Merge branch 'main' into add-readme-check

Azure · Nov 8, 2023 · 5b352ee · 5b352ee
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diff --git a/...class-classification/hftransformers-fridgeobjects-multiclass-classification-pipeline.yaml b/...class-classification/hftransformers-fridgeobjects-multiclass-classification-pipeline.yaml
@@ -52,6 +52,7 @@ jobs:
 
       # Model import args
       task_name: image-classification
+      download_from_source: False # True for downloading a model directly from HuggingFace
       model_family: HuggingFaceImage
       # # Specify the model_name instead of mlflow_model if you want to use a model from the huggingface hub
       mlflow_model: ${{parent.inputs.mlflow_model_path}} 

diff --git a/...models/system/finetune/image-classification/multiclass-classification/readme.md b/...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/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/5) | azureml registry |
-| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/5) | azureml registry |
-| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/5) | azureml registry |
-| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/5) | azureml registry |
+| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/11) | azureml registry |
+| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/11) | azureml registry |
+| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/10) | azureml registry |
+| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/10) | azureml registry |
 | [Image classification models from Huggingface's Transformer library](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers)| HuggingFace |
diff --git a/...label-classification/hftransformers-fridgeobjects-multilabel-classification-pipeline.yaml b/...label-classification/hftransformers-fridgeobjects-multilabel-classification-pipeline.yaml
@@ -52,6 +52,7 @@ jobs:
 
       # model
       task_name: image-classification-multilabel
+      download_from_source: False # True for downloading a model directly from HuggingFace
       model_family: HuggingFaceImage
       # # Specify the model_name instead of mlflow_model if you want to use a model from the huggingface hub
       mlflow_model: ${{parent.inputs.mlflow_model_path}} 

diff --git a/...models/system/finetune/image-classification/multilabel-classification/readme.md b/...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/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/5) | azureml registry |
-| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/5) | azureml registry |
-| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/5) | azureml registry |
-| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/5) | azureml registry |
+| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/11) | azureml registry |
+| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/11) | azureml registry |
+| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/10) | azureml registry |
+| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/10) | azureml registry |
 | [Image classification models from Huggingface's Transformer library](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers)| HuggingFace |
diff --git a/...image-instance-segmentation/mmdetection-fridgeobjects-instance-segmentation-pipeline.yaml b/...image-instance-segmentation/mmdetection-fridgeobjects-instance-segmentation-pipeline.yaml
@@ -53,6 +53,7 @@ jobs:
 
       # Model import args
       task_name: image-instance-segmentation
+      download_from_source: False # True for downloading a model directly from MMDetection
       # model_name: ${{parent.inputs.model_name}}
       # pytorch_model: ${{parent.inputs.pytorch_model}}
       mlflow_model: ${{parent.inputs.mlflow_model}}

diff --git a/cli/foundation-models/system/finetune/image-instance-segmentation/readme.md b/cli/foundation-models/system/finetune/image-instance-segmentation/readme.md
@@ -7,5 +7,5 @@ For using this component for instance segmentation, run the shell script file `b
 Currently following models are supported:
 | Model Name | Source |
 | :------------: | :-------:  |
-| [mask_rcnn_swin-t-p4-w7_fpn_1x_coco](https://ml.azure.com/registries/azureml/models/mask_rcnn_swin-t-p4-w7_fpn_1x_coco/version/3) | azureml registry |
+| [mask_rcnn_swin-t-p4-w7_fpn_1x_coco](https://ml.azure.com/registries/azureml/models/mask_rcnn_swin-t-p4-w7_fpn_1x_coco/version/8) | azureml registry |
 | [Image instance-segmentation models from MMDetection](https://github.com/open-mmlab/mmdetection/blob/v2.28.2/docs/en/model_zoo.md) | MMDetection |
diff --git a/.../system/finetune/image-object-detection/mmdetection-fridgeobjects-detection-pipeline.yaml b/.../system/finetune/image-object-detection/mmdetection-fridgeobjects-detection-pipeline.yaml
@@ -53,6 +53,7 @@ jobs:
 
       # # Model import args
       task_name: image-object-detection
+      download_from_source: False # True for downloading a model directly from MMDetection
       # model_name: ${{parent.inputs.model_name}}
       # pytorch_model: ${{parent.inputs.pytorch_model}}
       mlflow_model: ${{parent.inputs.mlflow_model}}

diff --git a/cli/foundation-models/system/finetune/image-object-detection/readme.md b/cli/foundation-models/system/finetune/image-object-detection/readme.md
@@ -7,10 +7,10 @@ For using this component for object detection, run the shell script file `bash .
 Currently following models are supported:
 | Model Name | Source |
 | :------------: | :-------:  |
-| [deformable_detr_twostage_refine_r50_16x2_50e_coco](https://ml.azure.com/registries/azureml/models/deformable_detr_twostage_refine_r50_16x2_50e_coco/version/3) | azureml registry |
-| [sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco](https://ml.azure.com/registries/azureml/models/sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco/version/3) | azureml registry |
-| [sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco](https://ml.azure.com/registries/azureml/models/sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco/version/3) | azureml registry |
-| [vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco](https://ml.azure.com/registries/azureml/models/vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco/version/3) | azureml registry |
-| [vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco](https://ml.azure.com/registries/azureml/models/vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco/version/3) | azureml registry |
-| [yolof_r50_c5_8x8_1x_coco](https://ml.azure.com/registries/azureml/models/yolof_r50_c5_8x8_1x_coco/version/3) | azureml registry |
+| [deformable_detr_twostage_refine_r50_16x2_50e_coco](https://ml.azure.com/registries/azureml/models/deformable_detr_twostage_refine_r50_16x2_50e_coco/version/8) | azureml registry |
+| [sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco](https://ml.azure.com/registries/azureml/models/sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco/version/8) | azureml registry |
+| [sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco](https://ml.azure.com/registries/azureml/models/sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco/version/8) | azureml registry |
+| [vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco](https://ml.azure.com/registries/azureml/models/vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco/version/8) | azureml registry |
+| [vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco](https://ml.azure.com/registries/azureml/models/vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco/version/8) | azureml registry |
+| [yolof_r50_c5_8x8_1x_coco](https://ml.azure.com/registries/azureml/models/yolof_r50_c5_8x8_1x_coco/version/8) | azureml registry |
 | [Image object detection models from MMDetection](https://github.com/open-mmlab/mmdetection/blob/v2.28.2/docs/en/model_zoo.md) | MMDetection |
diff --git a/...-models/system/docs/component_docs/image_finetune/mmd_model_import_component.md b/...-models/system/docs/component_docs/image_finetune/mmd_model_import_component.md
@@ -55,6 +55,10 @@ The component copies the input model folder to the component output directory wh
     Please select models from AzureML Model Assets for all supported models. For MMDetection models, which are not supported in AzureML model registry, the model's config name is required, same as it's specified in MMDetection Model Zoo. For e.g. fast_rcnn_r101_fpn_1x_coco for [this config file](https://github.com/open-mmlab/mmdetection/blob/master/configs/fast_rcnn/fast_rcnn_r101_fpn_1x_coco.py). You can see the comprehensive list of model configs [here](https://github.com/open-mmlab/mmdetection/tree/v2.28.2/configs) and the documentation of model zoo [here](https://github.com/open-mmlab/mmdetection/blob/v2.28.2/docs/en/model_zoo.md).
     Please note that it is the user responsibility to comply with the model's license terms.
 
+3. __download_from_source__ (boolean, optional)
+    Set to True for downloading model directly from MMDetection instead of system registry.
+    Defaults to `False`.
+
 # 4. Run Settings
 
 This setting helps to choose the compute for running the component code. For the purpose of model selector, cpu compute should work. We recommend using D12 compute.

diff --git a/...ystem/docs/component_docs/image_finetune/transformers_model_import_component.md b/...ystem/docs/component_docs/image_finetune/transformers_model_import_component.md
@@ -55,6 +55,10 @@ The component copies the input model folder to the component output directory wh
     is subject to third party license terms available on the HuggingFace model details page.
     It is the user's responsibility to comply with the model's license terms.
 
+3. __download_from_source__ (boolean, optional)
+    Set to True for downloading model directly from HuggingFace instead of system registry.
+    Defaults to `False`.
+
 # 4. Run Settings
 
 This setting helps to choose the compute for running the component code. For the purpose of model selector, cpu compute should work. We recommend using D12 compute.

diff --git a/...on/multiclass-classification/hftransformers-fridgeobjects-multiclass-classification.ipynb b/...on/multiclass-classification/hftransformers-fridgeobjects-multiclass-classification.ipynb
@@ -204,15 +204,15 @@
    "outputs": [],
    "source": [
     "# Using the same compute cluster for model evaluation as finetuning. If you want to use a different cluster, specify it below\n",
-    "Model_eval_cluster_name = \"sample-finetune-cluster-gpu\"\n",
+    "model_eval_cluster_name = \"sample-finetune-cluster-gpu\"\n",
     "\n",
     "try:\n",
-    "    _ = workspace_ml_client.compute.get(Model_eval_cluster_name)\n",
+    "    _ = workspace_ml_client.compute.get(model_eval_cluster_name)\n",
     "    print(\"Found existing compute target.\")\n",
     "except ResourceNotFoundError:\n",
     "    print(\"Creating a new compute target...\")\n",
     "    compute_config = AmlCompute(\n",
-    "        name=Model_eval_cluster_name,\n",
+    "        name=model_eval_cluster_name,\n",
     "        type=\"amlcompute\",\n",
     "        size=\"Standard_NC6s_v3\",\n",
     "        idle_time_before_scale_down=120,\n",
@@ -235,10 +235,10 @@
     "\n",
     "| Model Name | Source |\n",
     "| ------ | ---------- |\n",
-    "| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/5) | azureml registry |\n",
-    "| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/5) | azureml registry |\n",
-    "| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/5) | azureml registry |\n",
-    "| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/5) | azureml registry |\n",
+    "| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/11) | azureml registry |\n",
+    "| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/11) | azureml registry |\n",
+    "| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/10) | azureml registry |\n",
+    "| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/10) | azureml registry |\n",
     "| [Image classification models from Huggingface's Transformer library](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers)| HuggingFace |"
    ]
   },
@@ -543,6 +543,7 @@
     "pipeline_component_args = {\n",
     "    # # Model import args\n",
     "    \"model_family\": \"HuggingFaceImage\",\n",
+    "    \"download_from_source\": False,  # True for downloading a model directly from HuggingFace\n",
     "    \"mlflow_model\": foundation_model.id,  # foundation_model.id is provided, only foundation_model gives UserErrorException: only path input is supported now but get: ...\n",
     "    # \"model_name\": huggingface_model_name, # specify the model_name instead of mlflow_model if you want to use a model from the huggingface hub\n",
     "    # # Finetune_args\n",
@@ -646,7 +647,7 @@
     "    transformers_pipeline_component: PipelineComponent = pipeline_component_transformers_func(\n",
     "        compute_model_import=model_import_cluster_name,\n",
     "        compute_finetune=finetune_cluster_name,\n",
-    "        compute_model_evaluation=Model_eval_cluster_name,\n",
+    "        compute_model_evaluation=model_eval_cluster_name,\n",
     "        training_data=Input(type=AssetTypes.MLTABLE, path=training_mltable_path),\n",
     "        validation_data=Input(type=AssetTypes.MLTABLE, path=validation_mltable_path),\n",
     "        # test data\n",
@@ -1170,5 +1171,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 2
 }
diff --git a/...on/multilabel-classification/hftransformers-fridgeobjects-multilabel-classification.ipynb b/...on/multilabel-classification/hftransformers-fridgeobjects-multilabel-classification.ipynb
@@ -205,15 +205,15 @@
    "outputs": [],
    "source": [
     "# Using the same compute cluster for model evaluation as finetuning. If you want to use a different cluster, specify it below\n",
-    "Model_eval_cluster_name = \"sample-finetune-cluster-gpu\"\n",
+    "model_eval_cluster_name = \"sample-finetune-cluster-gpu\"\n",
     "\n",
     "try:\n",
-    "    _ = workspace_ml_client.compute.get(Model_eval_cluster_name)\n",
+    "    _ = workspace_ml_client.compute.get(model_eval_cluster_name)\n",
     "    print(\"Found existing compute target.\")\n",
     "except ResourceNotFoundError:\n",
     "    print(\"Creating a new compute target...\")\n",
     "    compute_config = AmlCompute(\n",
-    "        name=Model_eval_cluster_name,\n",
+    "        name=model_eval_cluster_name,\n",
     "        type=\"amlcompute\",\n",
     "        size=\"Standard_NC6s_v3\",\n",
     "        idle_time_before_scale_down=120,\n",
@@ -236,10 +236,10 @@
     "\n",
     "| Model Name | Source |\n",
     "| ------ | ---------- |\n",
-    "| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/5) | azureml registry |\n",
-    "| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/5) | azureml registry |\n",
-    "| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/5) | azureml registry |\n",
-    "| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/5) | azureml registry |\n",
+    "| [microsoft-beit-base-patch16-224-pt22k-ft22k](https://ml.azure.com/registries/azureml/models/microsoft-beit-base-patch16-224-pt22k-ft22k/version/11) | azureml registry |\n",
+    "| [microsoft-swinv2-base-patch4-window12-192-22k](https://ml.azure.com/registries/azureml/models/microsoft-swinv2-base-patch4-window12-192-22k/version/11) | azureml registry |\n",
+    "| [facebook-deit-base-patch16-224](https://ml.azure.com/registries/azureml/models/facebook-deit-base-patch16-224/version/10) | azureml registry |\n",
+    "| [google-vit-base-patch16-224](https://ml.azure.com/registries/azureml/models/google-vit-base-patch16-224/version/10) | azureml registry |\n",
     "| [Image classification models from Huggingface's Transformer library](https://huggingface.co/models?pipeline_tag=image-classification&library=transformers)| HuggingFace |"
    ]
   },
@@ -543,6 +543,7 @@
     "pipeline_component_args = {\n",
     "    # # Model import args\n",
     "    \"model_family\": \"HuggingFaceImage\",\n",
+    "    \"download_from_source\": False,  # True for downloading a model directly from HuggingFace\n",
     "    \"mlflow_model\": foundation_model.id,  # foundation_model.id is provided, only foundation_model gives UserErrorException: only path input is supported now but get: ...\n",
     "    # \"model_name\": huggingface_model_name, # specify the model_name instead of mlflow_model if you want to use a model from the huggingface hub\n",
     "    # # Finetune_args\n",
@@ -646,7 +647,7 @@
     "    transformers_pipeline_component: PipelineComponent = pipeline_component_transformers_func(\n",
     "        compute_model_import=model_import_cluster_name,\n",
     "        compute_finetune=finetune_cluster_name,\n",
-    "        compute_model_evaluation=Model_eval_cluster_name,\n",
+    "        compute_model_evaluation=model_eval_cluster_name,\n",
     "        training_data=Input(type=AssetTypes.MLTABLE, path=training_mltable_path),\n",
     "        validation_data=Input(type=AssetTypes.MLTABLE, path=validation_mltable_path),\n",
     "        # test data\n",