/external/pytorch/torch/csrc/jit/passes/ |
D | frozen_conv_folding.cpp | 120 auto fused_conv_w = b->owningGraph()->insertConstant(std::get<0>(out)); in FoldFrozenConvBatchnorm() 121 auto fused_conv_b = b->owningGraph()->insertConstant(std::get<1>(out)); in FoldFrozenConvBatchnorm() 273 conv->output(), b->owningGraph()->insertConstant(bias)); in FoldFrozenConvAddOrSub() 275 1, b->owningGraph()->insertConstant(add_or_sub_tensor)); in FoldFrozenConvAddOrSub() 281 auto fused_conv_b = b->owningGraph()->insertConstant(fuse_bias); in FoldFrozenConvAddOrSub() 344 conv->output(), b->owningGraph()->insertConstant(weight_tensor)); in FoldFrozenConvMulOrDiv() 345 mul_or_div->replaceInput(1, b->owningGraph()->insertConstant(mul_tensor)); in FoldFrozenConvMulOrDiv() 351 auto fused_conv_weight = b->owningGraph()->insertConstant(fuse_weight); in FoldFrozenConvMulOrDiv() 367 mul_or_div->replaceInput(0, b->owningGraph()->insertConstant(bias)); in FoldFrozenConvMulOrDiv() 369 1, b->owningGraph()->insertConstant(mul_tensor)); in FoldFrozenConvMulOrDiv() [all …]
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D | peephole.cpp | 157 auto const_sizes_val = node->owningGraph()->insertConstant(ival); in optimizeBlock() 171 auto output = node->owningGraph()->insertConstant( in optimizeBlock() 197 auto const_sizes_val = node->owningGraph()->insertConstant(ival); in optimizeBlock() 215 auto new_constant = node->owningGraph()->insertConstant(ival); in optimizeBlock() 231 auto new_constant = node->owningGraph()->insertConstant(ival); in optimizeBlock() 244 auto output = node->owningGraph()->insertConstant( in optimizeBlock() 260 auto output = node->owningGraph()->insertConstant(*ptt->device()); in optimizeBlock() 282 auto output = node->owningGraph()->insertConstant(device); in optimizeBlock() 297 node->owningGraph()->insertConstant(static_cast<int64_t>(*dim)); in optimizeBlock() 313 node->owningGraph()->insertConstant((*ptt->device()).is_cuda()); in optimizeBlock() [all …]
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D | frozen_concat_linear.cpp | 98 Value* cat_weight_value = graph_->insertConstant(std::move(cat_weight)); in mergeLinearLayers() 104 Value* cat_bias_value = graph_->insertConstant(std::move(cat_bias)); in mergeLinearLayers() 115 Value* neg1 = graph_->insertConstant(-1); in mergeLinearLayers() 116 Value* one = graph_->insertConstant(1); in mergeLinearLayers() 119 Value* slice_start_val = graph_->insertConstant(0); in mergeLinearLayers() 129 Value* slice_end_val = graph_->insertConstant(slice_end); in mergeLinearLayers()
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D | autocast.cpp | 172 graph->insertConstant(IValue(context.gpu_enabled)), in castTensorInputs() 173 graph->insertConstant(IValue(context.cpu_enabled))}); in castTensorInputs() 179 graph->insertConstant(IValue(context.gpu_enabled)), in castTensorInputs() 180 graph->insertConstant(IValue(context.cpu_enabled)), in castTensorInputs() 181 graph->insertConstant(IValue(context.gpu_scalar_type)), in castTensorInputs() 182 graph->insertConstant(IValue(context.cpu_scalar_type))}); in castTensorInputs() 247 Value* true_constant = graph->insertConstant(IValue(true)); in updateAutocastEnabledCheck()
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D | remove_exceptions.cpp | 20 Value* false_const = graph->insertConstant(IValue(false)); in EliminateExceptions() 21 Value* true_const = graph->insertConstant(IValue(true)); in EliminateExceptions()
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D | peephole_non_tensor.cpp | 86 node.replaceInput(1, node.owningGraph()->insertConstant(merged)); in trySimplifyAddOrSub() 117 output->replaceAllUsesWith(graph_->insertConstant(IValue())); in optimizeBlock() 182 auto output = node->owningGraph()->insertConstant( in optimizeBlock() 260 graph_->insertConstant(node->kind() == aten::eq)); in optimizeBlock()
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D | frozen_linear_transpose.cpp | 63 Value* weight_t = graph_->insertConstant(std::move(weight_t_tensor)); in replace_linear_with_matmul() 74 Value* bias_scale = graph_->insertConstant(1); in replace_linear_with_matmul()
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D | mkldnn_rewrite.cpp | 48 auto input_size = graph->insertConstant(input_size_value); in insertPrePackedConvOpForNode() 59 auto attr = graph->insertConstant(IValue("none")); in insertPrePackedConvOpForNode() 178 Value* packed_weight = graph->insertConstant(weak_class_obj) in PrePackingOpsFolder()
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D | concat_opt.cpp | 303 auto none = graph_->insertConstant(IValue()); in expandCat() 304 auto one = graph_->insertConstant(1); in expandCat() 312 cat_out_size.push_back(graph_->insertConstant(tensortype_sizes[i])); in expandCat() 332 auto start = graph_->insertConstant(start_idx); in expandCat() 342 auto end = graph_->insertConstant(end_idx); in expandCat()
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D | frozen_linear_folding.cpp | 116 auto fused_linear_w = b->owningGraph()->insertConstant(std::get<0>(out)); in FoldFrozenLinearBatchnorm() 117 auto fused_linear_b = b->owningGraph()->insertConstant(std::get<1>(out)); in FoldFrozenLinearBatchnorm()
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D | integer_value_refinement.cpp | 146 graph_->insertConstant(static_cast<int64_t>(*refine)); in RefineIntegerValues() 196 graph_->insertConstant(static_cast<int64_t>(*refine)); in RefineIntegerValues()
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D | erase_number_types.cpp | 42 Value* r = block->owningGraph()->insertConstant( in EraseNumberTypesOnBlock()
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D | peephole_list_idioms.cpp | 99 graph_->insertConstant(static_cast<int64_t>(*maybe_len))); in RefineListLens() 259 node->output()->replaceAllUsesWith(graph_->insertConstant( in runBlock()
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/external/pytorch/torch/csrc/jit/frontend/ |
D | canonicalize_modified_loop.cpp | 23 auto zero = g->insertConstant(0); in canonicalizeModifiedLoop() 24 auto one = g->insertConstant(1); in canonicalizeModifiedLoop() 28 g->insertConstant(std::numeric_limits<int64_t>::max())); in canonicalizeModifiedLoop()
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D | sugared_value.cpp | 179 auto idx = m.graph()->insertConstant(IValue(static_cast<int64_t>(i))); in attr() 557 start_ = g.insertConstant(0, loc); in RangeValue() 558 step_ = g.insertConstant(1, loc); in RangeValue() 567 step_ = g.insertConstant(1, loc); in RangeValue() 585 return insertConstant(*m.graph(), *static_len_, loc); in len() 809 m.graph()->insertConstant(IValue(enum_holder), loc)); in attr() 825 m.graph()->insertConstant(enum_value_ivalues, loc)); in iter()
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D | tracer.cpp | 38 Value* v = n->owningGraph()->insertConstant(value); in genericAddInput() 178 Value* constant = graph->insertConstant(ten); in getValue() 378 auto static_key = state->graph->insertConstant(key); in addInput() 594 auto static_key = graph->insertConstant(entry.key()); in setValue() 798 info[i] = g->insertConstant(value[i]); in addInputs() 862 info.push_back(g->insertConstant(elt)); in addInputs() 943 auto dim_val = graph->insertConstant(dim); in getSizeOf()
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/external/pytorch/torch/csrc/jit/python/ |
D | python_sugared_value.cpp | 139 auto err_msg = insertConstant( in call() 406 std::make_shared<SimpleValue>(insertConstant(*m.graph(), prefix)); in recurseThroughNestedModules() 449 std::make_shared<SimpleValue>(insertConstant(*m.graph(), name)); in getSugaredNamedBufferDict() 477 std::make_shared<SimpleValue>(insertConstant(*m.graph(), name)); in getSugaredNamedParameterList() 505 std::make_shared<SimpleValue>(insertConstant(*m.graph(), name)); in getSugaredDict() 535 std::make_shared<SimpleValue>(insertConstant(*m.graph(), name)); in getSugaredNamedParameterDict() 612 return toSimple(m.graph()->insertConstant(v, loc)); in toSugaredValue() 979 error_message = insertConstant(*caller.graph(), "", loc); in call() 998 insertConstant(*caller.graph(), exception_class_qualified_name_, loc); in call() 1080 return toSimple(m.graph()->insertConstant(enum_ivalue, loc)); in createSimpleEnumValue() [all …]
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/external/pytorch/test/jit/ |
D | test_python_ir.py | 64 foo.graph.insertConstant("goodbye") 65 foo.graph.insertConstant("hello") 67 foo.graph.insertConstant("hello")
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/external/pytorch/torch/csrc/jit/serialization/ |
D | import_source.cpp | 89 value = m.graph()->insertConstant(non_holding_object_cache[obj], loc); in attr() 91 value = m.graph()->insertConstant(constants_->at(offset), loc); in attr() 236 graph->insertConstant(std::numeric_limits<double>::infinity(), loc)); in resolveValue() 240 graph->insertConstant(std::numeric_limits<double>::quiet_NaN(), loc)); in resolveValue() 243 return std::make_shared<SimpleValue>(graph->insertConstant( in resolveValue() 247 return std::make_shared<SimpleValue>(graph->insertConstant( in resolveValue()
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/external/pytorch/torch/csrc/jit/ir/ |
D | constants.h | 25 TORCH_API Value* insertConstant(
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D | named_value.h | 56 return insertConstant( in value()
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/external/pytorch/torch/csrc/jit/passes/onnx/ |
D | prepare_division_for_onnx.cpp | 26 auto* nonblocking = subgraph->insertConstant(0); in PrepareDivisionForONNXOnBlock()
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/external/pytorch/torch/csrc/jit/runtime/ |
D | autodiff.cpp | 219 auto* cDim = g->insertConstant(node->i(attr::dim)); in buildSymbolicGradient() 239 graph->insertConstant(c10::List<bool>({true, true, true}))}); in buildSymbolicGradient() 269 graph->insertConstant(c10::List<bool>({true, true, true}))}); in buildSymbolicGradient() 579 size = node->owningGraph()->insertConstant(*input_size); in foldSizeIfNotEqual() 581 size = node->owningGraph()->insertConstant(IValue()); in foldSizeIfNotEqual()
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/external/pytorch/torch/csrc/jit/passes/quantization/ |
D | insert_quant_dequant.cpp | 95 auto reduce_range = graph->insertConstant(reduce_range_param); in insertChooseQParams() 173 Value* float_scalar_type = graph->insertConstant(IValue(c10::kFloat)); in insertScalarToTensor() 174 Value* none = graph->insertConstant(IValue()); in insertScalarToTensor() 323 Value* optimized_qparams_false = g->insertConstant(optimized_qparams); in insertEmbeddingBagOps() 324 Value* nbins_200 = g->insertConstant(NBINS); in insertEmbeddingBagOps() 325 Value* ratio_0_16 = g->insertConstant(RATIO); in insertEmbeddingBagOps() 362 Value* none = g->insertConstant(IValue()); in insertEmbeddingBagOps() 363 Value* zero = g->insertConstant(IValue(0)); in insertEmbeddingBagOps() 365 auto pruned_const = g->insertConstant(pruned_wt); in insertEmbeddingBagOps() 1180 Value* qparam_val = graph->insertConstant(qparam.second); in propagateQParams()
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/external/pytorch/torch/csrc/lazy/ts_backend/ |
D | dynamic_ir.cpp | 16 auto index = loctx->graph()->insertConstant(static_cast<int64_t>(this->dim_)); in Lower()
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