[lua-torch-nn] 04/07: patch: remove merged fix-spelling-errors
Zhou Mo
cdluminate-guest at moszumanska.debian.org
Sat Sep 10 03:27:37 UTC 2016
This is an automated email from the git hooks/post-receive script.
cdluminate-guest pushed a commit to branch master
in repository lua-torch-nn.
commit 06063cbcc91526ef18c3ade9be825e2162693af7
Author: Zhou Mo <cdluminate at gmail.com>
Date: Sat Sep 10 02:36:27 2016 +0000
patch: remove merged fix-spelling-errors
---
debian/changelog | 1 +
debian/patches/fix-spelling-errors | 158 -------------------------------------
debian/patches/series | 1 -
3 files changed, 1 insertion(+), 159 deletions(-)
diff --git a/debian/changelog b/debian/changelog
index eb83cca..4387d15 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -1,6 +1,7 @@
lua-torch-nn (0~20160908-g9d7b9ea+dfsg-1) UNRELEASED; urgency=medium
* Import upstream snapshot 9d7b9ea4c9ba38e92dc0186af33ff7c0f323d2a4.
+ * Remove patch 'fix-spelling-errors' which was merged to upstream.
-- Zhou Mo <cdluminate at gmail.com> Sat, 10 Sep 2016 02:34:03 +0000
diff --git a/debian/patches/fix-spelling-errors b/debian/patches/fix-spelling-errors
deleted file mode 100644
index 2fdae71..0000000
--- a/debian/patches/fix-spelling-errors
+++ /dev/null
@@ -1,158 +0,0 @@
-Forward: yes, merged. https://github.com/torch/nn/pull/929
-diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
-index d4da7c9..92574db 100644
---- a/CONTRIBUTING.md
-+++ b/CONTRIBUTING.md
-@@ -22,7 +22,7 @@ restrictions:
- [mailing-list](http://groups.google.com/forum/#!forum/torch7)).
-
- * Please **do not** open issues regarding the code in a torch package
-- outside the core. For example dont open issues about the
-+ outside the core. For example don't open issues about the
- REPL in the nn issue tracker, use the trepl issue tracker for that.
-
- <a name="bugs"></a>
-diff --git a/ClassSimplexCriterion.lua b/ClassSimplexCriterion.lua
-index 6ccaed9..9cabc01 100644
---- a/ClassSimplexCriterion.lua
-+++ b/ClassSimplexCriterion.lua
-@@ -64,7 +64,7 @@ function ClassSimplexCriterion:__init(nClasses)
- end
-
- -- handle target being both 1D tensor, and
---- target being 2D tensor (2D tensor means dont do anything)
-+-- target being 2D tensor (2D tensor means don't do anything)
- local function transformTarget(self, target)
- if torch.type(target) == 'number' then
- self._target:resize(self.nClasses)
-diff --git a/Container.lua b/Container.lua
-index 6af4d7d..469a370 100644
---- a/Container.lua
-+++ b/Container.lua
-@@ -22,7 +22,7 @@ end
-
- -- Check if passing arguments through xpcall is supported in this Lua interpreter.
- local _, XPCALL_ARGS = xpcall(function(x) return x ~= nil end, function() end, 1)
--local TRACEBACK_WARNING = "WARNING: If you see a stack trace below, it doesn't point to the place where this error occured. Please use only the one above."
-+local TRACEBACK_WARNING = "WARNING: If you see a stack trace below, it doesn't point to the place where this error occurred. Please use only the one above."
- -- module argument can be retrieved with moduleIndex, but code is cleaner when
- -- it has to be specified anyway.
- function Container:rethrowErrors(module, moduleIndex, funcName, ...)
-diff --git a/LookupTable.lua b/LookupTable.lua
-index 8a60354..cf9c687 100644
---- a/LookupTable.lua
-+++ b/LookupTable.lua
-@@ -125,7 +125,7 @@ function LookupTable:renorm(input)
- if not self.maxNorm then
- return
- end
-- -- copy input into _input, so _input is continous.
-+ -- copy input into _input, so _input is continuous.
- -- The copied _input will be modified in the C code.
- self._input:resize(input:size()):copy(input)
- local row_idx = self._input
-diff --git a/SpatialDropout.lua b/SpatialDropout.lua
-index 35daa18..99cd0fc 100644
---- a/SpatialDropout.lua
-+++ b/SpatialDropout.lua
-@@ -19,7 +19,7 @@ function SpatialDropout:updateOutput(input)
- end
- self.noise:bernoulli(1-self.p)
- -- We expand the random dropouts to the entire feature map because the
-- -- features are likely correlated accross the map and so the dropout
-+ -- features are likely correlated across the map and so the dropout
- -- should also be correlated.
- self.output:cmul(torch.expandAs(self.noise, input))
- else
-diff --git a/Sum.lua b/Sum.lua
-index 5d61c28..9ff73f8 100644
---- a/Sum.lua
-+++ b/Sum.lua
-@@ -36,8 +36,8 @@ end
-
- function Sum:updateGradInput(input, gradOutput)
- local dimension = self:_getPositiveDimension(input)
-- -- zero-strides dont work with MKL/BLAS, so
-- -- dont set self.gradInput to zero-stride tensor.
-+ -- zero-strides don't work with MKL/BLAS, so
-+ -- don't set self.gradInput to zero-stride tensor.
- -- Instead, do a deepcopy
- local size = input:size()
- size[dimension] = 1
-diff --git a/VolumetricDropout.lua b/VolumetricDropout.lua
-index 5f495af..1be85b1 100644
---- a/VolumetricDropout.lua
-+++ b/VolumetricDropout.lua
-@@ -19,7 +19,7 @@ function VolumetricDropout:updateOutput(input)
- end
- self.noise:bernoulli(1-self.p)
- -- We expand the random dropouts to the entire feature map because the
-- -- features are likely correlated accross the map and so the dropout
-+ -- features are likely correlated across the map and so the dropout
- -- should also be correlated.
- self.output:cmul(torch.expandAs(self.noise, input))
- else
-diff --git a/doc/simple.md b/doc/simple.md
-index 6f01a56..2d94465 100644
---- a/doc/simple.md
-+++ b/doc/simple.md
-@@ -598,7 +598,7 @@ end
- module = nn.Copy(inputType, outputType, [forceCopy, dontCast])
- ```
-
--This layer copies the input to output with type casting from `inputType` to `outputType`. Unless `forceCopy` is true, when the first two arguments are the same, the input isn't copied, only transfered as the output. The default `forceCopy` is false.
-+This layer copies the input to output with type casting from `inputType` to `outputType`. Unless `forceCopy` is true, when the first two arguments are the same, the input isn't copied, only transferred as the output. The default `forceCopy` is false.
- When `dontCast` is true, a call to `nn.Copy:type(type)` will not cast the module's `output` and `gradInput` Tensors to the new type. The default is false.
-
- <a name="nn.Narrow"></a>
-@@ -1432,10 +1432,10 @@ gpustr = torch.serialize(gpu)
- ```
-
- The module is located in the __nn__ package instead of __cunn__ as this allows
--it to be used in CPU-only enviroments, which are common for production models.
-+it to be used in CPU-only environments, which are common for production models.
-
- The module supports nested table `input` and `gradOutput` tensors originating from multiple devices.
--Each nested tensor in the returned `gradInput` will be transfered to the device its commensurate tensor in the `input`.
-+Each nested tensor in the returned `gradInput` will be transferred to the device its commensurate tensor in the `input`.
-
- The intended use-case is not for model-parallelism where the models are executed in parallel on multiple devices, but
- for sequential models where a single GPU doesn't have enough memory.
-diff --git a/lib/THNN/generic/SpatialUpSamplingNearest.c b/lib/THNN/generic/SpatialUpSamplingNearest.c
-index 7ef093c..b67c68d 100644
---- a/lib/THNN/generic/SpatialUpSamplingNearest.c
-+++ b/lib/THNN/generic/SpatialUpSamplingNearest.c
-@@ -14,7 +14,7 @@ void THNN_(SpatialUpSamplingNearest_updateOutput)(
- int yDim = input->nDimension-1;
-
- // dims
-- int idim = input->nDimension; // Gauranteed to be between 3 and 5
-+ int idim = input->nDimension; // Guaranteed to be between 3 and 5
- int osz0 = output->size[0];
- int osz1 = output->size[1];
- int osz2 = output->size[2];
-@@ -80,7 +80,7 @@ void THNN_(SpatialUpSamplingNearest_updateGradInput)(
- int yDim = gradInput->nDimension-1;
-
- // dims
-- int idim = gradInput->nDimension; // Gauranteed to be between 3 and 5
-+ int idim = gradInput->nDimension; // Guaranteed to be between 3 and 5
- int isz0 = gradInput->size[0];
- int isz1 = gradInput->size[1];
- int isz2 = gradInput->size[2];
-diff --git a/test.lua b/test.lua
-index e288e25..fa16c47 100644
---- a/test.lua
-+++ b/test.lua
-@@ -6306,9 +6306,9 @@ function nntest.addSingletonDimension()
- local resultArg = torch.Tensor()
- local resultR = nn.utils.addSingletonDimension(resultArg, tensor, dim)
- mytester:eq(resultArg:size():totable(), resultSize,
-- 'wrong content for random singleton dimention '..
-+ 'wrong content for random singleton dimension '..
- 'when the result is passed as argument')
-- mytester:eq(resultArg, result, 'wrong content for random singleton dimention '..
-+ mytester:eq(resultArg, result, 'wrong content for random singleton dimension '..
- 'when the result is passed as argument')
-
- mytester:eq(resultR == resultArg, true,
diff --git a/debian/patches/series b/debian/patches/series
index babcb03..5022a13 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1,4 +1,3 @@
THNN-cmake-add-soversion
THNN-assume-torch-is-present
cmake-only-generate-lua
-fix-spelling-errors
--
Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-science/packages/lua-torch-nn.git
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