[jira] [Updated] (MXNET-806) Undefined Behavior of mx.sym.where with shape-mismatched cond

[ https://issues.apache.org/jira/browse/MXNET-806?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Lin Yuan updated MXNET-806: --- Status: In Review (was: In Progress) > Undefined Behavior of mx.sym.where with shape-mismatched cond >

[jira] [Commented] (MXNET-806) Undefined Behavior of mx.sym.where with shape-mismatched cond

[ https://issues.apache.org/jira/browse/MXNET-806?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16580573#comment-16580573 ] Lin Yuan commented on MXNET-806: PR under review: https://github.com/apache/incubator-mxnet/pull/12174 >

[jira] [Updated] (MXNET-817) Python, Bug: Speech_recognition crashes in threaded_engine.h:379: Error: compute_ctc_loss, stat = execution failed

[ https://issues.apache.org/jira/browse/MXNET-817?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Vandana Kannan updated MXNET-817: - Status: In Progress (was: To Do) > Python, Bug: Speech_recognition crashes in

[jira] [Updated] (MXNET-806) Undefined Behavior of mx.sym.where with shape-mismatched cond

[ https://issues.apache.org/jira/browse/MXNET-806?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Lin Yuan updated MXNET-806: --- Status: In Progress (was: To Do) > Undefined Behavior of mx.sym.where with shape-mismatched cond >

[jira] [Updated] (MXNET-816) how to convert parameters dtype from float32 to float64 in gluon?

[ https://issues.apache.org/jira/browse/MXNET-816?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Lin Yuan updated MXNET-816: --- Status: In Progress (was: To Do) > how to convert parameters dtype from float32 to float64 in gluon? >

[jira] [Updated] (MXNET-798) Dangling outputs and dtype != float32: Gradient computation fails

[ https://issues.apache.org/jira/browse/MXNET-798?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Lin Yuan updated MXNET-798: --- Status: In Progress (was: To Do) > Dangling outputs and dtype != float32: Gradient computation fails >

[jira] [Updated] (MXNET-696) 43 Undefined names in Python code

[ https://issues.apache.org/jira/browse/MXNET-696?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Vandana Kannan updated MXNET-696: - Status: In Review (was: In Progress) > 43 Undefined names in Python code >

[jira] [Assigned] (MXNET-702) Dangling outputs and dtype != float32: Gradient computation fails

[ https://issues.apache.org/jira/browse/MXNET-702?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Vandana Kannan reassigned MXNET-702: Assignee: Lin Yuan (was: Vandana Kannan) > Dangling outputs and dtype != float32:

[jira] [Updated] (MXNET-633) Fix the begin_round for epochs while training in R

[ https://issues.apache.org/jira/browse/MXNET-633?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anirudh Acharya updated MXNET-633: -- Sprint: R-package 1 (08/15-08/27) 2 > Fix the begin_round for epochs while training in R >

[jira] [Updated] (MXNET-784) Need to have multiple loss function while training in R

[ https://issues.apache.org/jira/browse/MXNET-784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anirudh Acharya updated MXNET-784: -- Sprint: R-package 1 (08/15-08/27) 2 > Need to have multiple loss function while training in R >

[jira] [Updated] (MXNET-628) Fix LSTM Bucketing example

[ https://issues.apache.org/jira/browse/MXNET-628?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anirudh Acharya updated MXNET-628: -- Sprint: Apache Sprint 7, Apache Sprint 8, R-package 1 (08/15-08/27) 2 (was: Apache Sprint 7,

[jira] [Updated] (MXNET-611) R package frequently fails to install due to single gpg server

[ https://issues.apache.org/jira/browse/MXNET-611?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anirudh Acharya updated MXNET-611: -- Resolution: Fixed Status: Done (was: To Do) > R package frequently fails to install

[jira] [Assigned] (MXNET-633) Fix the begin_round for epochs while training in R

[ https://issues.apache.org/jira/browse/MXNET-633?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Ankit Khedia reassigned MXNET-633: -- Assignee: Ankit Khedia > Fix the begin_round for epochs while training in R >

[jira] [Updated] (MXNET-783) Describe input format for charRNN model

[ https://issues.apache.org/jira/browse/MXNET-783?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anirudh Acharya updated MXNET-783: -- Resolution: Fixed Status: Done (was: To Do) > Describe input format for charRNN model