[incubator-mxnet] branch master updated: Document the newly added env variable (#13049)

[an...@apache.org]

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anirudh2290 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
     new 91c1f82  Document the newly added env variable (#13049)
91c1f82 is described below

commit 91c1f821c7816d59d666d21549ac524c863c46b2
Author: Lin Yuan <ap...@gmail.com>
AuthorDate: Tue Nov 6 12:19:28 2018 -0800

    Document the newly added env variable (#13049)
    
    * add env variable to choose deterministic cudnn alg
    
    * set default value to false
    
    * fix build failure in Windows GPU
    
    * revert the previous change
    
    * only check determinism in CUDNN 7.x release
    
    * Add cudnn version check
    
    * fix lint error
    
    * document env variable MXNET_ENFORCE_DETERMINISM
    
    * use cudnnGet instead of cudnnFind when determinism required
    
    * Revert "use cudnnGet instead of cudnnFind when determinism required"
    
    This reverts commit d1bdf0f38f50b8c499f22ae1d50770b819f27678.
---
 docs/faq/env_var.md | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/docs/faq/env_var.md b/docs/faq/env_var.md
index 92cf493..e373377 100644
--- a/docs/faq/env_var.md
+++ b/docs/faq/env_var.md
@@ -196,6 +196,12 @@ When USE_PROFILER is enabled in Makefile or CMake, the following environments ca
   - Flag to enable or disable MKLDNN accelerator. On by default.
   - Only applies to mxnet that has been compiled with MKLDNN (```pip install mxnet-mkl``` or built from source with ```USE_MKLDNN=1```)
 
+* MXNET_ENFORCE_DETERMINISM
+  - Values: 0(false) or 1(true) ```(default=0)```
+  - If set to true, MXNet will only use deterministic algorithms in forward and backward computation.
+  If no such algorithm exists given other constraints, MXNet will error out. This variable affects the choice
+  of CUDNN convolution algorithms. Please see [CUDNN developer guide](https://docs.nvidia.com/deeplearning/sdk/cudnn-developer-guide/index.html) for more details.
+
 Settings for Minimum Memory Usage
 ---------------------------------
 - Make sure ```min(MXNET_EXEC_NUM_TEMP, MXNET_GPU_WORKER_NTHREADS) = 1```