This document lists the release notes for MXNet-Neuron framework.
Date 12/1/2019
Issue: Compiler flags cannot be passed to compiler during compile call.- [RESOLVED: Compiler flags can be passed to compiler during compile call using “flags” option followed by a list of flags.]
Issue: Advanced CPU fallback option is a way to attempt to improve the number of operators on Inferentia. The default is currently set to on, which may cause failures.- [RESOLVED: This option is now off by default.]
Date: 11/25/2019
This version is available only in released DLAMI v26.0. Please update to latest version.
- Issue: Compiler flags cannot be passed to compiler during compile call.
- Issue: Advanced CPU fallback option is a way to attempt to improve the number of operators on Inferentia. The default is currently set to on, which may cause failures.
- Workaround: explicitly turn it off by setting compile option op_by_op_compiler_retry to 0.
- Issue: Temporary files are put in current directory when debug is enabled.
- Workaround: create a separate work directory and run the process from within the work directory
- Issue: When a model needs hardware resources (memory/neuron-cores) which cannot be allocated, the runtime daemon fails to load the model and enters an unstable state.
- Workaround: When runtime fails due to unavailable resources, manually restart neuron-rtd
- Issue: MXNet Model Server is not able to clean up Neuron RTD states after model is unloaded (deleted) from model server.
- Workaround: run “/opt/aws/neuron/bin/neuron-cli reset“ to clear Neuron RTD states after model is unloaded and server is shut down. This unloads all models and remove all created NeuronCore Groups.
- Issue: MXNet 1.5.1 may return inconsistent node names for some operators when they are the primary outputs of a Neuron subgraph. This causes failures during inference.
- Workaround : Use the
excl_node_names
compilation option to change the partitioning of the graph during compile so that these nodes are not the primary output of a neuron subgraph. See MXNet-Neuron Compilation API
compile_args = { 'excl_node_names': ["node_name_to_exclude"] }
- Workaround : Use the
The following models have successfully run on neuron-inferentia systems
- Resnet50 V1/V2
- Inception-V2/V3/V4
- Parallel-WaveNet
- Tacotron 2
- WaveRNN