fn) for t in tensors]
52 return list(tensors)
54 return tuple(tensors)
55 return tensors_type(*tensors) # collections.namedtuple
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