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More API Doc Edits #5886

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merged 15 commits into from
Apr 25, 2017
Merged

More API Doc Edits #5886

merged 15 commits into from
Apr 25, 2017

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jiajiechen
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@jiajiechen jiajiechen commented Apr 19, 2017

  • l2_normalization

  • Activation

  • BlockGrad (same as stop_gradient)

  • MakeLoss

@nswamy @zackchase @Roshrini @mli @madjam @piiswrong

"If it is set to ``channel``, the operator will compute an L2 norm for each channel in "
"the multidimensional array. "
"If it is set to ``spatial``, the operator will compute a cross channel norm for each "
"position in the multidimensional array.");
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suggest to move the long argument doc to the description of the function


out = data / sqrt(sum(data ** 2) + eps)

The parameter ``mode`` can specify the dimension along which to compute L2 norm.
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explain more about general n-d input

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also add a particular example such as l2normalize([[1,2,3],[2,3,4]]) = [[...]]]

w = Variable('w')
out = Activation(data = data, act_type = 'sigmoid')
cross_entropy = y * log(out) + (1 - y) * log(1 - out)
loss = MakeLoss(w * cross_entropy)
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change to something like:

assume out is the predicted output and label is the true label, then cross entropy can be defined by

cross_entropy = label * log(out) + (1 - label) * log(1 - out)

now create the loss

loss = MakeLoss(cross_entropy)

in additional, we can give a scale to loss by grad_scale=.1

also explain why Makeloss is needed, namely stop_gradient is called. also support scale

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@jiajiechen jiajiechen Apr 20, 2017

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Edited, Preview as below

screen shot 2017-04-20 at 1 32 04 pm

.MXNET_DESCRIBE("Get output from a symbol and pass 0 gradient back")
.MXNET_DESCRIBE(R"code(Stops gradient computation.

Stops the accumulated gradient of the inputs from flowing through this operator
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explain more what it means, best by examples

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@jiajiechen jiajiechen Apr 20, 2017

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Edited. Preview as below.

screen shot 2017-04-20 at 4 18 03 pm

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Hey thanks for contributions! Can you please check the comments and make the requested changes?

@@ -66,15 +66,17 @@ DMLC_REGISTER_PARAMETER(ActivationParam);

MXNET_REGISTER_OP_PROPERTY(Activation, ActivationProp)
.describe(R"code(Elementwise activation function.
The activation operations are applied elementwisely to each array elements. The
following types are supported:
The activation operations are applied elementwisely to each array elements.
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Hi "elementwisely" occurred frequently throughout the old docs but it's not a word :). Let's say "element-wise" instead (the proper term and standard on numpy docs). Thanks!

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Thanks! fixed!

for i in 0...N
out[i,:,:,...,:] = data[i,:,:,...,:] / sqrt(sum(data[i,:,:,...,:] ** 2) + eps)

with ``mode`` = ``channel``, it normalize each channel in the array by its L2 norm.::
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Conjugation issue: should say "it normalizes" as above (not "it normalize")

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Thanks! fixed!

for i in 0...N
out[:,i,:,...,:] = data[:,i,:,...,:] / sqrt(sum(data[:,i,:,...,:] ** 2) + eps)

with ``mode`` = ``spatial``, it normalize the cross channel norm for each position
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Conjugation issue: should say "it normalizes" as above (not "it normalize")

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Thanks! fixed!

DMLC_DECLARE_FIELD(valid_thresh).set_default(0.0f)
.describe("regard element valid when x > valid_thresh, this is "
"used only in valid normalization mode.");
.describe("Clip x to 0 when x <= valid_thresh, where x is the elements in the "
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Might be more intuitive if you could just say "clip each element in the array to 0 when it is less than valid_thresh.

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Thanks! fixed!

The activation operations are applied elementwisely to each array elements. The
following types are supported:
.describe(R"code(Element-wise activation function.
The activation operations are applied element-wisely to each array elements.
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suggest changing "element-wisely to each array elements" to "element-wise to each array element"

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Thanks Madan! Fixed

@zackchase
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zackchase commented Apr 20, 2017 via email

@@ -19,8 +19,60 @@ Operator* L2NormalizationProp::CreateOperator(Context ctx) const {
DMLC_REGISTER_PARAMETER(L2NormalizationParam);

MXNET_REGISTER_OP_PROPERTY(L2Normalization, L2NormalizationProp)
.describe("Set the l2 norm of each instance to a constant.")
.add_argument("data", "NDArray-or-Symbol", "Input data to the L2NormalizationOp.")
.describe(R"code(Normalize the input array using a L2 norm.
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suggest changing "a L2 norm" to "the L2 norm"

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Thanks! Fixed

@madjam madjam added the Doc label Apr 20, 2017
@mli
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mli commented Apr 21, 2017

@yajiedesign can you have a look why win gpu is failed, it is caused by test_operator_gpu.test_convolution_dilated_impulse_response

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@mli some accidental errors

@piiswrong piiswrong merged commit 2ea2f23 into apache:master Apr 25, 2017
cjolivier01 pushed a commit to cjolivier01/mxnet that referenced this pull request Apr 26, 2017
* edit activation doc

* doc l2_normalization

* edit MakeLoss doc

* edit blockgrad doc

* blockgrad fileline fix

* edit MakeLoss doc cont.

* doc change 'tensor' to 'multidimensional array'

* l2normalization doc improve

* makeloss doc improve, blockgrad doc improve

* fix doc in activation, l2_normalization, make_loss

* fix minor grammar

* use .describe to avoid build failure.
piiswrong pushed a commit that referenced this pull request May 16, 2017
…at64 as well as operator gtest framework (#5936)

* Batch Norm rewrite without mshadow as well as operator gtest framework

* performance testing

* lint fixes

* use CUDNN for this test

* remove superfluous omp define

* Fix file names in comments

* build, run, clean gtest works (although a test is failing)

* CR comments

* Adjust timing tests for more strenuous sample

* Remove temp resource allocation

* DeviceTensor3 added, forEachFast not yet converted

* DeviceTensor3 version working

* DeviceTensor3 working

* .

* Fix for use_global_stats

* fixed bug with testing suite for double (Float64)

* python unit tests working for batchnorm

* python unit tests

* Update documentation for mxnet.initializer.Mixed (#5937)

* Update documentation for SVMOutput. (#5931)

* Update documentation for SVMOutput.

* Update doc for SVMOutput - fix formatting.

* Adding install instruction for Ubuntu-CPU-Python (#5885)

* edit ndarray API docs (#5806)

* edit docs in broadcast_reduce_op

* edit docs in broadcast_reduce_op

* minor change

* lint fix

* fix

* mx.nd.ones

* mx.nd.repeat

* mx.nd.reverse

* add example in repeat

* optimizer update

* fix nanprod

* fix optimizer_op api doc

* fix reduce_op api doc

* fix nd.ones api doc

* mx.nd.repeat doc change

* Update broadcast_reduce_op.h

* Symbol docs fixes (#5930)

* symbol docs minor formatting changes

* deepcopy, infer_shape, infer_shape_partial docs modified

* Few more small fixes

* arithmetic functions fixes

* some more modifications

* changes after review

* small change

* grad function note added

* More API Doc Edits (#5886)

* edit activation doc

* doc l2_normalization

* edit MakeLoss doc

* edit blockgrad doc

* blockgrad fileline fix

* edit MakeLoss doc cont.

* doc change 'tensor' to 'multidimensional array'

* l2normalization doc improve

* makeloss doc improve, blockgrad doc improve

* fix doc in activation, l2_normalization, make_loss

* fix minor grammar

* use .describe to avoid build failure.

* Update documentation for mxnet.image.imdecode (#5957)

* Update documentation for mxnet.image.imdecode

* Update documentation for mxnet.image.imdecode (clarify that we need OpenCV and not the CV2 Python library)

* Fix script by adding path to Dockerfile (#5958)

* Clean install script

* Add test for pip installations

* Remove debug statements & comments

* Make test runnable as script and from framework

* Fix path to Dockerfiles

* Putting failing cases at the end

* Update doc for Custom operator. (#5875)

* Update doc for Custom operator.

* Update doc for Custom operator.

* Fix formating in doc for Custom operator.

* Fix formating in doc for Custom operator.

* Minor change to ndarray.Custom documentation.

* Minor edit in doc for Custom operator.

* Minor change to doc for Custom operator. Data is 'NDArray-or-Symbol'.

* Minor formatting change for Custom operator documentation.

* For Custom operator doc, move example into ndarray_doc.py.

* Minor change in Custom operator documentation

* Improve the doc of pick + Update dmlc-core (#5946)

* Add PickParam to fix the docstring and the initial value for axis

* Update dmlc-core

* Update dmlc-core

* Image docs modified (#5973)

* imageIter doc modified

* edited imageiter

* ADD missing Libri_sample.json, FIX minor bugs in speech_recognition example (#5962)

* [KVStore] Add support for other data types (#5818)

* Fix kvstore type

* Fix lint

* Parse inputs to DataDesc

* Make module support dtype

* Fix lint

* Add default dtype in Comm

* Fix lint

* Revert rename

* [cpp-package] Add C++ basic tutorial and build instruction (#5971)

* Add C++ basic tutorial and build instruction

* Remove binaries

* Fix lint

* Avoid sign-compare

* Update documentation for mxnet.metric.np (#5977)

* Getting rid of identity (#5935)

* Activation ops (#5938)

* [Ops] Add op: 'relu'

* Add op: 'sigmoid'

* Introduce 'kernel_launch_op'

* Add tests and describe; move it to elemwise_unary_op

* Fix GPU version

* Convert caffe AbsVal to mx.symbol.abs in caffe converter (#5984)

* Correction to LSTMCell docstring (#5986)

* [Module] fix input_grads order (#5980)

* fix input_grads order + update dmlc-core

* set label to be optional

* update env_var doc (#5964)

* Adjusting make, Callback removed

* batch norm gpu testing

* Batch Norm rewrite without mshadow as well as operator gtest framework

* performance testing

* lint fixes

* use CUDNN for this test

* remove superfluous omp define

* Fix file names in comments

* build, run, clean gtest works (although a test is failing)

* CR comments

* Adjust timing tests for more strenuous sample

* Remove temp resource allocation

* rearrange source into cc and cu files

* lint fixes

* Trigger build

* Use latest mshadow

* temporarily revert channel position parameter field

* Add more tests for batchnorm

* Add more tests for batchnorm

* test_operator_gpu working for all types

* Compiles after AccReal

* Compiles after AccReal

* All tests working

* All tests working

* build, run, clean gtest works (although a test is failing)

* vc++ requires explicit int type for omp for loop

* Repair cpp-package

* signed/unsigned fixed in cuda file

* lint fixes in tests and cpp-package directories

* more lint

* use IsWriting() helper

* Fall-through for unsupported MKL shapes/types

* Fall-through for unsupported MKL shapes/types

* cleaner mkl_off approach

* Warning only whem MKL is requested

* Warning only whem MKL is requested

* lint

* ..

* python problem fixed

* python problem fixed

* Merge branch 'batchnorm' into batchnorm_pr

# Conflicts:
#	src/operator/batch_norm.cc
#	src/operator/batch_norm.cu
#	tests/cpp/operator/batchnorm_test.cc

* lint fix

* lint fix

* lint fix

* lint fix

* lint fix

* Fix visual c++ compile problem

* .

* .

* All unit tests pass again

* lint fix

* fix strange compile errors in CUDNN batchnorm header

* FInish using flags instead of bools

* lint

* Fix timing pass count for forward pass

* Fix R script install roxygen problem

* code formatting, addition of doc strings is causing IDE to add spaces before the calls

* removed commented

* cr comments

* Change back to compilable code

* For CPU mode, store as invstd

* move testing code around a little

* lint fix

* Use AccReal in some places to avoid fp16 problems

* Fix minor invstd problem in cuda version

* remove unused scale param

* add permutation unit test, handle cudnn doesn't like 3D

* .

* lint

* .

* Remove mkl_off

* lint fix and time cudnn when enabled
saurabh3949 pushed a commit to saurabh3949/mxnet that referenced this pull request May 23, 2017
…at64 as well as operator gtest framework (apache#5936)

* Batch Norm rewrite without mshadow as well as operator gtest framework

* performance testing

* lint fixes

* use CUDNN for this test

* remove superfluous omp define

* Fix file names in comments

* build, run, clean gtest works (although a test is failing)

* CR comments

* Adjust timing tests for more strenuous sample

* Remove temp resource allocation

* DeviceTensor3 added, forEachFast not yet converted

* DeviceTensor3 version working

* DeviceTensor3 working

* .

* Fix for use_global_stats

* fixed bug with testing suite for double (Float64)

* python unit tests working for batchnorm

* python unit tests

* Update documentation for mxnet.initializer.Mixed (apache#5937)

* Update documentation for SVMOutput. (apache#5931)

* Update documentation for SVMOutput.

* Update doc for SVMOutput - fix formatting.

* Adding install instruction for Ubuntu-CPU-Python (apache#5885)

* edit ndarray API docs (apache#5806)

* edit docs in broadcast_reduce_op

* edit docs in broadcast_reduce_op

* minor change

* lint fix

* fix

* mx.nd.ones

* mx.nd.repeat

* mx.nd.reverse

* add example in repeat

* optimizer update

* fix nanprod

* fix optimizer_op api doc

* fix reduce_op api doc

* fix nd.ones api doc

* mx.nd.repeat doc change

* Update broadcast_reduce_op.h

* Symbol docs fixes (apache#5930)

* symbol docs minor formatting changes

* deepcopy, infer_shape, infer_shape_partial docs modified

* Few more small fixes

* arithmetic functions fixes

* some more modifications

* changes after review

* small change

* grad function note added

* More API Doc Edits (apache#5886)

* edit activation doc

* doc l2_normalization

* edit MakeLoss doc

* edit blockgrad doc

* blockgrad fileline fix

* edit MakeLoss doc cont.

* doc change 'tensor' to 'multidimensional array'

* l2normalization doc improve

* makeloss doc improve, blockgrad doc improve

* fix doc in activation, l2_normalization, make_loss

* fix minor grammar

* use .describe to avoid build failure.

* Update documentation for mxnet.image.imdecode (apache#5957)

* Update documentation for mxnet.image.imdecode

* Update documentation for mxnet.image.imdecode (clarify that we need OpenCV and not the CV2 Python library)

* Fix script by adding path to Dockerfile (apache#5958)

* Clean install script

* Add test for pip installations

* Remove debug statements & comments

* Make test runnable as script and from framework

* Fix path to Dockerfiles

* Putting failing cases at the end

* Update doc for Custom operator. (apache#5875)

* Update doc for Custom operator.

* Update doc for Custom operator.

* Fix formating in doc for Custom operator.

* Fix formating in doc for Custom operator.

* Minor change to ndarray.Custom documentation.

* Minor edit in doc for Custom operator.

* Minor change to doc for Custom operator. Data is 'NDArray-or-Symbol'.

* Minor formatting change for Custom operator documentation.

* For Custom operator doc, move example into ndarray_doc.py.

* Minor change in Custom operator documentation

* Improve the doc of pick + Update dmlc-core (apache#5946)

* Add PickParam to fix the docstring and the initial value for axis

* Update dmlc-core

* Update dmlc-core

* Image docs modified (apache#5973)

* imageIter doc modified

* edited imageiter

* ADD missing Libri_sample.json, FIX minor bugs in speech_recognition example (apache#5962)

* [KVStore] Add support for other data types (apache#5818)

* Fix kvstore type

* Fix lint

* Parse inputs to DataDesc

* Make module support dtype

* Fix lint

* Add default dtype in Comm

* Fix lint

* Revert rename

* [cpp-package] Add C++ basic tutorial and build instruction (apache#5971)

* Add C++ basic tutorial and build instruction

* Remove binaries

* Fix lint

* Avoid sign-compare

* Update documentation for mxnet.metric.np (apache#5977)

* Getting rid of identity (apache#5935)

* Activation ops (apache#5938)

* [Ops] Add op: 'relu'

* Add op: 'sigmoid'

* Introduce 'kernel_launch_op'

* Add tests and describe; move it to elemwise_unary_op

* Fix GPU version

* Convert caffe AbsVal to mx.symbol.abs in caffe converter (apache#5984)

* Correction to LSTMCell docstring (apache#5986)

* [Module] fix input_grads order (apache#5980)

* fix input_grads order + update dmlc-core

* set label to be optional

* update env_var doc (apache#5964)

* Adjusting make, Callback removed

* batch norm gpu testing

* Batch Norm rewrite without mshadow as well as operator gtest framework

* performance testing

* lint fixes

* use CUDNN for this test

* remove superfluous omp define

* Fix file names in comments

* build, run, clean gtest works (although a test is failing)

* CR comments

* Adjust timing tests for more strenuous sample

* Remove temp resource allocation

* rearrange source into cc and cu files

* lint fixes

* Trigger build

* Use latest mshadow

* temporarily revert channel position parameter field

* Add more tests for batchnorm

* Add more tests for batchnorm

* test_operator_gpu working for all types

* Compiles after AccReal

* Compiles after AccReal

* All tests working

* All tests working

* build, run, clean gtest works (although a test is failing)

* vc++ requires explicit int type for omp for loop

* Repair cpp-package

* signed/unsigned fixed in cuda file

* lint fixes in tests and cpp-package directories

* more lint

* use IsWriting() helper

* Fall-through for unsupported MKL shapes/types

* Fall-through for unsupported MKL shapes/types

* cleaner mkl_off approach

* Warning only whem MKL is requested

* Warning only whem MKL is requested

* lint

* ..

* python problem fixed

* python problem fixed

* Merge branch 'batchnorm' into batchnorm_pr

# Conflicts:
#	src/operator/batch_norm.cc
#	src/operator/batch_norm.cu
#	tests/cpp/operator/batchnorm_test.cc

* lint fix

* lint fix

* lint fix

* lint fix

* lint fix

* Fix visual c++ compile problem

* .

* .

* All unit tests pass again

* lint fix

* fix strange compile errors in CUDNN batchnorm header

* FInish using flags instead of bools

* lint

* Fix timing pass count for forward pass

* Fix R script install roxygen problem

* code formatting, addition of doc strings is causing IDE to add spaces before the calls

* removed commented

* cr comments

* Change back to compilable code

* For CPU mode, store as invstd

* move testing code around a little

* lint fix

* Use AccReal in some places to avoid fp16 problems

* Fix minor invstd problem in cuda version

* remove unused scale param

* add permutation unit test, handle cudnn doesn't like 3D

* .

* lint

* .

* Remove mkl_off

* lint fix and time cudnn when enabled
Guneet-Dhillon pushed a commit to Guneet-Dhillon/mxnet that referenced this pull request Sep 13, 2017
* edit activation doc

* doc l2_normalization

* edit MakeLoss doc

* edit blockgrad doc

* blockgrad fileline fix

* edit MakeLoss doc cont.

* doc change 'tensor' to 'multidimensional array'

* l2normalization doc improve

* makeloss doc improve, blockgrad doc improve

* fix doc in activation, l2_normalization, make_loss

* fix minor grammar

* use .describe to avoid build failure.
Guneet-Dhillon pushed a commit to Guneet-Dhillon/mxnet that referenced this pull request Sep 13, 2017
…at64 as well as operator gtest framework (apache#5936)

* Batch Norm rewrite without mshadow as well as operator gtest framework

* performance testing

* lint fixes

* use CUDNN for this test

* remove superfluous omp define

* Fix file names in comments

* build, run, clean gtest works (although a test is failing)

* CR comments

* Adjust timing tests for more strenuous sample

* Remove temp resource allocation

* DeviceTensor3 added, forEachFast not yet converted

* DeviceTensor3 version working

* DeviceTensor3 working

* .

* Fix for use_global_stats

* fixed bug with testing suite for double (Float64)

* python unit tests working for batchnorm

* python unit tests

* Update documentation for mxnet.initializer.Mixed (apache#5937)

* Update documentation for SVMOutput. (apache#5931)

* Update documentation for SVMOutput.

* Update doc for SVMOutput - fix formatting.

* Adding install instruction for Ubuntu-CPU-Python (apache#5885)

* edit ndarray API docs (apache#5806)

* edit docs in broadcast_reduce_op

* edit docs in broadcast_reduce_op

* minor change

* lint fix

* fix

* mx.nd.ones

* mx.nd.repeat

* mx.nd.reverse

* add example in repeat

* optimizer update

* fix nanprod

* fix optimizer_op api doc

* fix reduce_op api doc

* fix nd.ones api doc

* mx.nd.repeat doc change

* Update broadcast_reduce_op.h

* Symbol docs fixes (apache#5930)

* symbol docs minor formatting changes

* deepcopy, infer_shape, infer_shape_partial docs modified

* Few more small fixes

* arithmetic functions fixes

* some more modifications

* changes after review

* small change

* grad function note added

* More API Doc Edits (apache#5886)

* edit activation doc

* doc l2_normalization

* edit MakeLoss doc

* edit blockgrad doc

* blockgrad fileline fix

* edit MakeLoss doc cont.

* doc change 'tensor' to 'multidimensional array'

* l2normalization doc improve

* makeloss doc improve, blockgrad doc improve

* fix doc in activation, l2_normalization, make_loss

* fix minor grammar

* use .describe to avoid build failure.

* Update documentation for mxnet.image.imdecode (apache#5957)

* Update documentation for mxnet.image.imdecode

* Update documentation for mxnet.image.imdecode (clarify that we need OpenCV and not the CV2 Python library)

* Fix script by adding path to Dockerfile (apache#5958)

* Clean install script

* Add test for pip installations

* Remove debug statements & comments

* Make test runnable as script and from framework

* Fix path to Dockerfiles

* Putting failing cases at the end

* Update doc for Custom operator. (apache#5875)

* Update doc for Custom operator.

* Update doc for Custom operator.

* Fix formating in doc for Custom operator.

* Fix formating in doc for Custom operator.

* Minor change to ndarray.Custom documentation.

* Minor edit in doc for Custom operator.

* Minor change to doc for Custom operator. Data is 'NDArray-or-Symbol'.

* Minor formatting change for Custom operator documentation.

* For Custom operator doc, move example into ndarray_doc.py.

* Minor change in Custom operator documentation

* Improve the doc of pick + Update dmlc-core (apache#5946)

* Add PickParam to fix the docstring and the initial value for axis

* Update dmlc-core

* Update dmlc-core

* Image docs modified (apache#5973)

* imageIter doc modified

* edited imageiter

* ADD missing Libri_sample.json, FIX minor bugs in speech_recognition example (apache#5962)

* [KVStore] Add support for other data types (apache#5818)

* Fix kvstore type

* Fix lint

* Parse inputs to DataDesc

* Make module support dtype

* Fix lint

* Add default dtype in Comm

* Fix lint

* Revert rename

* [cpp-package] Add C++ basic tutorial and build instruction (apache#5971)

* Add C++ basic tutorial and build instruction

* Remove binaries

* Fix lint

* Avoid sign-compare

* Update documentation for mxnet.metric.np (apache#5977)

* Getting rid of identity (apache#5935)

* Activation ops (apache#5938)

* [Ops] Add op: 'relu'

* Add op: 'sigmoid'

* Introduce 'kernel_launch_op'

* Add tests and describe; move it to elemwise_unary_op

* Fix GPU version

* Convert caffe AbsVal to mx.symbol.abs in caffe converter (apache#5984)

* Correction to LSTMCell docstring (apache#5986)

* [Module] fix input_grads order (apache#5980)

* fix input_grads order + update dmlc-core

* set label to be optional

* update env_var doc (apache#5964)

* Adjusting make, Callback removed

* batch norm gpu testing

* Batch Norm rewrite without mshadow as well as operator gtest framework

* performance testing

* lint fixes

* use CUDNN for this test

* remove superfluous omp define

* Fix file names in comments

* build, run, clean gtest works (although a test is failing)

* CR comments

* Adjust timing tests for more strenuous sample

* Remove temp resource allocation

* rearrange source into cc and cu files

* lint fixes

* Trigger build

* Use latest mshadow

* temporarily revert channel position parameter field

* Add more tests for batchnorm

* Add more tests for batchnorm

* test_operator_gpu working for all types

* Compiles after AccReal

* Compiles after AccReal

* All tests working

* All tests working

* build, run, clean gtest works (although a test is failing)

* vc++ requires explicit int type for omp for loop

* Repair cpp-package

* signed/unsigned fixed in cuda file

* lint fixes in tests and cpp-package directories

* more lint

* use IsWriting() helper

* Fall-through for unsupported MKL shapes/types

* Fall-through for unsupported MKL shapes/types

* cleaner mkl_off approach

* Warning only whem MKL is requested

* Warning only whem MKL is requested

* lint

* ..

* python problem fixed

* python problem fixed

* Merge branch 'batchnorm' into batchnorm_pr

# Conflicts:
#	src/operator/batch_norm.cc
#	src/operator/batch_norm.cu
#	tests/cpp/operator/batchnorm_test.cc

* lint fix

* lint fix

* lint fix

* lint fix

* lint fix

* Fix visual c++ compile problem

* .

* .

* All unit tests pass again

* lint fix

* fix strange compile errors in CUDNN batchnorm header

* FInish using flags instead of bools

* lint

* Fix timing pass count for forward pass

* Fix R script install roxygen problem

* code formatting, addition of doc strings is causing IDE to add spaces before the calls

* removed commented

* cr comments

* Change back to compilable code

* For CPU mode, store as invstd

* move testing code around a little

* lint fix

* Use AccReal in some places to avoid fp16 problems

* Fix minor invstd problem in cuda version

* remove unused scale param

* add permutation unit test, handle cudnn doesn't like 3D

* .

* lint

* .

* Remove mkl_off

* lint fix and time cudnn when enabled
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6 participants