Arraymancer
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mratsim
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
Related to #162 but deserves to be its own issue. Given the existence of `readCsv` and `toCsv` it's not unexpected to think that arraymancer could parse its own csv files....
Hello, it seems like the output from the forward pass zeros out with this small example below: ```nim import arraymancer let ctx = newContext Tensor[float32] network ctx, Test: layers: hidden1:...
Format to be defined: ### Non-binary (will certainly have size issues) - JSON via Nim [marshal](https://nim-lang.org/docs/marshal.html) module - YAML via [NimYAML](https://nimyaml.org/serialization.html) - ... ### Binary - MessagePack via [msgpack4nim](https://github.com/jangko/msgpack4nim) or...
```nim import nimpy import times import arraymancer var tic, toc: float # for math let np = pyImport("numpy") tic = cpuTime() for i in 0..
It would be very useful to be able to access an elemenent of a tensor using a sequence or array of int Use case example : ```nim var tensor1 :...
This replaces the use of `mapX_inline` and `applyX_inline` by the forEach / forEachContiguous / forEachParallel / forEachSerial laser iterators. This is particularly valuable for recurrent neural network like GRU because...
Currently, reshaping respects existing memory layout, so two tensors with different contiguity can often differ after reshaping: ```nim let a = toSeq(1..12).toTensor().reshape(3, 2, 2).asContiguous(rowMajor, force=true) b = toSeq(1..12).toTensor().reshape(3, 2, 2).asContiguous(colMajor,...
I'm going to need some help refining this (especially not sure yet how the backward pass will work), but I think that I can add a CRF head for sequence...
Fix https://github.com/mratsim/Arraymancer/issues/185 Pending https://github.com/nim-lang/Nim/pull/8715, upstream fix of https://github.com/nim-lang/Nim/issues/8706 This should avoid the regression https://github.com/mratsim/Arraymancer/issues/241