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#
# 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.
"""Utilities to support workflow."""
from __future__ import absolute_import
import inspect
import logging
from functools import wraps
from pathlib import Path
from typing import List, Sequence, Union, Set, TYPE_CHECKING
import hashlib
from urllib.parse import unquote, urlparse
from _hashlib import HASH as Hash
from sagemaker.workflow.parameters import Parameter
from sagemaker.workflow.pipeline_context import _StepArguments
from sagemaker.workflow.entities import (
Entity,
RequestType,
)
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from sagemaker.workflow.step_collections import StepCollection
BUF_SIZE = 65536 # 64KiB
def list_to_request(entities: Sequence[Union[Entity, "StepCollection"]]) -> List[RequestType]:
"""Get the request structure for list of entities.
Args:
entities (Sequence[Entity]): A list of entities.
Returns:
list: A request structure for a workflow service call.
"""
from sagemaker.workflow.step_collections import StepCollection
request_dicts = []
for entity in entities:
if isinstance(entity, Entity):
request_dicts.append(entity.to_request())
elif isinstance(entity, StepCollection):
request_dicts.extend(entity.request_dicts())
return request_dicts
def hash_file(path: str) -> str:
"""Get the MD5 hash of a file.
Args:
path (str): The local path for the file.
Returns:
str: The MD5 hash of the file.
"""
return _hash_file(path, hashlib.md5()).hexdigest()
def hash_files_or_dirs(paths: List[str]) -> str:
"""Get the MD5 hash of the contents of a list of files or directories.
Hash is changed if:
* input list is changed
* new nested directories/files are added to any directory in the input list
* nested directory/file names are changed for any of the inputted directories
* content of files is edited
Args:
paths: List of file or directory paths
Returns:
str: The MD5 hash of the list of files or directories.
"""
md5 = hashlib.md5()
for path in sorted(paths):
md5 = _hash_file_or_dir(path, md5)
return md5.hexdigest()
def _hash_file_or_dir(path: str, md5: Hash) -> Hash:
"""Updates the inputted Hash with the contents of the current path.
Args:
path: path of file or directory
Returns:
str: The MD5 hash of the file or directory
"""
if isinstance(path, str) and path.lower().startswith("file://"):
path = unquote(urlparse(path).path)
md5.update(path.encode())
if Path(path).is_dir():
md5 = _hash_dir(path, md5)
elif Path(path).is_file():
md5 = _hash_file(path, md5)
return md5
def _hash_dir(directory: Union[str, Path], md5: Hash) -> Hash:
"""Updates the inputted Hash with the contents of the current path.
Args:
directory: path of the directory
Returns:
str: The MD5 hash of the directory
"""
if not Path(directory).is_dir():
raise ValueError(str(directory) + " is not a valid directory")
for path in sorted(Path(directory).iterdir()):
md5.update(path.name.encode())
if path.is_file():
md5 = _hash_file(path, md5)
elif path.is_dir():
md5 = _hash_dir(path, md5)
return md5
def _hash_file(file: Union[str, Path], md5: Hash) -> Hash:
"""Updates the inputted Hash with the contents of the current path.
Args:
file: path of the file
Returns:
str: The MD5 hash of the file
"""
if isinstance(file, str) and file.lower().startswith("file://"):
file = unquote(urlparse(file).path)
if not Path(file).is_file():
raise ValueError(str(file) + " is not a valid file")
with open(file, "rb") as f:
while True:
data = f.read(BUF_SIZE)
if not data:
break
md5.update(data)
return md5
def validate_step_args_input(
step_args: _StepArguments, expected_caller: Set[str], error_message: str
):
"""Validate the `_StepArguments` object which is passed into a pipeline step
Args:
step_args (_StepArguments): A `_StepArguments` object to be used for composing
a pipeline step.
expected_caller (Set[str]): The expected name of the caller function which is
intercepted by the PipelineSession to get the step arguments.
error_message (str): The error message to be thrown if the validation fails.
"""
if not isinstance(step_args, _StepArguments):
raise TypeError(error_message)
if step_args.caller_name not in expected_caller:
raise ValueError(error_message)
def override_pipeline_parameter_var(func):
"""A decorator to override pipeline Parameters passed into a function
This is a temporary decorator to override pipeline Parameter objects with their default value
and display warning information to instruct users to update their code.
This decorator can help to give a grace period for users to update their code when
we make changes to explicitly prevent passing any pipeline variables to a function.
We should remove this decorator after the grace period.
"""
warning_msg_template = (
"The input argument %s of function (%s) is a pipeline variable (%s), which is not allowed. "
"The default_value of this Parameter object will be used to override it. "
"Please make sure the default_value is valid."
)
@wraps(func)
def wrapper(*args, **kwargs):
func_name = "{}.{}".format(func.__module__, func.__name__)
params = inspect.signature(func).parameters
args = list(args)
for i, (arg_name, _) in enumerate(params.items()):
if i >= len(args):
break
if isinstance(args[i], Parameter):
logger.warning(warning_msg_template, arg_name, func_name, type(args[i]))
args[i] = args[i].default_value
args = tuple(args)
for arg_name, value in kwargs.items():
if isinstance(value, Parameter):
logger.warning(warning_msg_template, arg_name, func_name, type(value))
kwargs[arg_name] = value.default_value
return func(*args, **kwargs)
return wrapper
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