GitLab

Two input version of the broadcast operator to handle dynamic shapes
Added comments to describe the versions of the broadcast operator
Dynamic broadcast only handles broadcasting a static 1D shape tensor into the other input shape

Can be enabled via environment variable MIGRAPHX_ENABLE_NHWC

Allows for a model to be converted to the same opset but turn on infer_shapes through
onnx. This allows us to get an idea of what should be valid for the output of nodes
in a network.

Usecase:

python3 tools/convert_onnx_version.py --model <model_name> --opset=<same_as_model> --infer_shapes --output <new_model_name>

Trying to keep the PRs separate

Newer split moves the split attribute to an input. In this case we check the
number of input args then.

It doesn't look like this functionality is used. Probably was a thing in
ONNX that became deprecated when they adopted NumPy-like broadcasting.

change to shape::operator== makes it so this will work the same

Local Threads of multiples 32 were introduced in #1348
But LocalThreads that are not multiple of 64 are causing correctness issues.

Upgraded Dockerfiles and fixed tidy issues to make Ubuntu 20.04 and ROCm 5.3.0 the default 

Merge branch 'dyn_ref_multibroadcast' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into dyn_ref_multibroadcast

updated GPU pad to now use JIT version.
added range functions for JIT kernels.

Fixes an observed regression error on certain Frozen Protobuf models due to PR 1280

use_dynamic_same_auto_pad was removed from convolution, but the driver models still retain the fields. This PR regenerates the files so that they are compatible again.