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Diffstat (limited to 'reference_model/src/ops/shape.cc')
| -rw-r--r-- | reference_model/src/ops/shape.cc | 198 |
1 files changed, 198 insertions, 0 deletions
diff --git a/reference_model/src/ops/shape.cc b/reference_model/src/ops/shape.cc new file mode 100644 index 0000000..b087dd8 --- /dev/null +++ b/reference_model/src/ops/shape.cc @@ -0,0 +1,198 @@ +// Copyright (c) 2023-2024, ARM Limited. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "shape.h" + +using namespace TosaReference; +using namespace Eigen; +using namespace tosa; + +OpConstShape::OpConstShape(SubgraphTraverser* sgt_, uint64_t id_) + : GraphNode(sgt_, Op_CONST, id_) +{ + setRequiredOperands(0, 1); +} + +OpConstShape::~OpConstShape() +{} + +int OpConstShape::checkTensorAttributes() +{ + if (validateRequiredOperands()) + return 1; + + return 0; +} + +int OpConstShape::eval() +{ + for (auto ct : getOutputs()) + { + if (!ct->getIsValid()) + { + std::string err = "Constant Shape tensor " + ct->getName() + " not correctly initialized"; + printNodeValidationError(err.c_str()); + return 1; + } + } + + // Evaluation is trivial for constants + return GraphNode::eval(); +} + +OpConcatShape::OpConcatShape(SubgraphTraverser* sgt_, uint64_t id_) + : GraphNode(sgt_, Op_CONCAT_SHAPE, id_) +{ + setRequiredOperands(-1, 1); + setRequiredRank(1, 1); +} + +OpConcatShape::~OpConcatShape() +{} + +int OpConcatShape::checkTensorAttributes() +{ + if (validateRequiredOperands()) + return 1; + + if (inputs.empty()) + { + printNodeValidationError("ConcatShape operator must have at least one input tensor"); + return 1; + } + + int32_t num_inputs = inputs.size(); + int32_t elements_count = 0; + for (int32_t i = 0; i < num_inputs; i++) + { + if (validateRequiredRank(inputs[i])) + return 1; + ins.push_back(dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[i])); + elements_count += inputs[i]->getShape()[0]; + } + + ERROR_IF(elements_count != outputs[0]->getShape()[0], + "OpConcatShape: sum of input elements not equal to output number of elements"); + + num_dims = outputs[0]->getShape()[0]; + out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); + + return 0; +} + +int OpConcatShape::eval() +{ + ETensor1<EigenType> out_tensor(num_dims); + int32_t out_idx = 0; + for (size_t i = 0; i < ins.size(); i++) + { + // all tosa.shape values are 1-d tensors + // interate in_idx in range of [0, rank of 1-d tensor] + for (int32_t in_idx = 0; in_idx < inputs[i]->getShape()[0]; in_idx++) + { + out_tensor(out_idx) = ins[i]->getTensor()(in_idx); + out_idx++; + } + } + out->getTensor() = out_tensor; + return GraphNode::eval(); +} + +ShapeBinaryNodeBase::ShapeBinaryNodeBase(SubgraphTraverser* sgt_, const Op& op_, uint64_t id_) + : GraphNode(sgt_, op_, id_) +{ + setRequiredOperands(2, 1); + setRequiredRank(1, 1); + + fcn = [](EigenType a, EigenType b) -> EigenType { return EigenType(); }; +} + +ShapeBinaryNodeBase::~ShapeBinaryNodeBase() +{} + +int ShapeBinaryNodeBase::checkTensorAttributes() +{ + if (validateRequiredOperands()) + return 1; + if (validateRequiredRank(inputs[0]) || validateRequiredRank(inputs[1]) || validateRequiredRank(outputs[0])) + return 1; + + num_dims = outputs[0]->getShape()[0]; + + if (inputs[0]->getShape()[0] != num_dims) + { + std::string err = "Binary shape operators " + std::string(EnumNamesOp()[nodeType]) + + " lhs input and output rank/shape must match"; + printNodeValidationError(err.c_str()); + return 1; + } + + if (inputs[1]->getShape()[0] != num_dims) + { + std::string err = "Binary shape operators " + std::string(EnumNamesOp()[nodeType]) + + " rhs input and output rank/shape must match"; + printNodeValidationError(err.c_str()); + return 1; + } + + a = dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[0]); + b = dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[1]); + result = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); + + ASSERT_MEM(a && b && result); + + return 0; +} + +int ShapeBinaryNodeBase::eval() +{ + auto ia = a->getTensor(); + auto ib = b->getTensor(); + ETensor1<EigenType> out_tens(num_dims); + for (int32_t i = 0; i < num_dims; i++) + { + EigenType lhs = ia(i); + EigenType rhs = ib(i); + out_tens(i) = (lhs < 0 || rhs < 0) ? static_cast<EigenType>(-1) : fcn(lhs, rhs); + } + + result->getTensor() = out_tens; + return GraphNode::eval(); +} + +int OpAddShape::register_fcn() +{ + fcn = [](EigenType a, EigenType b) -> EigenType { return a + b; }; + return 0; +} + +int OpSubShape::register_fcn() +{ + fcn = [](EigenType a, EigenType b) -> EigenType { return a - b; }; + return 0; +} + +int OpMulShape::register_fcn() +{ + fcn = [](EigenType a, EigenType b) -> EigenType { return a * b; }; + return 0; +} + +int OpDivShape::register_fcn() +{ + fcn = [](EigenType a, EigenType b) -> EigenType { + return (b == static_cast<EigenType>(0)) ? static_cast<EigenType>(-1) : (a / b); + }; + return 0; +}
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