constants.py

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
#     http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import


SPECIAL_MODEL_SPECS_DICT = {
    "env-var-variant-model": {
        "model_id": "huggingface-llm-falcon-180b-bf16",
        "url": "https://huggingface.co/tiiuae/falcon-180B",
        "version": "1.0.0",
        "min_sdk_version": "2.175.0",
        "training_supported": False,
        "incremental_training_supported": False,
        "hosting_ecr_specs": {
            "framework": "huggingface-llm",
            "framework_version": "0.9.3",
            "py_version": "py39",
            "huggingface_transformers_version": "4.29.2",
        },
        "hosting_artifact_key": "huggingface-infer/infer-huggingface-llm-falcon-180b-bf16.tar.gz",
        "hosting_script_key": "source-directory-tarballs/huggingface/inference/llm/v1.0.1/sourcedir.tar.gz",
        "hosting_prepacked_artifact_key": "huggingface-infer/prepack/v1.0.1/infer-prepack"
        "-huggingface-llm-falcon-180b-bf16.tar.gz",
        "hosting_prepacked_artifact_version": "1.0.1",
        "hosting_use_script_uri": False,
        "inference_vulnerable": False,
        "inference_dependencies": [],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "ENDPOINT_SERVER_TIMEOUT",
                "type": "int",
                "default": 3600,
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_ENV",
                "type": "text",
                "default": "1",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "HF_MODEL_ID",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SM_NUM_GPUS",
                "type": "text",
                "default": "8",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "MAX_INPUT_LENGTH",
                "type": "text",
                "default": "1024",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "MAX_TOTAL_TOKENS",
                "type": "text",
                "default": "2048",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "int",
                "default": 1,
                "scope": "container",
                "required_for_model_class": True,
            },
        ],
        "metrics": [],
        "default_inference_instance_type": "ml.p4de.24xlarge",
        "supported_inference_instance_types": ["ml.p4de.24xlarge"],
        "model_kwargs": {},
        "deploy_kwargs": {
            "model_data_download_timeout": 3600,
            "container_startup_health_check_timeout": 3600,
        },
        "predictor_specs": {
            "supported_content_types": ["application/json"],
            "supported_accept_types": ["application/json"],
            "default_content_type": "application/json",
            "default_accept_type": "application/json",
        },
        "inference_volume_size": 512,
        "inference_enable_network_isolation": True,
        "validation_supported": False,
        "fine_tuning_supported": False,
        "resource_name_base": "hf-llm-falcon-180b-bf16",
        "hosting_instance_type_variants": {
            "regional_aliases": {
                "us-west-2": {
                    "gpu_image_uri": "763104351884.dkr.ecr.us-west-2.amazonaws.com/"
                    "huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
                    "cpu_image_uri": "867930986793.dkr.us-west-2.amazonaws.com/cpu-blah",
                }
            },
            "variants": {
                "g4dn": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "g5": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "local_gpu": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "p2": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "p3": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "p3dn": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "p4d": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "p4de": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "p5": {"regional_properties": {"image_uri": "$gpu_ecr_uri_1"}},
                "ml.g5.48xlarge": {"properties": {"environment_variables": {"SM_NUM_GPUS": "80"}}},
                "ml.p4d.24xlarge": {
                    "properties": {
                        "environment_variables": {
                            "YODEL": "NACEREMA",
                        }
                    }
                },
            },
        },
    },
    "variant-model": {
        "model_id": "pytorch-ic-mobilenet-v2",
        "url": "https://pytorch.org/hub/pytorch_vision_mobilenet_v2/",
        "version": "1.0.0",
        "min_sdk_version": "2.49.0",
        "training_supported": True,
        "incremental_training_supported": True,
        "hosting_ecr_specs": {
            "framework": "pytorch",
            "framework_version": "1.5.0",
            "py_version": "py3",
        },
        "hosting_instance_type_variants": {
            "regional_aliases": {
                "us-west-2": {
                    "gpu_image_uri": "763104351884.dkr.ecr.us-west-2.amazonaws.com/"
                    "huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04",
                    "cpu_image_uri": "867930986793.dkr.us-west-2.amazonaws.com/cpu-blah",
                }
            },
            "variants": {
                "p2": {"regional_properties": {"image_uri": "$gpu_image_uri"}},
                "p3": {"regional_properties": {"image_uri": "$gpu_image_uri"}},
                "p4": {"regional_properties": {"image_uri": "$gpu_image_uri"}},
                "g4dn": {"regional_properties": {"image_uri": "$gpu_image_uri"}},
                "m2": {"regional_properties": {"image_uri": "$cpu_image_uri"}},
                "c2": {"regional_properties": {"image_uri": "$cpu_image_uri"}},
                "ml.g5.48xlarge": {
                    "properties": {"environment_variables": {"TENSOR_PARALLEL_DEGREE": "8"}}
                },
                "ml.g5.12xlarge": {
                    "properties": {"environment_variables": {"TENSOR_PARALLEL_DEGREE": "4"}}
                },
            },
        },
        "training_ecr_specs": {
            "framework": "pytorch",
            "framework_version": "1.5.0",
            "py_version": "py3",
        },
        "training_instance_type_variants": None,
        "hosting_artifact_key": "pytorch-infer/infer-pytorch-ic-mobilenet-v2.tar.gz",
        "training_artifact_key": "pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz",
        "hosting_script_key": "source-directory-tarballs/pytorch/inference/ic/v1.0.0/sourcedir.tar.gz",
        "training_script_key": "source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz",
        "training_prepacked_script_key": None,
        "hosting_prepacked_artifact_key": None,
        "training_model_package_artifact_uris": None,
        "deprecate_warn_message": None,
        "deprecated_message": None,
        "hosting_model_package_arns": None,
        "hosting_eula_key": None,
        "hyperparameters": [
            {
                "name": "epochs",
                "type": "int",
                "default": 3,
                "min": 1,
                "max": 1000,
                "scope": "algorithm",
            },
            {
                "name": "adam-learning-rate",
                "type": "float",
                "default": 0.05,
                "min": 1e-08,
                "max": 1,
                "scope": "algorithm",
            },
            {
                "name": "batch-size",
                "type": "int",
                "default": 4,
                "min": 1,
                "max": 1024,
                "scope": "algorithm",
            },
            {
                "name": "sagemaker_submit_directory",
                "type": "text",
                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
                "scope": "container",
            },
            {
                "name": "sagemaker_program",
                "type": "text",
                "default": "transfer_learning.py",
                "scope": "container",
            },
            {
                "name": "sagemaker_container_log_level",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
        ],
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "ENDPOINT_SERVER_TIMEOUT",
                "type": "int",
                "default": 3600,
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_ENV",
                "type": "text",
                "default": "1",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "int",
                "default": 1,
                "scope": "container",
                "required_for_model_class": True,
            },
        ],
        "inference_vulnerable": False,
        "inference_dependencies": [],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "default_inference_instance_type": "ml.p2.xlarge",
        "supported_inference_instance_types": [
            "ml.p2.xlarge",
            "ml.p3.2xlarge",
            "ml.g4dn.xlarge",
            "ml.m5.large",
            "ml.m5.xlarge",
            "ml.c5.xlarge",
            "ml.c5.2xlarge",
        ],
        "default_training_instance_type": "ml.p3.2xlarge",
        "supported_training_instance_types": [
            "ml.p3.2xlarge",
            "ml.p2.xlarge",
            "ml.g4dn.2xlarge",
            "ml.m5.xlarge",
            "ml.c5.2xlarge",
        ],
        "hosting_use_script_uri": True,
        "metrics": [{"Regex": "val_accuracy: ([0-9\\.]+)", "Name": "pytorch-ic:val-accuracy"}],
        "model_kwargs": {"some-model-kwarg-key": "some-model-kwarg-value"},
        "deploy_kwargs": {"some-model-deploy-kwarg-key": "some-model-deploy-kwarg-value"},
        "estimator_kwargs": {
            "encrypt_inter_container_traffic": True,
        },
        "fit_kwargs": {"some-estimator-fit-key": "some-estimator-fit-value"},
        "predictor_specs": {
            "supported_content_types": ["application/x-image"],
            "supported_accept_types": ["application/json;verbose", "application/json"],
            "default_content_type": "application/x-image",
            "default_accept_type": "application/json",
        },
        "inference_volume_size": 123,
        "training_volume_size": 456,
        "inference_enable_network_isolation": True,
        "training_enable_network_isolation": False,
        "resource_name_base": "dfsdfsds",
    },
    "js-model-package-arn": {
        "model_id": "meta-textgeneration-llama-2-7b-f",
        "url": "https://ai.meta.com/resources/models-and-libraries/llama-downloads/",
        "version": "1.0.0",
        "min_sdk_version": "2.173.0",
        "training_supported": False,
        "incremental_training_supported": False,
        "hosting_ecr_specs": {
            "framework": "pytorch",
            "framework_version": "1.12.0",
            "py_version": "py38",
        },
        "hosting_artifact_key": "meta-infer/infer-meta-textgeneration-llama-2-7b-f.tar.gz",
        "hosting_script_key": "source-directory-tarballs/meta/inference/textgeneration/v1.0.0/sourcedir.tar.gz",
        "hosting_eula_key": "fmhMetadata/eula/llamaEula.txt",
        "hosting_model_package_arns": {
            "us-west-2": "arn:aws:sagemaker:us-west-2:594846645681:model-package/"
            "llama2-7b-f-e46eb8a833643ed58aaccd81498972c3",
            "us-east-1": "arn:aws:sagemaker:us-east-1:865070037744:model-package/"
            "llama2-7b-f-e46eb8a833643ed58aaccd81498972c3",
        },
        "inference_vulnerable": False,
        "inference_dependencies": [],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "inference_environment_variables": [],
        "metrics": [],
        "default_inference_instance_type": "ml.g5.2xlarge",
        "supported_inference_instance_types": [
            "ml.g5.2xlarge",
            "ml.g5.4xlarge",
            "ml.g5.8xlarge",
            "ml.g5.12xlarge",
            "ml.g5.24xlarge",
            "ml.g5.48xlarge",
            "ml.p4d.24xlarge",
        ],
        "model_kwargs": {},
        "deploy_kwargs": {
            "model_data_download_timeout": 3600,
            "container_startup_health_check_timeout": 3600,
        },
        "predictor_specs": {
            "supported_content_types": ["application/json"],
            "supported_accept_types": ["application/json"],
            "default_content_type": "application/json",
            "default_accept_type": "application/json",
        },
        "inference_volume_size": 256,
        "inference_enable_network_isolation": True,
        "validation_supported": False,
        "fine_tuning_supported": False,
        "resource_name_base": "meta-textgeneration-llama-2-7b-f",
    },
    "js-trainable-model-prepacked": {
        "model_id": "huggingface-text2text-flan-t5-base",
        "url": "https://huggingface.co/google/flan-t5-base",
        "version": "1.2.0",
        "min_sdk_version": "2.130.0",
        "training_supported": True,
        "incremental_training_supported": False,
        "hosting_ecr_specs": {
            "framework": "huggingface",
            "framework_version": "1.10.2",
            "py_version": "py38",
            "huggingface_transformers_version": "4.17.0",
        },
        "hosting_artifact_key": "huggingface-infer/infer-huggingface-text2text-flan-t5-base.tar.gz",
        "hosting_script_key": "source-directory-tarballs/huggingface/inference/text2text/v1.0.4/sourcedir.tar.gz",
        "hosting_prepacked_artifact_key": "huggingface-infer/prepack/v1.0.0/infer-prepack-"
        "huggingface-text2text-flan-t5-base.tar.gz",
        "hosting_prepacked_artifact_version": "1.0.0",
        "inference_vulnerable": False,
        "inference_dependencies": [
            "accelerate==0.16.0",
            "bitsandbytes==0.37.0",
            "filelock==3.9.0",
            "huggingface_hub==0.12.0",
            "regex==2022.7.9",
            "tokenizers==0.13.2",
            "transformers==4.26.0",
        ],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [
            "Brotli==1.0.9",
            "absl-py==1.4.0",
            "accelerate==0.16.0",
            "datasets==2.9.0",
            "deepspeed==0.8.0",
            "evaluate==0.4.0",
            "hjson==3.1.0",
            "huggingface_hub==0.13.3",
            "inflate64==0.3.1",
            "multivolumefile==0.2.3",
            "ninja==1.11.1",
            "nltk==3.8.1",
            "psutil==5.9.4",
            "py-cpuinfo==9.0.0",
            "py7zr==0.20.4",
            "pybcj==1.0.1",
            "pycryptodomex==3.17",
            "pydantic==1.10.2",
            "pyppmd==1.0.0",
            "pyzstd==0.15.4",
            "rouge-score==0.1.2",
            "sagemaker_jumpstart_script_utilities==1.1.4",
            "sagemaker_jumpstart_tabular_script_utilities==1.0.0",
            "tensorboardX==2.6",
            "texttable==1.6.7",
            "transformers==4.26.0",
        ],
        "training_vulnerabilities": [],
        "deprecated": False,
        "hyperparameters": [
            {
                "name": "epochs",
                "type": "int",
                "default": 1,
                "min": 1,
                "max": 1000,
                "scope": "algorithm",
            },
            {
                "name": "seed",
                "type": "int",
                "default": 42,
                "min": 1,
                "max": 1000,
                "scope": "algorithm",
            },
            {
                "name": "batch_size",
                "type": "int",
                "default": 64,
                "min": 1,
                "max": 1024,
                "scope": "algorithm",
            },
            {
                "name": "learning_rate",
                "type": "float",
                "default": 0.0001,
                "min": 1e-08,
                "max": 1,
                "scope": "algorithm",
            },
            {
                "name": "validation_split_ratio",
                "type": "float",
                "default": 0.05,
                "min": 0,
                "max": 1,
                "scope": "algorithm",
            },
            {"name": "train_data_split_seed", "type": "int", "default": 0, "scope": "algorithm"},
            {
                "name": "sagemaker_submit_directory",
                "type": "text",
                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
                "scope": "container",
            },
            {
                "name": "sagemaker_program",
                "type": "text",
                "default": "transfer_learning.py",
                "scope": "container",
            },
            {
                "name": "sagemaker_container_log_level",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
        ],
        "training_script_key": "source-directory-tarballs/huggingface/transfer_learning/text2text/"
        "v1.1.0/sourcedir.tar.gz",
        "training_prepacked_script_key": "source-directory-tarballs/huggingface/transfer_learning/"
        "text2text/prepack/v1.0.1/sourcedir.tar.gz",
        "training_prepacked_script_version": "1.0.1",
        "training_ecr_specs": {
            "framework": "huggingface",
            "framework_version": "1.10.2",
            "py_version": "py38",
            "huggingface_transformers_version": "4.17.0",
        },
        "training_artifact_key": "huggingface-training/train-huggingface-text2text-flan-t5-base.tar.gz",
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
                "required_for_model_class": False,
            },
            {
                "name": "ENDPOINT_SERVER_TIMEOUT",
                "type": "int",
                "default": 3600,
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_ENV",
                "type": "text",
                "default": "1",
                "scope": "container",
                "required_for_model_class": True,
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "int",
                "default": 1,
                "scope": "container",
                "required_for_model_class": True,
            },
        ],
        "metrics": [
            {"Name": "huggingface-text2text:eval-loss", "Regex": "'eval_loss': ([0-9\\.]+)"}
        ],
        "default_inference_instance_type": "ml.g5.xlarge",
        "supported_inference_instance_types": [
            "ml.g5.xlarge",
            "ml.p2.xlarge",
            "ml.g4dn.xlarge",
            "ml.p3.2xlarge",
        ],
        "default_training_instance_type": "ml.p3.16xlarge",
        "supported_training_instance_types": [
            "ml.p3.8xlarge",
            "ml.p3.16xlarge",
            "ml.p3dn.24xlarge",
            "ml.g5.24xlarge",
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                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
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                "default": "20",
                "scope": "container",
            },
            {
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                "default": "/opt/ml/model",
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            },
            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
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        ],
        "metrics": [],
        "default_inference_instance_type": "ml.g5.12xlarge",
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            "ml.g5.24xlarge",
            "ml.p3.8xlarge",
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        "predictor_specs": {
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            "supported_accept_types": ["application/json;verbose", "application/json"],
            "default_content_type": "application/x-text",
            "default_accept_type": "application/json",
        },
    },
    "model_data_s3_prefix_model": {
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        "url": "https://huggingface.co/google/flan-t5-xxl",
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        "inference_vulnerable": False,
        "inference_dependencies": [
            "accelerate==0.16.0",
            "bitsandbytes==0.37.0",
            "filelock==3.9.0",
            "huggingface_hub==0.12.0",
            "regex==2022.7.9",
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            "transformers==4.26.0",
        ],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "inference_environment_variables": [
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                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
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                "scope": "container",
            },
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                "type": "text",
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                "scope": "container",
            },
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                "type": "text",
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                "scope": "container",
            },
            {
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                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
            },
            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "text",
                "default": "1",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
            },
        ],
        "metrics": [],
        "default_inference_instance_type": "ml.g5.12xlarge",
        "supported_inference_instance_types": [
            "ml.g5.12xlarge",
            "ml.g5.24xlarge",
            "ml.p3.8xlarge",
            "ml.p3.16xlarge",
            "ml.g4dn.12xlarge",
        ],
        "predictor_specs": {
            "supported_content_types": ["application/x-text"],
            "supported_accept_types": ["application/json;verbose", "application/json"],
            "default_content_type": "application/x-text",
            "default_accept_type": "application/json",
        },
    },
    "no-supported-instance-types-model": {
        "model_id": "pytorch-ic-mobilenet-v2",
        "url": "https://pytorch.org/hub/pytorch_vision_mobilenet_v2/",
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                "min": 1e-08,
                "max": 1,
                "scope": "algorithm",
            },
            {
                "name": "batch-size",
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                "min": 1,
                "max": 1024,
                "scope": "algorithm",
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                "type": "text",
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        ],
        "inference_environment_variables": [
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                "default": "inference.py",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
            {
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                "default": "/opt/ml/model",
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                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
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            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
            },
        ],
        "default_inference_instance_type": "",
        "supported_inference_instance_types": None,
        "default_training_instance_type": None,
        "supported_training_instance_types": [],
        "inference_vulnerable": False,
        "inference_dependencies": [],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "metrics": [],
    },
    "huggingface-text2text-flan-t5-xxl-fp16": {
        "model_id": "huggingface-text2text-flan-t5-xxl-fp16",
        "url": "https://huggingface.co/google/flan-t5-xxl",
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        "hosting_ecr_specs": {
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        "hosting_artifact_key": "huggingface-infer/infer-huggingface-text2text-flan-t5-xxl-fp16.tar.gz",
        "hosting_script_key": "source-directory-tarballs/huggingface/inference/text2text/v1.0.2/sourcedir.tar.gz",
        "hosting_prepacked_artifact_key": "huggingface-infer/prepack/v1.0.0/infer-prepack-huggingface-"
        "text2text-flan-t5-xxl-fp16.tar.gz",
        "hosting_prepacked_artifact_version": "1.0.0",
        "inference_vulnerable": False,
        "inference_dependencies": [
            "accelerate==0.16.0",
            "bitsandbytes==0.37.0",
            "filelock==3.9.0",
            "huggingface-hub==0.12.0",
            "regex==2022.7.9",
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            "transformers==4.26.0",
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        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
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            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
            },
            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "text",
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            },
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                "type": "text",
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                "scope": "container",
            },
        ],
        "inference_vulnerable": False,
        "training_vulnerable": False,
        "deprecated": False,
        "default_training_instance_type": None,
        "supported_training_instance_types": [],
        "metrics": [],
        "default_inference_instance_type": "ml.g5.12xlarge",
        "supported_inference_instance_types": [
            "ml.g5.12xlarge",
            "ml.g5.24xlarge",
            "ml.p3.8xlarge",
            "ml.p3.16xlarge",
            "ml.g4dn.12xlarge",
        ],
    },
    "mock-model-training-prepacked-script-key": {
        "model_id": "sklearn-classification-linear",
        "url": "https://scikit-learn.org/stable/",
        "version": "1.0.0",
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        "incremental_training_supported": False,
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        "hosting_script_key": "source-directory-tarballs/sklearn/inference/classification/v1.0.0/sourcedir.tar.gz",
        "inference_vulnerable": False,
        "inference_dependencies": [],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "hyperparameters": [
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                "name": "tol",
                "type": "float",
                "default": 0.0001,
                "min": 1e-20,
                "max": 50,
                "scope": "algorithm",
            },
            {
                "name": "penalty",
                "type": "text",
                "default": "l2",
                "options": ["l1", "l2", "elasticnet", "none"],
                "scope": "algorithm",
            },
            {
                "name": "alpha",
                "type": "float",
                "default": 0.0001,
                "min": 1e-20,
                "max": 999,
                "scope": "algorithm",
            },
            {
                "name": "l1_ratio",
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                "min": 0,
                "max": 1,
                "scope": "algorithm",
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                "scope": "container",
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            {
                "name": "sagemaker_program",
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                "default": "transfer_learning.py",
                "scope": "container",
            },
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                "name": "sagemaker_container_log_level",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
        ],
        "training_script_key": "source-directory-tarballs/sklearn/transfer_learning/classification/"
        "v1.0.0/sourcedir.tar.gz",
        "training_prepacked_script_key": "some/key/to/training_prepacked_script_key.tar.gz",
        "training_ecr_specs": {
            "framework_version": "0.23-1",
            "framework": "sklearn",
            "py_version": "py3",
        },
        "training_artifact_key": "sklearn-training/train-sklearn-classification-linear.tar.gz",
        "inference_environment_variables": [
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            },
            {
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                "type": "text",
                "default": "/opt/ml/model/code",
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            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
            {
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                "default": "/opt/ml/model",
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            },
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            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "text",
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            },
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                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
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        ],
    },
}


PROTOTYPICAL_MODEL_SPECS_DICT = {
    "pytorch-eqa-bert-base-cased": {
        "model_id": "pytorch-eqa-bert-base-cased",
        "url": "https://pytorch.org/hub/huggingface_pytorch-transformers/",
        "version": "1.0.0",
        "min_sdk_version": "2.68.1",
        "training_supported": True,
        "incremental_training_supported": False,
        "hosting_ecr_specs": {
            "framework": "pytorch",
            "framework_version": "1.5.0",
            "py_version": "py3",
        },
        "hosting_artifact_key": "pytorch-infer/infer-pytorch-eqa-bert-base-cased.tar.gz",
        "hosting_script_key": "source-directory-tarballs/pytorch/inference/eqa/v1.0.0/sourcedir.tar.gz",
        "inference_vulnerable": False,
        "inference_dependencies": [
            "transformers==3.5.1",
            "dataclasses==0.8",
            "filelock==3.0.12",
            "packaging==20.8",
            "pyparsing==2.4.7",
            "regex==2020.11.13",
            "sacremoses==0.0.43",
            "sentencepiece==0.1.91",
            "tokenizers==0.9.3",
        ],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [
            "transformers==3.5.1",
            "dataclasses==0.8",
            "filelock==3.0.12",
            "packaging==20.8",
            "pyparsing==2.4.7",
            "regex==2020.11.13",
            "sacremoses==0.0.43",
            "sentencepiece==0.1.91",
            "tokenizers==0.9.3",
        ],
        "training_vulnerabilities": [],
        "deprecated": False,
        "hyperparameters": [
            {
                "name": "epochs",
                "type": "int",
                "default": 3,
                "min": 1,
                "max": 1000,
                "scope": "algorithm",
            },
            {
                "name": "adam-learning-rate",
                "type": "float",
                "default": 2e-05,
                "min": 1e-08,
                "max": 1,
                "scope": "algorithm",
            },
            {
                "name": "batch-size",
                "type": "int",
                "default": 4,
                "min": 1,
                "max": 1024,
                "scope": "algorithm",
            },
            {
                "name": "sagemaker_submit_directory",
                "type": "text",
                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
                "scope": "container",
            },
            {
                "name": "sagemaker_program",
                "type": "text",
                "default": "transfer_learning.py",
                "scope": "container",
            },
            {
                "name": "sagemaker_container_log_level",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
        ],
        "training_script_key": "source-directory-tarballs/pytorch/transfer_learning/eqa/v1.0.0/sourcedir.tar.gz",
        "training_ecr_specs": {
            "framework_version": "1.5.0",
            "framework": "pytorch",
            "py_version": "py3",
        },
        "training_artifact_key": "pytorch-training/train-pytorch-eqa-bert-base-cased.tar.gz",
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
            },
            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "text",
                "default": "1",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
            },
        ],
    },
    "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1": {
        "model_id": "tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1",
        "url": "https://tfhub.dev/google/bit/m-r101x1/ilsvrc2012_classification/1",
        "version": "1.0.0",
        "min_sdk_version": "2.68.1",
        "training_supported": True,
        "incremental_training_supported": False,
        "hosting_ecr_specs": {
            "framework": "tensorflow",
            "framework_version": "2.3",
            "py_version": "py37",
        },
        "hosting_artifact_key": "tensorflow-infer/infer-tensorflow-ic-bit-m-r101x1-ilsvrc2012-classification-1.tar.gz",
        "hosting_script_key": "source-directory-tarballs/tensorflow/inference/ic/v1.0.0/sourcedir.tar.gz",
        "inference_vulnerable": False,
        "inference_dependencies": [],
        "inference_vulnerabilities": [],
        "training_vulnerable": False,
        "training_dependencies": [],
        "training_vulnerabilities": [],
        "deprecated": False,
        "hyperparameters": [
            {
                "name": "epochs",
                "type": "int",
                "default": 3,
                "min": 1,
                "max": 1000,
                "scope": "algorithm",
            },
            {
                "name": "adam-learning-rate",
                "type": "float",
                "default": 0.05,
                "min": 1e-08,
                "max": 1,
                "scope": "algorithm",
            },
            {
                "name": "batch-size",
                "type": "int",
                "default": 4,
                "min": 1,
                "max": 1024,
                "scope": "algorithm",
            },
            {
                "name": "sagemaker_submit_directory",
                "type": "text",
                "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
                "scope": "container",
            },
            {
                "name": "sagemaker_program",
                "type": "text",
                "default": "transfer_learning.py",
                "scope": "container",
            },
            {
                "name": "sagemaker_container_log_level",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
        ],
        "training_script_key": "source-directory-tarballs/tensorflow/transfer_learning/ic/v1.0.0/sourcedir.tar.gz",
        "training_ecr_specs": {
            "framework_version": "2.3",
            "framework": "tensorflow",
            "py_version": "py37",
        },
        "training_artifact_key": "tensorflow-training/train-tensorflow-ic-bit-"
        "m-r101x1-ilsvrc2012-classification-1.tar.gz",
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
            },
            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "text",
                "default": "1",
                "scope": "container",
            },
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                "type": "text",
                "default": "20",
                "scope": "container",
            },
        ],
        "training_script_key": "source-directory-tarballs/sklearn/transfer_learning/classification/"
        "v1.0.0/sourcedir.tar.gz",
        "training_ecr_specs": {
            "framework_version": "0.23-1",
            "framework": "sklearn",
            "py_version": "py3",
        },
        "training_artifact_key": "sklearn-training/train-sklearn-classification-linear.tar.gz",
        "inference_environment_variables": [
            {
                "name": "SAGEMAKER_PROGRAM",
                "type": "text",
                "default": "inference.py",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_SUBMIT_DIRECTORY",
                "type": "text",
                "default": "/opt/ml/model/code",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
                "type": "text",
                "default": "20",
                "scope": "container",
            },
            {
                "name": "MODEL_CACHE_ROOT",
                "type": "text",
                "default": "/opt/ml/model",
                "scope": "container",
            },
            {"name": "SAGEMAKER_ENV", "type": "text", "default": "1", "scope": "container"},
            {
                "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
                "type": "text",
                "default": "1",
                "scope": "container",
            },
            {
                "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
                "type": "text",
                "default": "3600",
                "scope": "container",
            },
        ],
    },
}

BASE_SPEC = {
    "model_id": "pytorch-ic-mobilenet-v2",
    "url": "https://pytorch.org/hub/pytorch_vision_mobilenet_v2/",
    "version": "1.0.0",
    "min_sdk_version": "2.49.0",
    "training_supported": True,
    "incremental_training_supported": True,
    "hosting_ecr_specs": {
        "framework": "pytorch",
        "framework_version": "1.5.0",
        "py_version": "py3",
    },
    "hosting_instance_type_variants": None,
    "training_ecr_specs": {
        "framework": "pytorch",
        "framework_version": "1.5.0",
        "py_version": "py3",
    },
    "training_instance_type_variants": None,
    "hosting_artifact_key": "pytorch-infer/infer-pytorch-ic-mobilenet-v2.tar.gz",
    "training_artifact_key": "pytorch-training/train-pytorch-ic-mobilenet-v2.tar.gz",
    "hosting_script_key": "source-directory-tarballs/pytorch/inference/ic/v1.0.0/sourcedir.tar.gz",
    "training_script_key": "source-directory-tarballs/pytorch/transfer_learning/ic/v1.0.0/sourcedir.tar.gz",
    "training_prepacked_script_key": None,
    "hosting_prepacked_artifact_key": None,
    "training_model_package_artifact_uris": None,
    "deprecate_warn_message": None,
    "deprecated_message": None,
    "hosting_model_package_arns": None,
    "hosting_eula_key": None,
    "hyperparameters": [
        {
            "name": "epochs",
            "type": "int",
            "default": 3,
            "min": 1,
            "max": 1000,
            "scope": "algorithm",
        },
        {
            "name": "adam-learning-rate",
            "type": "float",
            "default": 0.05,
            "min": 1e-08,
            "max": 1,
            "scope": "algorithm",
        },
        {
            "name": "batch-size",
            "type": "int",
            "default": 4,
            "min": 1,
            "max": 1024,
            "scope": "algorithm",
        },
        {
            "name": "sagemaker_submit_directory",
            "type": "text",
            "default": "/opt/ml/input/data/code/sourcedir.tar.gz",
            "scope": "container",
        },
        {
            "name": "sagemaker_program",
            "type": "text",
            "default": "transfer_learning.py",
            "scope": "container",
        },
        {
            "name": "sagemaker_container_log_level",
            "type": "text",
            "default": "20",
            "scope": "container",
        },
    ],
    "inference_environment_variables": [
        {
            "name": "SAGEMAKER_PROGRAM",
            "type": "text",
            "default": "inference.py",
            "scope": "container",
            "required_for_model_class": True,
        },
        {
            "name": "SAGEMAKER_SUBMIT_DIRECTORY",
            "type": "text",
            "default": "/opt/ml/model/code",
            "scope": "container",
            "required_for_model_class": False,
        },
        {
            "name": "SAGEMAKER_CONTAINER_LOG_LEVEL",
            "type": "text",
            "default": "20",
            "scope": "container",
            "required_for_model_class": False,
        },
        {
            "name": "SAGEMAKER_MODEL_SERVER_TIMEOUT",
            "type": "text",
            "default": "3600",
            "scope": "container",
            "required_for_model_class": False,
        },
        {
            "name": "ENDPOINT_SERVER_TIMEOUT",
            "type": "int",
            "default": 3600,
            "scope": "container",
            "required_for_model_class": True,
        },
        {
            "name": "MODEL_CACHE_ROOT",
            "type": "text",
            "default": "/opt/ml/model",
            "scope": "container",
            "required_for_model_class": True,
        },
        {
            "name": "SAGEMAKER_ENV",
            "type": "text",
            "default": "1",
            "scope": "container",
            "required_for_model_class": True,
        },
        {
            "name": "SAGEMAKER_MODEL_SERVER_WORKERS",
            "type": "int",
            "default": 1,
            "scope": "container",
            "required_for_model_class": True,
        },
    ],
    "inference_vulnerable": False,
    "inference_dependencies": [],
    "inference_vulnerabilities": [],
    "training_vulnerable": False,
    "training_dependencies": [],
    "training_vulnerabilities": [],
    "deprecated": False,
    "default_inference_instance_type": "ml.p2.xlarge",
    "supported_inference_instance_types": [
        "ml.p2.xlarge",
        "ml.p3.2xlarge",
        "ml.g4dn.xlarge",
        "ml.m5.large",
        "ml.m5.xlarge",
        "ml.c5.xlarge",
        "ml.c5.2xlarge",
    ],
    "default_training_instance_type": "ml.p3.2xlarge",
    "supported_training_instance_types": [
        "ml.p3.2xlarge",
        "ml.p2.xlarge",
        "ml.g4dn.2xlarge",
        "ml.m5.xlarge",
        "ml.c5.2xlarge",
    ],
    "hosting_use_script_uri": True,
    "metrics": [{"Regex": "val_accuracy: ([0-9\\.]+)", "Name": "pytorch-ic:val-accuracy"}],
    "model_kwargs": {"some-model-kwarg-key": "some-model-kwarg-value"},
    "deploy_kwargs": {"some-model-deploy-kwarg-key": "some-model-deploy-kwarg-value"},
    "estimator_kwargs": {
        "encrypt_inter_container_traffic": True,
    },
    "fit_kwargs": {"some-estimator-fit-key": "some-estimator-fit-value"},
    "predictor_specs": {
        "supported_content_types": ["application/x-image"],
        "supported_accept_types": ["application/json;verbose", "application/json"],
        "default_content_type": "application/x-image",
        "default_accept_type": "application/json",
    },
    "inference_volume_size": 123,
    "training_volume_size": 456,
    "inference_enable_network_isolation": True,
    "training_enable_network_isolation": False,
    "resource_name_base": "dfsdfsds",
}

BASE_HEADER = {
    "model_id": "tensorflow-ic-imagenet-inception-v3-classification-4",
    "version": "1.0.0",
    "min_version": "2.49.0",
    "spec_key": "community_models_specs/tensorflow-ic-imagenet"
    "-inception-v3-classification-4/specs_v1.0.0.json",
}

BASE_MANIFEST = [
    {
        "model_id": "tensorflow-ic-imagenet-inception-v3-classification-4",
        "version": "1.0.0",
        "min_version": "2.49.0",
        "spec_key": "community_models_specs/tensorflow-ic-imagenet"
        "-inception-v3-classification-4/specs_v1.0.0.json",
    },
    {
        "model_id": "tensorflow-ic-imagenet-inception-v3-classification-4",
        "version": "2.0.0",
        "min_version": "2.49.0",
        "spec_key": "community_models_specs/tensorflow-ic-imagenet"
        "-inception-v3-classification-4/specs_v2.0.0.json",
    },
    {
        "model_id": "pytorch-ic-imagenet-inception-v3-classification-4",
        "version": "1.0.0",
        "min_version": "2.49.0",
        "spec_key": "community_models_specs/pytorch-ic-"
        "imagenet-inception-v3-classification-4/specs_v1.0.0.json",
    },
    {
        "model_id": "pytorch-ic-imagenet-inception-v3-classification-4",
        "version": "2.0.0",
        "min_version": "2.49.0",
        "spec_key": "community_models_specs/pytorch-ic-imagenet-"
        "inception-v3-classification-4/specs_v2.0.0.json",
    },
    {
        "model_id": "tensorflow-ic-imagenet-inception-v3-classification-4",
        "version": "3.0.0",
        "min_version": "4.49.0",
        "spec_key": "community_models_specs/tensorflow-ic-"
        "imagenet-inception-v3-classification-4/specs_v3.0.0.json",
    },
]