MMD OD/IS sdk, cli examples; Update HuggingFace Classification examples

cli/foundation-models/system/finetune/image-classification/multiclass-classification/hftransformers-fridgeobjects-multiclass-classification-pipeline.yaml

@@ -6,7 +6,7 @@ experiment_name: AzureML-Train-Finetune-Vision-MultiClass-Samples
 inputs:
   # # model - specify the foundation model available in the azureml system registry
   mlflow_model_path:
-    path: azureml://registries/azureml-preview/models/google-vit-base-patch16-224/versions/1
+    path: azureml://registries/azureml-staging/models/google-vit-base-patch16-224/versions/1
     type: mlflow_model
   # model_name: microsoft/beit-base-patch16-224-pt22k-ft22k
   # dataset files
@@ -22,7 +22,7 @@ inputs:
     type: uri_file
   # compute
   compute_model_import: sample-model-import-cluster
-  compute_finetune: sample-finetune-cluster-gpu-nc6
+  compute_finetune: sample-finetune-cluster-gpu
 
 outputs:
   # map the output of the fine tuning job to the output of pipeline job so that we can easily register the fine tuned model
@@ -32,12 +32,12 @@ outputs:
 
 settings:
   force_rerun: true
-  default_compute: azureml:sample-finetune-cluster-gpu-nc6
+  default_compute: azureml:sample-finetune-cluster-gpu
 
 jobs:
   huggingface_transformers_model_finetune_job:
     type: pipeline
-    component: azureml://registries/azureml-preview/components/image_classification_pipeline/labels/latest
+    component: azureml://registries/azureml-staging/components/image_classification_pipeline/labels/latest
     inputs:
 
       # Compute
@@ -57,7 +57,6 @@ jobs:
       training_data: ${{parent.inputs.training_data}}
       validation_data: ${{parent.inputs.validation_data}}
 
-      auto_hyperparameter_selection: False
       image_width: -1
       image_height: -1
       metric_for_best_model: accuracy

cli/foundation-models/system/finetune/image-classification/multiclass-classification/hftransformers-fridgeobjects-multiclass-classification.sh

@@ -2,16 +2,16 @@
 set -x
 
 # script inputs
-registry_name="azureml-preview"
+registry_name="azureml-staging"
 subscription_id="<SUBSCRIPTION_ID>"
 resource_group_name="<RESOURCE_GROUP>"
 workspace_name="<WORKSPACE_NAME>"
 
 compute_cluster_model_import="sample-model-import-cluster"
-compute_cluster_finetune="sample-finetune-cluster-gpu-nc6"
+compute_cluster_finetune="sample-finetune-cluster-gpu"
 # if above compute cluster does not exist, create it with the following vm size
 compute_model_import_sku="Standard_D12"
-compute_finetune_sku="Standard_NC6"
+compute_finetune_sku="STANDARD_NC6s_v3"
 # This is the number of GPUs in a single node of the selected 'vm_size' compute. 
 # Setting this to less than the number of GPUs will result in underutilized GPUs, taking longer to train.
 # Setting this to more than the number of GPUs will result in an error.
@@ -38,12 +38,12 @@ huggingface_sample_request_data="./huggingface_sample_request_data.json"
 # finetuning job parameters
 finetuning_pipeline_component="transformers_image_classification_pipeline"
 # Training settings
-number_of_gpu_to_use_finetuning=$gpus_per_node # set to the number of GPUs available in the compute
+process_count_per_instance=$gpus_per_node # set to the number of GPUs available in the compute
 
 # 1. Install dependencies
 pip install azure-ai-ml==1.8.0
 pip install azure-identity==1.13.0
-pip install datasets==2.3.2
+pip install datasets==2.12.0
 
 unameOut=$(uname -a)
 case "${unameOut}" in

cli/foundation-models/system/finetune/image-classification/multiclass-classification/readme.md

@@ -7,8 +7,8 @@ For using this component, run the shell script file `bash ./hftransformers-fridg
 Currently following models are supported:
 | Model Name | Source |
 | ------ | ---------- |
-| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml-preview/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml-preview/models/microsoft-swinv2-base-patch4-window12-192-22k/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml-preview/models/facebook-deit-base-patch16-224/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml-preview/models/google-vit-base-patch16-224/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [Image classification models from Huggingface](https://huggingface.co/models?pipeline_tag=image-classification&sort=downloads) | HuggingFace |
+| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml-staging/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml-staging/models/microsoft-swinv2-base-patch4-window12-192-22k/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml-staging/models/facebook-deit-base-patch16-224/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml-staging/models/google-vit-base-patch16-224/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [Image classification models from Huggingface's Transformer library](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers)| HuggingFace |

cli/foundation-models/system/finetune/image-classification/multilabel-classification/hftransformers-fridgeobjects-multilabel-classification-pipeline.yaml

@@ -6,7 +6,7 @@ experiment_name: AzureML-Train-Finetune-Vision-MultiLabel-Samples
 inputs:
   # # model - specify the foundation model available in the azureml system registry
   mlflow_model_path:
-    path: azureml://registries/azureml-preview/models/google-vit-base-patch16-224/versions/1
+    path: azureml://registries/azureml-staging/models/google-vit-base-patch16-224/versions/1
     type: mlflow_model
   # model_name: microsoft/beit-base-patch16-224-pt22k-ft22k
   # dataset files
@@ -22,7 +22,7 @@ inputs:
     type: uri_file
   # compute
   compute_model_import: sample-model-import-cluster
-  compute_finetune: sample-finetune-cluster-gpu-nc6
+  compute_finetune: sample-finetune-cluster-gpu
 
 
 outputs:
@@ -33,12 +33,12 @@ outputs:
 
 settings:
   force_rerun: true
-  default_compute: azureml:sample-finetune-cluster-gpu-nc6
+  default_compute: azureml:sample-finetune-cluster-gpu
 
 jobs:
   huggingface_transformers_model_finetune_job:
     type: pipeline
-    component: azureml://registries/azureml-preview/components/image_classification_pipeline/labels/latest
+    component: azureml://registries/azureml-staging/components/image_classification_pipeline/labels/latest
     inputs:
 
       # Compute
@@ -58,7 +58,6 @@ jobs:
       training_data: ${{parent.inputs.training_data}}
       validation_data: ${{parent.inputs.validation_data}}
 
-      auto_hyperparameter_selection: False
       image_width: -1
       image_height: -1
       metric_for_best_model: iou

cli/foundation-models/system/finetune/image-classification/multilabel-classification/hftransformers-fridgeobjects-multilabel-classification.sh

@@ -2,16 +2,16 @@
 set -x
 
 # script inputs
-registry_name="azureml-preview"
+registry_name="azureml-staging"
 subscription_id="<SUBSCRIPTION_ID>"
 resource_group_name="<RESOURCE_GROUP>"
 workspace_name="<WORKSPACE_NAME>"
 
 compute_cluster_model_import="sample-model-import-cluster"
-compute_cluster_finetune="sample-finetune-cluster-gpu-nc6"
+compute_cluster_finetune="sample-finetune-cluster-gpu"
 # if above compute cluster does not exist, create it with the following vm size
 compute_model_import_sku="Standard_D12"
-compute_finetune_sku="Standard_NC6"
+compute_finetune_sku="STANDARD_NC6s_v3"
 # This is the number of GPUs in a single node of the selected 'vm_size' compute. 
 # Setting this to less than the number of GPUs will result in underutilized GPUs, taking longer to train.
 # Setting this to more than the number of GPUs will result in an error.
@@ -38,12 +38,12 @@ huggingface_sample_request_data="./huggingface_sample_request_data.json"
 # finetuning job parameters
 finetuning_pipeline_component="transformers_image_classification_pipeline"
 # Training settings
-number_of_gpu_to_use_finetuning=$gpus_per_node # set to the number of GPUs available in the compute
+process_count_per_instance=$gpus_per_node # set to the number of GPUs available in the compute
 
 # 1. Install dependencies
 pip install azure-ai-ml==1.8.0
 pip install azure-identity==1.13.0
-pip install datasets==2.3.2
+pip install datasets==2.12.0
 
 unameOut=$(uname -a)
 case "${unameOut}" in

cli/foundation-models/system/finetune/image-classification/multilabel-classification/readme.md

@@ -7,8 +7,8 @@ For using this component, run the shell script file `bash ./hftransformers-fridg
 Currently following models are supported:
 | Model Name | Source |
 | ------ | ---------- |
-| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml-preview/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml-preview/models/microsoft-swinv2-base-patch4-window12-192-22k/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml-preview/models/facebook-deit-base-patch16-224/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml-preview/models/google-vit-base-patch16-224/version/1?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-preview registry |
-| [Image classification models from Huggingface](https://huggingface.co/models?pipeline_tag=image-classification&sort=downloads) | HuggingFace |
+| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml-staging/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml-staging/models/microsoft-swinv2-base-patch4-window12-192-22k/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml-staging/models/facebook-deit-base-patch16-224/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml-staging/models/google-vit-base-patch16-224/version/3?tid=72f988bf-86f1-41af-91ab-2d7cd011db47#overview) | azureml-staging registry |
+| [Image classification models from Huggingface's Transformer library](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers)| HuggingFace |

cli/foundation-models/system/finetune/image-instance-segmentation/deepspeed_configs/zero1.json

@@ -0,0 +1,42 @@
+{
+  "fp16": {
+    "enabled": true,
+    "loss_scale": 0,
+    "loss_scale_window": 1000,
+    "hysteresis": 2,
+    "min_loss_scale": 1
+  },
+  "zero_optimization": {
+    "stage": 1,
+    "allgather_partitions": true,
+    "allgather_bucket_size": 200000000,
+    "overlap_comm": true,
+    "reduce_scatter": true,
+    "reduce_bucket_size": 200000000,
+    "contiguous_gradients": false,
+    "cpu_offload": false
+  },
+  "zero_allow_untested_optimizer": true,
+  "optimizer": {
+    "type": "AdamW",
+    "params": {
+      "lr": "auto",
+      "betas": "auto",
+      "eps": "auto",
+      "weight_decay": "auto"
+    }
+  },
+  "scheduler": {
+    "type": "WarmupLR",
+    "params": {
+      "warmup_min_lr": "auto",
+      "warmup_max_lr": "auto",
+      "warmup_num_steps": "auto"
+    }
+  },
+  "steps_per_print": 2000,
+  "train_batch_size": "auto",
+  "train_micro_batch_size_per_gpu": "auto",
+  "gradient_accumulation_steps": "auto",
+  "wall_clock_breakdown": false
+}

cli/foundation-models/system/finetune/image-instance-segmentation/deploy.yaml

@@ -0,0 +1,4 @@
+$schema: https://azuremlschemas.azureedge.net/latest/managedOnlineDeployment.schema.json
+name: demo
+instance_type: Standard_DS3_v2
+instance_count: 1