diff --git a/03_finetune_swift.ipynb b/03_finetune_swift.ipynb index da0bbb0..d0bdafb 100644 --- a/03_finetune_swift.ipynb +++ b/03_finetune_swift.ipynb @@ -63,7 +63,7 @@ " get_aws_account_id_for_region,\n", " is_docker_installed,\n", " is_docker_compose_installed,\n", - " check_and_enable_docker_access_sagemaker_studio\n", + " enable_docker_access_sagemaker_studio\n", ")" ] }, @@ -340,7 +340,7 @@ "metadata": {}, "outputs": [], "source": [ - "use_local_mode = True # Set to true to run on local instance\n", + "use_local_mode = False # Set to true to run on local instance\n", "instance_type = \"local_gpu\" if use_local_mode else \"ml.g6.8xlarge\" # \"ml.g6.12xlarge\" " ] }, @@ -354,7 +354,9 @@ " border-radius: 5px; \n", " max-width: 100%;\n", " background: #f0fbff;\">\n", - " Note: If you run into out of memory errors during training use a larger instance type. For example if you are training a larger model or with more data. If you are using local mode then you will need a GPU on your local machine, for example running inside a SageMaker Studio JuypterLab on a ml.g6.8xlarge instance.\n", + " Note: If you run into out of memory errors during training use a larger instance type. For example if you are training a larger model or with more data. \n", + "

\n", + "If you are using local mode then you will need a GPU on your local machine, for example running inside a SageMaker Studio JuypterLab on a ml.g6.8xlarge instance.\n", "" ] }, @@ -373,7 +375,7 @@ "metadata": {}, "outputs": [], "source": [ - "use_spot = True" + "use_spot = True # Set to False to use on-demand instances instead of spot instances." ] }, { @@ -423,7 +425,7 @@ "metadata": {}, "outputs": [], "source": [ - "checkpoint_loc = None" + "checkpoint_loc = None # Default: None - No checkpointing. Re-run cell above \"Note box\" to set checkpoint_loc " ] }, { @@ -724,24 +726,26 @@ { "cell_type": "code", "execution_count": null, - "id": "2d40f9f3-ee0d-4ba0-8472-f6bfde86503c", + "id": "39563e42-1a02-4c14-af64-68101a055633", "metadata": {}, "outputs": [], "source": [ - "if use_local_mode and (not is_docker_installed() or not is_docker_compose_installed()): \n", - " # we need docker and docker-compose for LocalMode execution\n", - " !bash docker-artifacts/01_docker_install.sh" + "if use_local_mode:\n", + " # for local mode we need docker enabled\n", + " # if in SageMaker Studio the following function ensures that docker access is enabled\n", + " enable_docker_access_sagemaker_studio(session)" ] }, { "cell_type": "code", "execution_count": null, - "id": "39563e42-1a02-4c14-af64-68101a055633", + "id": "2d40f9f3-ee0d-4ba0-8472-f6bfde86503c", "metadata": {}, "outputs": [], "source": [ - "# if in SageMaker Studio check if docker access is enabled if it is not enable it\n", - "check_and_enable_docker_access_sagemaker_studio(use_local_mode, session)" + "if use_local_mode and (not is_docker_installed() or not is_docker_compose_installed()): \n", + " # we need docker and docker-compose for LocalMode execution\n", + " !bash docker-artifacts/01_docker_install.sh" ] }, { diff --git a/04_run_batch_inference.ipynb b/04_run_batch_inference.ipynb index 00e5ddf..c34def0 100644 --- a/04_run_batch_inference.ipynb +++ b/04_run_batch_inference.ipynb @@ -65,10 +65,7 @@ " get_sagemaker_distribution, \n", " SageMakerDistribution, \n", " get_python_version, \n", - " get_aws_account_id_for_region,\n", - " is_docker_installed,\n", - " is_docker_compose_installed,\n", - " check_and_enable_docker_access_sagemaker_studio\n", + " get_aws_account_id_for_region\n", ")" ] }, @@ -389,6 +386,30 @@ "sagemaker_dist_uri = f\"{sagemaker_distr_account_id}.dkr.ecr.{region}.amazonaws.com/sagemaker-distribution-prod:{sm_distro_version.image_version}-gpu\"" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "04305c64-7ae5-4ffc-be2f-fe0e6e1a398b", + "metadata": {}, + "outputs": [], + "source": [ + "instance_type = \"ml.g6e.xlarge\"" + ] + }, + { + "cell_type": "markdown", + "id": "d0bb0ade-103c-4746-bd48-524a0fe54de5", + "metadata": {}, + "source": [ + "
\n", + " Note: If you run into out of memory errors during inference use a larger instance type. For example if you have trained a larger model. \n", + "
" + ] + }, { "cell_type": "markdown", "id": "202dfb1b-322c-470d-9191-29490a7ffee6", @@ -521,7 +542,7 @@ " # RoleArn: \n", " S3RootUri: {s3_root_uri}\n", " ImageUri: {sagemaker_dist_uri} \n", - " InstanceType: ml.g6e.4xlarge\n", + " InstanceType: ml.g6e.4xlarge # default instance type to use\n", " Dependencies: requirements.txt\n", " IncludeLocalWorkDir: true\n", " PreExecutionCommands:\n", @@ -610,6 +631,22 @@ "## Batch Inference Function" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "e9050ae0-98eb-48c9-8d76-320a5b4ee86d", + "metadata": {}, + "outputs": [], + "source": [ + "inference_kwargs = {\n", + " \"model_id\":model_config.model_id,\n", + " \"model_type\":model_config.model_type,\n", + " \"dataset_s3\":dataset_s3_uri,\n", + " \"test_data_path\":\"conversations_test_swift_format.json\",\n", + " \"guided_decoding\":guided_decoding\n", + "}" + ] + }, { "cell_type": "code", "execution_count": null, @@ -618,11 +655,11 @@ "outputs": [], "source": [ "@remote(\n", - " instance_type=\"ml.g6e.xlarge\", # Powerful GPU for fast inference\n", + " instance_type=instance_type, # Powerful GPU for fast inference\n", " instance_count=1, # Single instance for cost efficiency\n", " volume_size=200, # Large volume for model and data storage\n", " job_name_prefix=job_name_prefix,\n", - " # use_spot_instances=True, # Cost efficient inference. Inference can be restarted if no spot capacity. \n", + " # use_spot_instances=True, # Enable cost efficient inference. Inference can be restarted if no spot capacity. \n", " max_wait_time_in_seconds=172800, # 48 hours max wait\n", " max_runtime_in_seconds=172800, # 48 hours max runtime\n", ")\n", @@ -710,28 +747,12 @@ }, { "cell_type": "markdown", - "id": "6eb0b491-7f9f-4b83-98d1-daedabe3f311", + "id": "259ae020-c35d-4470-95ce-0043a1b61893", "metadata": {}, "source": [ "## Run Batch Inference" ] }, - { - "cell_type": "code", - "execution_count": null, - "id": "e9050ae0-98eb-48c9-8d76-320a5b4ee86d", - "metadata": {}, - "outputs": [], - "source": [ - "inference_kwargs = {\n", - " \"model_id\":model_config.model_id,\n", - " \"model_type\":model_config.model_type,\n", - " \"dataset_s3\":dataset_s3_uri,\n", - " \"test_data_path\":\"conversations_test_swift_format.json\",\n", - " \"guided_decoding\":guided_decoding\n", - "}" - ] - }, { "cell_type": "code", "execution_count": null, diff --git a/06_deploy_model_endpoint.ipynb b/06_deploy_model_endpoint.ipynb index 55884b4..8dfe450 100644 --- a/06_deploy_model_endpoint.ipynb +++ b/06_deploy_model_endpoint.ipynb @@ -241,7 +241,7 @@ "metadata": {}, "outputs": [], "source": [ - "REPO_NAME = \"swift-json-vlm-container-finetuned\"\n", + "REPO_NAME = \"sagemaker-json-vlm-finetuned\"\n", "os.environ['REPO_NAME'] = REPO_NAME\n", "os.environ[\"S3_MODEL_URI\"]=s3_model_uri" ] diff --git a/utils/training_image.py b/utils/training_image.py index 1370622..38c99ee 100644 --- a/utils/training_image.py +++ b/utils/training_image.py @@ -129,33 +129,32 @@ def load_json_file(file_path): DOCKER_ENABLED = "ENABLED" DOCKER_DISABLED = "DISABLED" -def check_and_enable_docker_access_sagemaker_studio(use_local_mode, session): - if use_local_mode: - resource_metadata = load_json_file(SAGEMAKER_STUDIO_METADATA) - if resource_metadata: - docker_access_disabled = True - docker_access = None - try: - domain_id = resource_metadata["DomainId"] - sm_client = session.boto_session.client("sagemaker") - domain = sm_client.describe_domain(DomainId=domain_id) - if docker_access_disabled := ((docker_access := domain["DomainSettings"]["DockerSettings"]["EnableDockerAccess"]) == DOCKER_DISABLED): - print("Docker disabled on SageMaker Studio domain. Trying to enable docker access...") - sm_client.update_domain( - DomainId=domain_id, - DomainSettingsForUpdate={ - 'DockerSettings': { - 'EnableDockerAccess': DOCKER_ENABLED - } +def enable_docker_access_sagemaker_studio(session): + resource_metadata = load_json_file(SAGEMAKER_STUDIO_METADATA) + if resource_metadata: + docker_access_disabled = True + docker_access = None + try: + domain_id = resource_metadata["DomainId"] + sm_client = session.boto_session.client("sagemaker") + domain = sm_client.describe_domain(DomainId=domain_id) + if docker_access_disabled := ((docker_access := domain["DomainSettings"]["DockerSettings"]["EnableDockerAccess"]) == DOCKER_DISABLED): + print("Docker disabled on SageMaker Studio domain. Trying to enable docker access...") + sm_client.update_domain( + DomainId=domain_id, + DomainSettingsForUpdate={ + 'DockerSettings': { + 'EnableDockerAccess': DOCKER_ENABLED } - ) - time.sleep(4) - domain = sm_client.describe_domain(DomainId=domain_id) - docker_access = domain["DomainSettings"]["DockerSettings"]["EnableDockerAccess"] - docker_access_disabled = (docker_access == DOCKER_DISABLED) - except Exception as e: - print(e) - - print(f"SageMaker Studio domain ({domain_id}) docker access: {docker_access}") - if docker_access_disabled: - print("Failed to enable Docker Access on SageMaker Studio domain. Please enable it manually or ask your administrator. Docker access is required to run in local mode. https://docs.aws.amazon.com/sagemaker/latest/dg/studio-updated-local-get-started.html#studio-updated-local-enable") \ No newline at end of file + } + ) + time.sleep(4) + domain = sm_client.describe_domain(DomainId=domain_id) + docker_access = domain["DomainSettings"]["DockerSettings"]["EnableDockerAccess"] + docker_access_disabled = (docker_access == DOCKER_DISABLED) + except Exception as e: + print(e) + + print(f"SageMaker Studio domain ({domain_id}) docker access: {docker_access}") + if docker_access_disabled: + print("Failed to enable Docker Access on SageMaker Studio domain. Please enable it manually or ask your administrator. Docker access is required to run in local mode. https://docs.aws.amazon.com/sagemaker/latest/dg/studio-updated-local-get-started.html#studio-updated-local-enable") \ No newline at end of file