- fixed yaml generation when adding new scripts

- improved get,cudnn
- a few minor clean ups

README.md

@@ -23,7 +23,7 @@ from [MLCommons projects](https://mlcommons.org) and [research papers](https://c
 in a unified way on any operating system with any software and hardware
 either natively or inside containers.
 
-Here are some most commonly used examples from the community:
+Here are some most commonly used examples from our users:
 
 ```bash
 pip install cmind
@@ -89,7 +89,7 @@ running experiments, processing logs, and reproducing results
 without thinking where and how they run.
 
 That is why we implemented CM as a [small Python library](https://github.com/mlcommons/ck/tree/master/cm) 
-with minimal dependencies (Python 3.7+, git, wget), simple Python API, StreamLit GUI and human-friendly command line.
+with minimal dependencies (Python 3.7+, git, wget), simple Python API, GUI and human-friendly command line.
 CM simply searches for CM scripts by tags or Unique IDs in all pulled Git repositories, automatically generates command lines 
 for a given script or tool on a given platform, updates all paths and environment variables, 
 runs a given automation either natively or inside automatically-generated containers

cm-mlops/automation/script/module.py

@@ -2125,6 +2125,16 @@ def add(self, i):
         tags_list = utils.convert_tags_to_list(i)
         if 'tags' in i: del(i['tags'])
 
+        if len(tags_list)==0:
+            if console:
+                x=input('Please specify a combination of unique tags separated by comma for this script: ')
+                x = x.strip()
+                if x!='':
+                    tags_list = x.split(',')
+
+        if len(tags_list)==0:
+            return {'return':1, 'error':'you must specify a combination of unique tags separate by comman using "--new_tags"'}
+
         # Add placeholder (use common action)
         ii['out']='con'
         ii['common']=True # Avoid recursion - use internal CM add function to add the script artifact
@@ -2150,18 +2160,19 @@ def add(self, i):
 
         # Check if preloaded meta exists
         meta = {
-                 'cache':False,
-                 'new_env_keys':[],
-                 'new_state_keys':[],
-                 'input_mapping':{},
-                 'docker_input_mapping':{},
-                 'deps':[],
-                 'prehook_deps':[],
-                 'posthook_deps':[],
-                 'post_deps':[],
-                 'versions':{},
-                 'variations':{},
-                 'input_description':{}
+                 'cache':False
+# 20240127: Grigori commented that because newly created script meta looks ugly
+#                 'new_env_keys':[],
+#                 'new_state_keys':[],
+#                 'input_mapping':{},
+#                 'docker_input_mapping':{},
+#                 'deps':[],
+#                 'prehook_deps':[],
+#                 'posthook_deps':[],
+#                 'post_deps':[],
+#                 'versions':{},
+#                 'variations':{},
+#                 'input_description':{}
                }
 
         fmeta = os.path.join(template_path, self.cmind.cfg['file_cmeta'])
@@ -2200,6 +2211,7 @@ def add(self, i):
             ii['yaml']=True
 
         ii['automation']='script,5b4e0237da074764'
+
         r_obj=self.cmind.access(ii)
         if r_obj['return']>0: return r_obj
 

cm-mlops/script/app-image-classification-onnx-py/README-extra.md

@@ -4,13 +4,14 @@ See [this tutorial](https://github.com/mlcommons/ck/blob/master/docs/tutorials/m
 
 # Collaborative testing
 
+## Windows 11
+
+* CUDA 11.8; cuDNN 8.7.0; ONNX GPU 1.16.1
+
 ## Windows 10
 
-* ONNX Runtime 1.13.1 with CPU and CUDA
-* CUDA 11.6
-* cuDNN 8.5.0.96
+* CUDA 11.6; cuDNN 8.6.0.96; ONNX GPU 1.13.1
 
 ## Ubuntu 22.04
 
-* ONNX Runtime 1.12.0 with CPU and CUDA
-* CUDA 11.3
+* CUDA 11.3; ONNX 1.12.0

cm-mlops/script/get-cudnn/README-extra.md

@@ -0,0 +1,3 @@
+# TBD
+
+We need to add detection of cuDNN version on Windows, Linux and MacOS

cm-mlops/script/get-cudnn/customize.py

@@ -28,6 +28,7 @@ def preprocess(i):
 
        libfilename = extra_pre + 'cudnn.' +extra_ext
        env['CM_CUDNN_VERSION'] = 'vdetected'
+
        if os.path.exists(os.path.join(cuda_path_lib, libfilename)):
            env['CM_CUDA_PATH_LIB_CUDNN'] = env['CM_CUDA_PATH_LIB']
            return {'return': 0}

cm-mlops/script/get-generic-python-lib/customize.py

@@ -15,6 +15,7 @@ def preprocess(i):
         return automation._available_variations({'meta':meta})
 
     if package_name == "onnxruntime_gpu":
+        # https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements
         cuda_version_split = env['CM_CUDA_VERSION'].split(".")
         if int(cuda_version_split[0]) >= 12:
             # env['CM_INSTALL_ONNXRUNTIME_GPU_FROM_SRC'] = "yes"

cm/cmind/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "1.6.0"
+__version__ = "1.6.0.1"
 
 from cmind.core import access
 from cmind.core import error

cmr.yaml

@@ -2,4 +2,4 @@ alias: mlcommons@ck
 git: true
 prefix: cm-mlops
 uid: a4705959af8e447a
-version: 1.5.4
+version: 1.6.0