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/*
* Copyright 2022 Google LLC
*
* 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 "fcp/aggregation/core/tensor_shape.h"
#include <utility>
#include "fcp/base/monitoring.h"
#ifndef FCP_NANOLIBC
#include "fcp/aggregation/core/tensor.pb.h"
#endif
namespace fcp {
namespace aggregation {
size_t TensorShape::NumElements() const {
size_t num_elements = 1;
for (auto dim_size : dim_sizes_) {
num_elements *= dim_size;
}
return num_elements;
}
#ifndef FCP_NANOLIBC
StatusOr<TensorShape> TensorShape::FromProto(
const TensorShapeProto& shape_proto) {
TensorShape::DimSizesVector dim_sizes;
for (int64_t dim_size : shape_proto.dim_sizes()) {
if (dim_size < 0) {
return FCP_STATUS(INVALID_ARGUMENT)
<< "Negative dimension size isn't supported when converting from "
<< "shape_proto: " << shape_proto.ShortDebugString();
}
dim_sizes.push_back(dim_size);
}
return TensorShape(std::move(dim_sizes));
}
TensorShapeProto TensorShape::ToProto() const {
TensorShapeProto shape_proto;
for (auto dim_size : dim_sizes()) {
shape_proto.add_dim_sizes(static_cast<int64_t>(dim_size));
}
return shape_proto;
}
#endif // FCP_NANOLIBC
} // namespace aggregation
} // namespace fcp
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