diff options
Diffstat (limited to 'reference_model/src/ops/data_layout.cc')
| -rw-r--r-- | reference_model/src/ops/data_layout.cc | 93 |
1 files changed, 65 insertions, 28 deletions
diff --git a/reference_model/src/ops/data_layout.cc b/reference_model/src/ops/data_layout.cc index 86326f5..f3e80f3 100644 --- a/reference_model/src/ops/data_layout.cc +++ b/reference_model/src/ops/data_layout.cc @@ -51,25 +51,49 @@ int OpConcat<Rank, Dtype>::checkTensorAttributes() printNodeValidationError("Concat operator must have at least one input tensor"); return 1; } + + int32_t num_inputs = inputs.size(); + // output and input must be the same types and rank - for (size_t i = 0; i < inputs.size(); i++) + for (int32_t i = 0; i < num_inputs; i++) { if (inputs[i]->matchRankType(*outputs[0])) { - printNodeValidationError("Concat operator input ranks and types must match"); + printNodeValidationError("OpConcat: input ranks and types must match"); return 1; } ins.push_back(dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[i])); } - out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); - - if (attribute->axis() < 0 || (size_t)attribute->axis() >= inputs[0]->getShape().size()) + if (attribute->axis() < 0 || (size_t)attribute->axis() >= Rank) { - printNodeValidationError("Axis is beyond input tensor rank"); + printNodeValidationError("OpConcat: axis is beyond output tensor rank"); return 1; } + int32_t output_dim_on_axis = 0; + for (int32_t j = 0; j < num_inputs; j++) + { + for (int32_t i = 0; i < Rank; i++) + { + int32_t input_dim = inputs[j]->getShape()[i]; + if (i == attribute->axis()) + { + output_dim_on_axis += input_dim; + } + else if (input_dim != outputs[0]->getShape()[i]) + { + printNodeValidationError("OpConcat: input dimension not matching output dimension"); + return 1; + } + } + } + + ERROR_IF(output_dim_on_axis == outputs[0]->getShape()[attribute->axis()], + "OpConcat: sum of input dimension on axis not equal to output dimension on axis"); + + out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); + return 0; } @@ -135,14 +159,13 @@ int OpPad<Rank, Dtype>::checkTensorAttributes() return 1; } - in = dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[0]); - out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); - TosaReference::TensorTemplate<ETensor2<int32_t>>* paddings = - dynamic_cast<TosaReference::TensorTemplate<ETensor2<int32_t>>*>(inputs[1]); + in = dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[0]); + out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); + paddings = dynamic_cast<TosaReference::TensorTemplate<ETensor2<int32_t>>*>(inputs[1]); - for (int i = 0; i < Rank; i++) + if (this->qinfo && Dtype != DType_INT8) { - paddings_array[i] = std::make_pair(paddings->getTensor()(i, 0), paddings->getTensor()(i, 1)); + ERROR_IF(this->qinfo->input_zp() != 0, "OpPad: zeropoint should be 0"); } return 0; @@ -151,6 +174,14 @@ int OpPad<Rank, Dtype>::checkTensorAttributes() template <int Rank, DType Dtype> int OpPad<Rank, Dtype>::eval() { + // Move this to + for (int i = 0; i < Rank; i++) + { + ERROR_IF((paddings->getTensor()(i, 0) < 0) || (paddings->getTensor()(i, 1) < 0), + "OpPad: padding can't be smaller than 0"); + paddings_array[i] = std::make_pair(paddings->getTensor()(i, 0), paddings->getTensor()(i, 1)); + } + InEigenType pad_value = 0; if (this->qinfo) { @@ -202,12 +233,20 @@ int OpReshape<InRank, OutRank, Dtype>::checkTensorAttributes() return 1; } + ERROR_IF(inputs[0]->getElementCount() != outputs[0]->getElementCount(), + "Input tensor size does not match output tensor size"); + for (uint32_t d = 0; d < OutRank; d++) { if (attribute->shape()[d] == -1) { minusOneCount++; } + else + { + ERROR_IF(attribute->shape()[d] != outputs[0]->getShape()[d], + "OpReshape: new_shape doesn't match output shape"); + } } if (minusOneCount > 1) @@ -358,7 +397,7 @@ OpSlice<Rank, Dtype>::OpSlice(SubgraphTraverser* sgt_, : GraphNode(sgt_, Op_SLICE, id_) { setRequiredOperands(1, 1); - setRequiredRank(0, 6); + setRequiredRank(1, 4); INIT_ATTRIBUTE(Slice); } @@ -391,23 +430,20 @@ int OpSlice<Rank, Dtype>::checkTensorAttributes() in = dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[0]); out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]); - for (size_t i = 0; i < attribute->begin().size(); i++) - { - begin_array[i] = attribute->begin()[i]; - } + ERROR_IF((int32_t)attribute->begin().size() != in->getRank(), + "OpSlice: begin array length needs to be rank(input)"); + ERROR_IF((int32_t)attribute->size().size() != in->getRank(), "OpSlice: size array length needs to be rank(input)"); - for (size_t i = 0; i < attribute->size().size(); i++) + for (int32_t i = 0; i < in->getRank(); i++) { - if (attribute->size()[i] != 0) - { - size_array[i] = attribute->size()[i]; - } - else - { - // Tensorflow assigns a zero size to dimensions that are kept - // Eigen expects size to be the full size of the dimension - size_array[i] = in->getTensor().dimension(0); - } + int32_t b = attribute->begin()[i]; + int32_t s = attribute->size()[i]; + ERROR_IF(b < 0 || b >= in->getShape()[i], "OpSlice: start out of boundary"); + ERROR_IF((b + s) < 0 || (b + s) > in->getShape()[i], "OpSlice: (start+size) out of boundary"); + ERROR_IF(s <= 0, "OpSlice: output must be positive"); + ERROR_IF(s != out->getShape()[i], "OpSlice: size doesn't match output tensor dimension"); + begin_array[i] = b; + size_array[i] = s; } return 0; @@ -611,6 +647,7 @@ int OpTranspose<Rank, Dtype>::eval() for (int32_t d = 0; d < Rank; d++) { perm_array[d] = this->perm_tensor->getTensor().data()[d]; + ERROR_IF(perm_array[d] < 0 or perm_array[d] >= Rank, "OpTranspose: index out of boundary"); } out->getTensor() = in->getTensor().shuffle(perm_array); |