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Remove incorrect links to zdevito/ATen (pytorch#50065)
Summary: Similar to pytorch#49028, this PR removes a few more references to https://github.com/zdevito/ATen. - The links for Functions.h, Tensor.h, and Type.h are simply broken, probably because they refer to `master` rather than a specific commit (cf. pytorch#47066) - I'm unsure about the change to the `about` section of `aten/conda/meta.yaml`; can someone comment on whether I am understanding that field correctly? - The reference to zdevito/ATen#163 remains [in `tools/autograd/derivatives.yaml`](https://github.com/pytorch/pytorch/blob/cd608fe59b70fa7cafb07110096b2e023a8b6e9c/tools/autograd/derivatives.yaml#L91), because the contents of that issue discussion don't seem to be mirrored anywhere else. Pull Request resolved: pytorch#50065 Reviewed By: ezyang, walterddr Differential Revision: D25767353 Pulled By: samestep fbshipit-source-id: 265f46f058bc54ef6d1a77f112cdfa1f115b3247
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aten/conda/meta.yaml

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- mkl # [not osx]
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about:
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home: https://github.com/zdevito/ATen
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home: https://github.com/pytorch/pytorch
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license: BSD
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summary: A TENsor library for C++14
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caffe2/contrib/aten/README.md

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# An ATen operator for Caffe2
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[ATen](https://github.com/zdevito/aten) is a simple tensor library thats exposes the Tensor operations in Torch
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ATen is a simple tensor library thats exposes the Tensor operations in Torch
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and PyTorch directly in C++14. This library provides a generated wrapper around the ATen API
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that makes these functions available in Caffe2 as an operator. It also makes it accessible using the
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ToffeeIR.
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### Example Usage in Caffe2
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First identify a function in ATen you want to call in [Functions.h](https://github.com/zdevito/ATen/blob/master/doc/Functions.h),
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[Tensor.h](https://github.com/zdevito/ATen/blob/master/doc/Tensor.h), or [Type.h](https://github.com/zdevito/ATen/blob/master/doc/Type.h).
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First identify a function in ATen you want to call in Functions.h,
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Tensor.h, or Type.h.
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We will call the `pow` operator:
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caffe2/contrib/aten/docs/pytorch_to_caffe2.md

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are specific to a network.
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To bridge this gap, we provide an experimental operator in ONNX that allows you to directly access PyTorch's tensor functions using the ATen library.
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[ATen](https://github.com/zdevito/aten) is the underlying C++ library that PyTorch uses to do tensor operations. Caffe2 has an [ATen operator](https://github.com/caffe2/caffe2/tree/master/caffe2/contrib/aten)
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[ATen](https://github.com/pytorch/pytorch/tree/master/aten) is the underlying C++ library that PyTorch uses to do tensor operations. Caffe2 has an [ATen operator](https://github.com/pytorch/pytorch/tree/master/caffe2/contrib/aten)
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that can run these tensor functions in a Caffe2 network after importing them through ONNX.
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This guide explains how to configure Caffe2 and modify your PyTorch program to use
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The function `graph.at` adds a new ATen op the computation graph.
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You can call any ATen function using this facility. To do so,
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first identify a function in ATen you want to call in [Functions.h](https://github.com/zdevito/ATen/blob/master/doc/Functions.h),
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[Tensor.h](https://github.com/zdevito/ATen/blob/master/doc/Tensor.h), or [Type.h](https://github.com/zdevito/ATen/blob/master/doc/Type.h).
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first identify a function in ATen you want to call in Functions.h,
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Tensor.h, or Type.h.
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As an example, we might want to call the `pow` operator:
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that determines the type. For instance, `ones` creates a new constant tensor of all ones:
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```
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class Type {
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...
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virtual Tensor ones(IntArrayRef size) const;
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...
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...
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virtual Tensor ones(IntArrayRef size) const;
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...
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};
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```
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