/aosp_15_r20/external/executorch/backends/xnnpack/partition/config/ |
H A D | generic_node_configs.py | 58 node_output = list(node.users)[0] 60 node_output.op == "call_function" 61 and format_target_name(node_output.target.__name__) in self.fused_acts 63 quantized_deps.append(node_output) 64 fused_out_users = list(node_output.users.keys()) 66 node_output = fused_out_users[0] 68 if not is_quant(node_output): 72 quantized_deps.append(node_output)
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/aosp_15_r20/external/tensorflow/tensorflow/core/grappler/optimizers/data/ |
H A D | function_utils.cc | 30 : node_name(node_name), node_output(output), position(position) { in FunctionDefTensorDesc() 31 full_str = strings::StrCat(node_name, ":", node_output, ":", position); in FunctionDefTensorDesc() 55 node_output = string(capture.data(), capture.size()); in FunctionDefTensorDesc()
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H A D | function_utils_test.cc | 34 EXPECT_EQ(f.node_output, "y"); in TEST() 40 EXPECT_EQ(f2.node_output, ""); in TEST()
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H A D | function_utils.h | 52 string node_output; member
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/aosp_15_r20/external/tensorflow/tensorflow/lite/experimental/acceleration/mini_benchmark/ |
H A D | call.cc | 113 TfLiteTensor* node_output = context->tensors + node->outputs->data[i]; in ValidateAndResizeOutputs() local 120 context, context->ResizeTensor(context, node_output, new_dims_array)); in ValidateAndResizeOutputs() 121 node_output->type = subgraph_output->type; in ValidateAndResizeOutputs()
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/aosp_15_r20/external/pytorch/torch/utils/tensorboard/ |
H A D | _pytorch_graph.py | 170 for node_output, outputSize in zip(node.outputs, node.outputstensor_size): 172 self.nodes_io[node_output] = NodeBase( 173 node_output,
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/aosp_15_r20/external/executorch/devtools/inspector/tests/ |
H A D | inspector_utils_test.py | 242 node_output = ValueNode("output", [node_div]) 252 node_output,
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/aosp_15_r20/external/tensorflow/tensorflow/core/common_runtime/ |
H A D | step_stats_collector.cc | 163 NodeOutput* node_output = stats_->add_output(); in SetOutput() local 164 node_output->set_slot(slot); in SetOutput() 165 tensor->FillDescription(node_output->mutable_tensor_description()); in SetOutput()
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/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/onnx/ |
H A D | shape_type_inference.cpp | 2163 for (auto node_output : n->outputs()) { in ONNXShapeTypeInference() local 2166 ConstantValueMap::SetUseInferredType(node_output->debugName(), true); in ONNXShapeTypeInference() 2208 for (auto node_output : n->outputs()) { in ONNXShapeTypeInference() local 2209 UpdateShapeConstantIfReliable(node_output); in ONNXShapeTypeInference() 2496 void UpdateShapeConstantIfReliable(torch::jit::Value* node_output) { in UpdateShapeConstantIfReliable() argument 2497 if (ConstantValueMap::HasTypeReliable(node_output->debugName())) { in UpdateShapeConstantIfReliable() 2498 auto reliable = ConstantValueMap::GetTypeReliable(node_output->debugName()) in UpdateShapeConstantIfReliable() 2500 if (reliable && !ConstantValueMap::HasShape(node_output->debugName())) { in UpdateShapeConstantIfReliable() 2502 if (auto output_tensor_type = node_output->type()->cast<TensorType>()) { in UpdateShapeConstantIfReliable() 2505 UpdateShapeConstantValueMap(node_output, symbolic_sizes); in UpdateShapeConstantIfReliable()
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H A D | peephole.cpp | 606 for (auto node_output : n->outputs()) { in speculateOps() local 607 for (auto node_output_use : node_output->uses()) { in speculateOps()
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/aosp_15_r20/external/tensorflow/tensorflow/lite/delegates/hexagon/builders/ |
H A D | matmul_builder.cc | 51 OpBuilder::TensorID* node_output) { in AddFullyConnectedHelper() argument 138 *node_output = in AddFullyConnectedHelper()
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/aosp_15_r20/external/tensorflow/tensorflow/core/grappler/costs/ |
H A D | utils.cc | 456 for (const auto& node_output : node_stat.output()) { in GetStatsStringFromRunMetadata() local 459 const auto size = node_output.tensor_description() in GetStatsStringFromRunMetadata()
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/aosp_15_r20/external/pytorch/torch/csrc/jit/python/ |
H A D | init.cpp | 2186 Value* node_output = nullptr; in initJITBindings() local 2203 node_output = in initJITBindings() 2211 jit::tracer::setValueTrace(retval, node_output); in initJITBindings()
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/aosp_15_r20/external/pytorch/torch/csrc/jit/serialization/ |
H A D | python_print.cpp | 596 [&](Value* block_input, Value* node_output) { in printLoop() argument 597 assignValue(block_input, node_output); in printLoop()
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/aosp_15_r20/external/pytorch/torch/_inductor/ |
H A D | graph.py | 754 def register_users_of(self, node_output): argument 773 register(node_output)
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/aosp_15_r20/external/pytorch/torch/csrc/jit/frontend/ |
H A D | ir_emitter.cpp | 4226 Value* node_output = in emitForkExpr() local 4228 return std::make_shared<SimpleValue>(node_output); in emitForkExpr() 4262 Value* node_output = in emitAwaitableExpr() local 4264 return std::make_shared<SimpleValue>(node_output); in emitAwaitableExpr()
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