Add matrix_rank #10338

vishwakftw · 2018-08-08T01:39:19Z

Similar functionality as NumPy
Added doc string
Added tests

- Similar functionality as NumPy - Added doc string - Added tests

aten/src/ATen/native/LinearAlgebra.cpp

  return V.mm(S_pseudoinv.diag().mm(U.t()));
 }

+static double _get_epsilon(const ScalarType& sc_type) {


aten/src/ATen/native/LinearAlgebra.cpp

+           "of floating types");
+
+  Tensor S = _matrix_rank_helper(self, symmetric);
+  return (S > tol).toType(kLong).sum().toCLong();


vishwakftw · 2018-08-09T04:51:58Z

@ssnl Is this good to go?

aten/src/ATen/native/LinearAlgebra.cpp

+           "of floating types");
+
+  Tensor S = _matrix_rank_helper(self, symmetric);
+  return (S > tol).toType(kLong).sum();


aten/src/ATen/native/LinearAlgebra.cpp

  return V.mm(S_pseudoinv.diag().mm(U.t()));
 }

+static double _get_epsilon(const ScalarType& sc_type) {


aten/src/ATen/native/LinearAlgebra.cpp

+           "of floating types");
+
+  Tensor S = _matrix_rank_helper(self, symmetric);
+  double tol = S.max().toCDouble() * std::max<double>(self.size(0), self.size(1)) *


…nto matrix-rank

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aten/src/ATen/native/LinearAlgebra.cpp

  return V.mm(S_pseudoinv.diag().mm(U.t()));
 }

+Tensor _matrix_rank_helper(const Tensor& self, bool symmetric) {


aten/src/ATen/native/LinearAlgebra.cpp

+           "of floating types");
+
+  Tensor S = _matrix_rank_helper(self, symmetric);
+  Tensor tol = S.max() * _get_epsilon(self.type());


torch/_torch_docs.py

+
+:attr:`tol` is the threshold below which the singular values (or the eigenvalues
+when :attr:`symmetric` is ``True``) are considered to be 0. If :attr:`tol` is not
+specified, :attr:`tol` is set to `S.max() * max(S.size()) * eps` where `S` is the


torch/_torch_docs.py

+
+    >>> a = torch.eye(10)
+    >>> torch.matrix_rank(a)
+    10


aten/src/ATen/native/LinearAlgebraUtils.h

+static inline Tensor _get_epsilon(const Type& type) {
+  switch (type.scalarType()) {
+    case at::ScalarType::Half:
+      return type.tensor({}).fill_(std::numeric_limits<at::Half>::epsilon());


goldsborough

Can be a future fix.

aten/src/ATen/native/LinearAlgebra.cpp

+
+  Tensor S = _matrix_rank_helper(self, symmetric);
+  Tensor tol = _get_epsilon(self.type()) * std::max(self.size(0), self.size(1));
+  tol.mul_(S.max());


ssnl

Thanks!

torch/_torch_docs.py

+:attr:`tol` is the threshold below which the singular values (or the eigenvalues
+when :attr:`symmetric` is ``True``) are considered to be 0. If :attr:`tol` is not
+specified, :attr:`tol` is set to ``S.max() * max(S.size()) * eps`` where `S` is the
+singular values (or the eigenvalues when :attr:`symmetric` is ``True``), and `eps`


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vishwakftw · 2018-08-12T01:03:03Z

@ssnl is this good to go?

vishwakftw · 2018-08-15T00:07:04Z

@ssnl ping :)

ssnl · 2018-08-15T00:08:08Z

I tried to get another person to look before merging but wasn't able to. Will get this going tomorrow.

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test/test_torch.py

        self.assertEqual(X, Xhat, 1e-8, 'USV\' wrong')

+    @staticmethod
+    def _test_matrix_rank(self, conv_fn):


…nto matrix-rank

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vishwakftw · 2018-08-17T16:40:27Z

@ssnl is this good to go?

ssnl · 2018-08-17T17:27:56Z

It’s failing internal test. I’ve no idea why yet, but I’ll look this afternoon.

…

On Fri, Aug 17, 2018 at 12:40 Vishwak Srinivasan ***@***.***> wrote: @ssnl <https://github.com/SsnL> is this good to go? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#10338 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AFaWZb8d-qn1fW7RjAUpfNUKWLmz97vsks5uRvIHgaJpZM4VzIvZ> .

ssnl · 2018-08-19T01:16:29Z

@vishwakftw There is some really weird things going on. I tried but can't quite repro or figure out why. I will talk with people knowing more about those tests on Monday. Sorry about it.

vishwakftw · 2018-08-19T01:29:10Z

Oh no worries. Please take your time. After all, it’s a weekend :)

ssnl · 2018-08-21T20:08:49Z

@vishwakftw the 3rd arg of np.linalg.matrix_rank is added in NumPy 0.14... Can you add a version check on the matrix_rank(aaT.cpu().numpy(), 0.01, True) test case? This is causing the internal test failure. Sorry about it.

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Summary: - Similar functionality as NumPy - Added doc string - Added tests Differential Revision: D9240850 Pulled By: SsnL fbshipit-source-id: 1d04cfadb076e99e03bdf699bc41b8fac06831bf

Add matrix_rank

b467995

- Similar functionality as NumPy - Added doc string - Added tests

vishwakftw requested review from apaszke, colesbury, ezyang, gchanan, soumith, ssnl, zdevito and zou3519 as code owners August 8, 2018 01:39

vishwakftw commented Aug 8, 2018

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ssnl reviewed Aug 8, 2018

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vishwakftw added 2 commits August 9, 2018 08:08

Modify matrix_rank to return scalar instead of int

5989f8a

Update return type of matrix_rank in docs

e1f1012

ssnl reviewed Aug 9, 2018

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vishwakftw added 2 commits August 9, 2018 13:26

CR

15753e0

Merge branch 'matrix-rank' of https://github.com/vishwakftw/pytorch i…

2374e88

…nto matrix-rank

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ssnl reviewed Aug 9, 2018

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torch/_torch_docs.py Outdated

>>> a = torch.eye(10)

>>> torch.matrix_rank(a)

10

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CR by SsnL

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aten/src/ATen/native/LinearAlgebra.cpp Outdated

Tensor S = _matrix_rank_helper(self, symmetric);

Tensor tol = _get_epsilon(self.type()) * std::max(self.size(0), self.size(1));

tol.mul_(S.max());

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More CR

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Update _torch_docs.py

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test/test_torch.py

self.assertEqual(X, Xhat, 1e-8, 'USV\' wrong')

@staticmethod

def _test_matrix_rank(self, conv_fn):

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vishwakftw added 2 commits August 16, 2018 08:30

Fix CUDA tests

79f815e

Merge branch 'matrix-rank' of https://github.com/vishwakftw/pytorch i…

b4b3324

…nto matrix-rank

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check numpy version for test

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vishwakftw closed this Aug 23, 2018

vishwakftw deleted the matrix-rank branch August 23, 2018 01:59

ezyang added the open source label Jun 24, 2019

Add matrix_rank #10338

Add matrix_rank #10338

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vishwakftw commented Aug 8, 2018 •

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