Add `at` method to accessors
VivekPanyam opened this issue · 2 comments
VivekPanyam commented
Bounds check and call [] operator
VivekPanyam commented
More context
Add an at method to TensorAccessor that does a bounds check and then calls the [] operator.
The relevant code is
neuropod/source/neuropod/internal/tensor_accessor.hh
Lines 99 to 140 in fab5a86
| // Indexing into a N dimensional accessor returns an N - 1 dimensional accessor | |
| const TensorAccessor<Container, N - 1> operator[](int64_t i) const | |
| { | |
| // This operator returns a TensorAccessor that accesses an `N - 1` dimensional tensor at index `i` | |
| // of this TensorAccessor. To do this, we compute the correct offsets into `data_` and pass along the last | |
| // `N - 1` elements in `dims_` and `strides_` to the new accessor. For example: | |
| // | |
| // auto tensor = allocator->allocate_tensor<float>({3, 5}); | |
| // | |
| // // Not using `auto` for clarity on types | |
| // TensorAccessor<float *, 2> accessor = tensor->accessor(); | |
| // | |
| // // In this accessor: | |
| // // `data_` points to the tensor's underlying buffer | |
| // // `dims_` points to an array containing 3, 5 | |
| // // `strides_` points to an array containing 5, 1 | |
| // // `offset_` is 0 | |
| // // This means that any indexing into this accessor indexes into the underlying buffer | |
| // // starting at `0` with a stride of `5` | |
| // | |
| // // Since `N` (in the template args) is > 1, this accessor returns another accessor when indexed into | |
| // TensorAccessor<float *, 1> subaccessor = accessor[2]; | |
| // | |
| // // In this accessor: | |
| // // `data_` points to the tensor's underlying buffer | |
| // // `dims_` points to an array containing 5 | |
| // // `strides_` points to an array containing 1 | |
| // // `offset_` is 10 | |
| // // This means that any indexing into this accessor indexes into the underlying buffer | |
| // // starting at `10` with a stride of `1` | |
| // | |
| // // This is equivalent to an index of 11 in the underlying buffer (or the 12th item) | |
| // float item = subaccessor[1]; | |
| // | |
| // // Same as this | |
| // float same_item = accessor[2][1]; | |
| // | |
| // // Same as this | |
| // float also_same = *(tensor->get_raw_data_ptr() + 11); | |
| // | |
| return TensorAccessor<Container, N - 1>(data_, dims_ + 1, strides_ + 1, offset_ + strides_[0] * i); | |
| } |
and
| auto operator[](int64_t i) const -> decltype(data_[offset_ + i]) { return data_[offset_ + i]; } |
ArkaprabhaChakraborty commented
Hi can I get some guidance to work on this issue?