Fix `Unregistered type : mrc::pymrc::coro::BoostFibersMainPyAwaitable…

…` error (#1869)

* Ensure `BoostFibersMainPyAwaitable` is registered by importing `mrc.core.coro`
* Work-around for undefined symbol link error with c-ares
* Fix paths to data files in validation scripts
* Fix path to C++ files for CI checks
* Replace usage of `ie.` to avoid documentation CI error

Closes #1868

## By Submitting this PR I confirm:
- I am familiar with the [Contributing Guidelines](https://github.com/nv-morpheus/Morpheus/blob/main/docs/source/developer_guide/contributing.md).
- When the PR is ready for review, new or existing tests cover these changes.
- When the PR is ready for review, the documentation is up to date with these changes.

Authors:
  - David Gardner (https://github.com/dagardner-nv)

Approvers:
  - Anuradha Karuppiah (https://github.com/AnuradhaKaruppiah)

URL: #1869

ci/scripts/common.sh

@@ -27,7 +27,7 @@ export PY_DIRS="${PY_ROOT} ci/scripts"
 export BASE_SHA=${CHANGE_TARGET:-${BASE_SHA:-$(${SCRIPT_DIR}/gitutils.py get_merge_target)}}
 export COMMIT_SHA=${GIT_COMMIT:-${COMMIT_SHA:-HEAD}}
 
-export CPP_FILE_REGEX='^(\.\/)?(examples|morpheus|tests)\/.*\.(cc|cpp|h|hpp)$'
+export CPP_FILE_REGEX='^(\.\/)?(examples|python|tests)\/.*\.(cc|cpp|h|hpp)$'
 export PYTHON_FILE_REGEX='^(\.\/)?(?!\.|build|external).*\.(py|pyx|pxd)$'
 
 # Use these options to skip any of the checks

conda/environments/all_cuda-121_arch-x86_64.yaml

@@ -17,6 +17,7 @@ dependencies:
 - benchmark=1.8.3
 - boto3
 - breathe=4.35.0
+- c-ares=1.32
 - ccache
 - clangdev=16
 - click>=8

conda/environments/dev_cuda-121_arch-x86_64.yaml

@@ -14,6 +14,7 @@ dependencies:
 - beautifulsoup4=4.12
 - benchmark=1.8.3
 - breathe=4.35.0
+- c-ares=1.32
 - ccache
 - clangdev=16
 - click>=8

dependencies.yaml

@@ -233,6 +233,7 @@ dependencies:
 
           # Non-Compiler Dependencies
           - automake=1.16.5 # Needed for DOCA build
+          - c-ares=1.32 # 1.33 causes an undefined symbol error
           - ccache
           - cmake=3.27
           - cuda-cudart-dev=12.1

docs/source/developer_guide/contributing.md

@@ -126,7 +126,7 @@ This workflow utilizes a Docker container to set up most dependencies ensuring a
    ```bash
    ./docker/run_container_dev.sh
    ```
-   1. The container tag follows the same rules as `build_container_dev.sh` and will default to the current `YYMMDD`. Specify the desired tag with `DOCKER_IMAGE_TAG`. i.e. `DOCKER_IMAGE_TAG=my_tag ./docker/run_container_dev.sh`
+   1. The container tag follows the same rules as `build_container_dev.sh` and will default to the current `YYMMDD`. Specify the desired tag with `DOCKER_IMAGE_TAG`. For example, `DOCKER_IMAGE_TAG=my_tag ./docker/run_container_dev.sh`
    2. This will automatically mount the current working directory to `/workspace`.
    3. Some of the validation tests require launching the Morpheus models Docker container within the Morpheus container. To enable this you will need to grant the Morpheus container access to your host OS's Docker socket file with:
       ```bash

python/morpheus/morpheus/_lib/stages/__init__.pyi

@@ -10,6 +10,7 @@ import morpheus._lib.stages
 import typing
 from morpheus._lib.common import FilterSource
 import morpheus._lib.common
+import mrc.core.coro
 import mrc.core.segment
 import os
 

python/morpheus/morpheus/_lib/stages/module.cpp

@@ -73,6 +73,9 @@ PYBIND11_MODULE(stages, _module)
     // Make sure to load mrc.core.segment to get ObjectProperties
     mrc::pymrc::import(_module, "mrc.core.segment");
 
+    // Import the mrc coro module
+    mrc::pymrc::import(_module, "mrc.core.coro");
+
     mrc::pymrc::from_import(_module, "morpheus._lib.common", "FilterSource");
 
     py::class_<mrc::segment::Object<AddClassificationsStageMM>,

scripts/validation/val-run-pipeline.sh

@@ -41,7 +41,7 @@ function run_pipeline_sid_minibert(){
       pipeline-nlp --model_seq_length=256 \
       from-file --filename=${INPUT_FILE} \
       deserialize \
-      preprocess --vocab_hash_file=${MORPHEUS_ROOT}/morpheus/data/bert-base-uncased-hash.txt --truncation=True --do_lower_case=True --add_special_tokens=False \
+      preprocess --vocab_hash_file=${MORPHEUS_ROOT}/python/morpheus/morpheus/data/bert-base-uncased-hash.txt --truncation=True --do_lower_case=True --add_special_tokens=False \
       ${INFERENCE_STAGE} \
       monitor --description "Inference Rate" --smoothing=0.001 --unit inf \
       add-class --prefix="si_" \
@@ -62,7 +62,7 @@ function run_pipeline_sid_bert(){
       pipeline-nlp --model_seq_length=256 \
       from-file --filename=${INPUT_FILE} \
       deserialize \
-      preprocess --vocab_hash_file=${MORPHEUS_ROOT}/morpheus/data/bert-base-cased-hash.txt --truncation=True --do_lower_case=False --add_special_tokens=False \
+      preprocess --vocab_hash_file=${MORPHEUS_ROOT}/python/morpheus/morpheus/data/bert-base-cased-hash.txt --truncation=True --do_lower_case=False --add_special_tokens=False \
       ${INFERENCE_STAGE} \
       monitor --description "Inference Rate" --smoothing=0.001 --unit inf \
       add-class --prefix="si_" \
@@ -80,7 +80,7 @@ function run_pipeline_abp_nvsmi(){
    VAL_OUTPUT=$5
 
    morpheus --log_level=DEBUG run --num_threads=$(nproc) --pipeline_batch_size=1024 --model_max_batch_size=1024 --use_cpp=${USE_CPP} \
-      pipeline-fil --columns_file=${MORPHEUS_ROOT}/morpheus/data/columns_fil.txt \
+      pipeline-fil --columns_file=${MORPHEUS_ROOT}/python/morpheus/morpheus/data/columns_fil.txt \
       from-file --filename=${INPUT_FILE} \
       deserialize \
       preprocess \
@@ -101,10 +101,10 @@ function run_pipeline_phishing_email(){
    VAL_OUTPUT=$5
 
    morpheus --log_level=DEBUG run --num_threads=$(nproc) --pipeline_batch_size=1024 --model_max_batch_size=32 --use_cpp=${USE_CPP} \
-      pipeline-nlp --model_seq_length=128 --labels_file=${MORPHEUS_ROOT}/morpheus/data/labels_phishing.txt \
+      pipeline-nlp --model_seq_length=128 --labels_file=${MORPHEUS_ROOT}/python/morpheus/morpheus/data/labels_phishing.txt \
       from-file --filename=${INPUT_FILE} \
       deserialize \
-      preprocess --vocab_hash_file=${MORPHEUS_ROOT}/morpheus/data/bert-base-uncased-hash.txt --truncation=True --do_lower_case=True --add_special_tokens=False \
+      preprocess --vocab_hash_file=${MORPHEUS_ROOT}/python/morpheus/morpheus/data/bert-base-uncased-hash.txt --truncation=True --do_lower_case=True --add_special_tokens=False \
       ${INFERENCE_STAGE} \
       monitor --description "Inference Rate" --smoothing=0.001 --unit inf \
       add-class --label=is_phishing --threshold=0.7 \
@@ -122,7 +122,7 @@ function run_pipeline_hammah_user123(){
    VAL_OUTPUT=$5
 
    morpheus --log_level=DEBUG run --num_threads=$(nproc) --pipeline_batch_size=1024 --model_max_batch_size=1024 --use_cpp=${USE_CPP} \
-      pipeline-ae --columns_file="${MORPHEUS_ROOT}/morpheus/data/columns_ae_cloudtrail.txt" --userid_filter="user123" --userid_column_name="userIdentitysessionContextsessionIssueruserName" --timestamp_column_name="event_dt" \
+      pipeline-ae --columns_file="${MORPHEUS_ROOT}/python/morpheus/morpheus/data/columns_ae_cloudtrail.txt" --userid_filter="user123" --userid_column_name="userIdentitysessionContextsessionIssueruserName" --timestamp_column_name="event_dt" \
       from-cloudtrail --input_glob="${MORPHEUS_ROOT}/models/datasets/validation-data/dfp-cloudtrail-*-input.csv" \
       train-ae --train_data_glob="${MORPHEUS_ROOT}/models/datasets/training-data/dfp-cloudtrail-*.csv" --source_stage_class=morpheus.stages.input.cloud_trail_source_stage.CloudTrailSourceStage --seed 42 \
       preprocess \
@@ -144,7 +144,7 @@ function run_pipeline_hammah_role-g(){
    VAL_OUTPUT=$5
 
    morpheus --log_level=DEBUG run --num_threads=$(nproc) --pipeline_batch_size=1024 --model_max_batch_size=1024 --use_cpp=${USE_CPP} \
-      pipeline-ae --columns_file="${MORPHEUS_ROOT}/morpheus/data/columns_ae_cloudtrail.txt" --userid_filter="role-g" --userid_column_name="userIdentitysessionContextsessionIssueruserName" --timestamp_column_name="event_dt" \
+      pipeline-ae --columns_file="${MORPHEUS_ROOT}/python/morpheus/morpheus/data/columns_ae_cloudtrail.txt" --userid_filter="role-g" --userid_column_name="userIdentitysessionContextsessionIssueruserName" --timestamp_column_name="event_dt" \
       from-cloudtrail --input_glob="${MORPHEUS_ROOT}/models/datasets/validation-data/dfp-cloudtrail-*-input.csv" \
       train-ae --train_data_glob="${MORPHEUS_ROOT}/models/datasets/training-data/dfp-cloudtrail-*.csv" --source_stage_class=morpheus.stages.input.cloud_trail_source_stage.CloudTrailSourceStage  --seed 42 \
       preprocess \