Update ModelTrainer to support s3 uri and tar.gz file as source_dir

src/sagemaker/modules/configs.py

@@ -88,7 +88,8 @@ class SourceCode(BaseConfig):
 
     Parameters:
         source_dir (Optional[str]):
-            The local directory containing the source code to be used in the training job container.
+            The local directory, s3 uri, or path to tar.gz file stored locally or in s3 that contains
+            the source code to be used in the training job container.
         requirements (Optional[str]):
             The path within ``source_dir`` to a ``requirements.txt`` file. If specified, the listed
             requirements will be installed in the training job container.

src/sagemaker/modules/train/model_trainer.py

@@ -407,28 +407,45 @@ def _validate_source_code(self, source_code: Optional[SourceCode]):
                         "If 'requirements' or 'entry_script' is provided in 'source_code', "
                         + "'source_dir' must also be provided.",
                     )
-                if not _is_valid_path(source_dir, path_type="Directory"):
+                if not (
+                    _is_valid_path(source_dir, path_type="Directory")
+                    or _is_valid_s3_uri(source_dir, path_type="Directory")
+                    or (
+                        _is_valid_path(source_dir, path_type="File")
+                        and source_dir.endswith(".tar.gz")
+                    )
+                    or (
+                        _is_valid_s3_uri(source_dir, path_type="File")
+                        and source_dir.endswith(".tar.gz")
+                    )
+                ):
                     raise ValueError(
-                        f"Invalid 'source_dir' path: {source_dir}. " + "Must be a valid directory.",
+                        f"Invalid 'source_dir' path: {source_dir}. "
+                        + "Must be a valid local directory, "
+                        "s3 uri or path to tar.gz file stored locally or in s3.",
                     )
                 if requirements:
-                    if not _is_valid_path(
-                        f"{source_dir}/{requirements}",
-                        path_type="File",
-                    ):
-                        raise ValueError(
-                            f"Invalid 'requirements': {requirements}. "
-                            + "Must be a valid file within the 'source_dir'.",
-                        )
+                    if not source_dir.endswith(".tar.gz"):
+                        if not _is_valid_path(
+                            f"{source_dir}/{requirements}", path_type="File"
+                        ) and not _is_valid_s3_uri(
+                            f"{source_dir}/{requirements}", path_type="File"
+                        ):
+                            raise ValueError(
+                                f"Invalid 'requirements': {requirements}. "
+                                + "Must be a valid file within the 'source_dir'.",
+                            )
                 if entry_script:
-                    if not _is_valid_path(
-                        f"{source_dir}/{entry_script}",
-                        path_type="File",
-                    ):
-                        raise ValueError(
-                            f"Invalid 'entry_script': {entry_script}. "
-                            + "Must be a valid file within the 'source_dir'.",
-                        )
+                    if not source_dir.endswith(".tar.gz"):
+                        if not _is_valid_path(
+                            f"{source_dir}/{entry_script}", path_type="File"
+                        ) and not _is_valid_s3_uri(
+                            f"{source_dir}/{entry_script}", path_type="File"
+                        ):
+                            raise ValueError(
+                                f"Invalid 'entry_script': {entry_script}. "
+                                + "Must be a valid file within the 'source_dir'.",
+                            )
 
     def model_post_init(self, __context: Any):
         """Post init method to perform custom validation and set default values."""
@@ -838,12 +855,17 @@ def _prepare_train_script(
 
         install_requirements = ""
         if source_code.requirements:
-            install_requirements = "echo 'Installing requirements'\n"
-            install_requirements = f"$SM_PIP_CMD install -r {source_code.requirements}"
+            install_requirements = (
+                "echo 'Installing requirements'\n"
+                + f"$SM_PIP_CMD install -r {source_code.requirements}"
+            )
 
         working_dir = ""
         if source_code.source_dir:
-            working_dir = f"cd {SM_CODE_CONTAINER_PATH}"
+            working_dir = f"cd {SM_CODE_CONTAINER_PATH} \n"
+            if source_code.source_dir.endswith(".tar.gz"):
+                tarfile_name = os.path.basename(source_code.source_dir)
+                working_dir += f"tar --strip-components=1 -xzf {tarfile_name} \n"
 
         if base_command:
             execute_driver = EXECUTE_BASE_COMMANDS.format(base_command=base_command)

tests/integ/sagemaker/modules/train/test_model_trainer.py

@@ -44,6 +44,24 @@
 
 DEFAULT_CPU_IMAGE = "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:2.0.0-cpu-py310"
 
+TAR_FILE_SOURCE_DIR = f"{DATA_DIR}/modules/script_mode/code.tar.gz"
+TAR_FILE_SOURCE_CODE = SourceCode(
+    source_dir=TAR_FILE_SOURCE_DIR,
+    requirements="requirements.txt",
+    entry_script="custom_script.py",
+)
+
+
+def test_source_dir_local_tar_file(modules_sagemaker_session):
+    model_trainer = ModelTrainer(
+        sagemaker_session=modules_sagemaker_session,
+        training_image=DEFAULT_CPU_IMAGE,
+        source_code=TAR_FILE_SOURCE_CODE,
+        base_job_name="source_dir_local_tar_file",
+    )
+
+    model_trainer.train()
+
 
 def test_hp_contract_basic_py_script(modules_sagemaker_session):
     model_trainer = ModelTrainer(

tests/unit/sagemaker/modules/train/test_model_trainer.py

@@ -92,9 +92,6 @@
     source_dir=DEFAULT_SOURCE_DIR,
     entry_script="custom_script.py",
 )
-UNSUPPORTED_SOURCE_CODE = SourceCode(
-    entry_script="train.py",
-)
 DEFAULT_ENTRYPOINT = ["/bin/bash"]
 DEFAULT_ARGUMENTS = [
     "-c",
@@ -152,7 +149,19 @@ def model_trainer():
         {
             "init_params": {
                 "training_image": DEFAULT_IMAGE,
-                "source_code": UNSUPPORTED_SOURCE_CODE,
+                "source_code": SourceCode(
+                    entry_script="train.py",
+                ),
+            },
+            "should_throw": True,
+        },
+        {
+            "init_params": {
+                "training_image": DEFAULT_IMAGE,
+                "source_code": SourceCode(
+                    source_dir="s3://bucket/requirements.txt",
+                    entry_script="custom_script.py",
+                ),
             },
             "should_throw": True,
         },
@@ -163,13 +172,47 @@ def model_trainer():
             },
             "should_throw": False,
         },
+        {
+            "init_params": {
+                "training_image": DEFAULT_IMAGE,
+                "source_code": SourceCode(
+                    source_dir=f"{DEFAULT_SOURCE_DIR}/code.tar.gz",
+                    entry_script="custom_script.py",
+                ),
+            },
+            "should_throw": False,
+        },
+        {
+            "init_params": {
+                "training_image": DEFAULT_IMAGE,
+                "source_code": SourceCode(
+                    source_dir="s3://bucket/code/",
+                    entry_script="custom_script.py",
+                ),
+            },
+            "should_throw": False,
+        },
+        {
+            "init_params": {
+                "training_image": DEFAULT_IMAGE,
+                "source_code": SourceCode(
+                    source_dir="s3://bucket/code/code.tar.gz",
+                    entry_script="custom_script.py",
+                ),
+            },
+            "should_throw": False,
+        },
     ],
     ids=[
         "no_params",
         "training_image_and_algorithm_name",
         "only_training_image",
-        "unsupported_source_code",
-        "supported_source_code",
+        "unsupported_source_code_missing_source_dir",
+        "unsupported_source_code_s3_other_file",
+        "supported_source_code_local_dir",
+        "supported_source_code_local_tar_file",
+        "supported_source_code_s3_dir",
+        "supported_source_code_s3_tar_file",
     ],
 )
 def test_model_trainer_param_validation(test_case, modules_session):