"""Task: a coarse-grained stage in an application."""
import collections
import inspect
import json
import os
import re
import typing
from typing import (Any, Callable, Dict, Iterable, List, Optional, Set, Tuple,
                    Union)

import colorama

import sky
from sky import clouds
from sky import exceptions
from sky import sky_logging
from sky.adaptors import common as adaptors_common
import sky.dag
from sky.data import data_utils
from sky.data import storage as storage_lib
from sky.provision import docker_utils
from sky.serve import service_spec
from sky.skylet import constants
from sky.utils import common_utils
from sky.utils import schemas
from sky.utils import ux_utils

if typing.TYPE_CHECKING:
    import yaml

    from sky import resources as resources_lib
else:
    yaml = adaptors_common.LazyImport('yaml')

logger = sky_logging.init_logger(__name__)

# A lambda generating commands (node rank_i, node addrs -> cmd_i).
CommandGen = Callable[[int, List[str]], Optional[str]]
CommandOrCommandGen = Union[str, CommandGen]

_VALID_NAME_REGEX = '[a-zA-Z0-9]+(?:[._-]{1,2}[a-zA-Z0-9]+)*'
_VALID_NAME_DESCR = ('ASCII characters and may contain lowercase and'
                     ' uppercase letters, digits, underscores, periods,'
                     ' and dashes. Must start and end with alphanumeric'
                     ' characters. No triple dashes or underscores.')

_RUN_FN_CHECK_FAIL_MSG = (
    'run command generator must take exactly 2 arguments: node_rank (int) and'
    'a list of node ip addresses (List[str]). Got {run_sig}')


def _is_valid_name(name: Optional[str]) -> bool:
    """Checks if the task name is valid.

    Valid is defined as either NoneType or str with ASCII characters which may
    contain lowercase and uppercase letters, digits, underscores, periods,
    and dashes. Must start and end with alphanumeric characters.
    No triple dashes or underscores.

    Examples:
        some_name_here
        some-name-here
        some__name__here
        some--name--here
        some__name--here
        some.name.here
        some-name_he.re
        this---shouldnt--work
        this___shouldnt_work
        _thisshouldntwork
        thisshouldntwork_
    """
    if name is None:
        return True
    return bool(re.fullmatch(_VALID_NAME_REGEX, name))


def _fill_in_env_vars(
    yaml_field: Dict[str, Any],
    task_envs: Dict[str, str],
) -> Dict[str, Any]:
    """Detects env vars in yaml field and fills them with task_envs.

    Use cases of env vars in file_mounts:
    - dst/src paths; e.g.,
        /model_path/llama-${SIZE}b: s3://llama-weights/llama-${SIZE}b
    - storage's name (bucket name)
    - storage's source (local path)

    Use cases of env vars in service:
    - model type; e.g.,
        service:
          readiness_probe:
            path: /v1/chat/completions
            post_data:
              model: $MODEL_NAME
              messages:
                - role: user
                  content: How to print hello world?
              max_tokens: 1

    We simply dump yaml_field into a json string, and replace env vars using
    regex. This should be safe as yaml config has been schema-validated.

    Env vars of the following forms are detected:
        - ${ENV}
        - $ENV
    where <ENV> must appear in task.envs.
    """
    # TODO(zongheng): support ${ENV:-default}?
    yaml_field_str = json.dumps(yaml_field)

    def replace_var(match):
        var_name = match.group(1)
        # If the variable isn't in the dictionary, return it unchanged
        return task_envs.get(var_name, match.group(0))

    # Pattern for valid env var names in bash.
    pattern = r'\$\{?\b([a-zA-Z_][a-zA-Z0-9_]*)\b\}?'
    yaml_field_str = re.sub(pattern, replace_var, yaml_field_str)
    return json.loads(yaml_field_str)


def _check_docker_login_config(task_envs: Dict[str, str]) -> bool:
    """Checks if there is a valid docker login config in task_envs.

    If any of the docker login env vars is set, all of them must be set.

    Returns:
        True if there is a valid docker login config in task_envs.
        False otherwise.
    Raises:
        ValueError: if any of the docker login env vars is set, but not all of
            them are set.
    """
    all_keys = constants.DOCKER_LOGIN_ENV_VARS
    existing_keys = all_keys & set(task_envs.keys())
    if not existing_keys:
        return False
    if len(existing_keys) != len(all_keys):
        with ux_utils.print_exception_no_traceback():
            raise ValueError(
                f'If any of {", ".join(all_keys)} is set, all of them must '
                f'be set. Missing envs: {all_keys - existing_keys}')
    return True


def _with_docker_login_config(
    resources: Union[Set['resources_lib.Resources'],
                     List['resources_lib.Resources']],
    task_envs: Dict[str, str],
) -> Union[Set['resources_lib.Resources'], List['resources_lib.Resources']]:
    if not _check_docker_login_config(task_envs):
        return resources
    docker_login_config = docker_utils.DockerLoginConfig.from_env_vars(
        task_envs)

    def _add_docker_login_config(resources: 'resources_lib.Resources'):
        docker_image = resources.extract_docker_image()
        if docker_image is None:
            logger.warning(f'{colorama.Fore.YELLOW}Docker login configs '
                           f'{", ".join(constants.DOCKER_LOGIN_ENV_VARS)} '
                           'are provided, but no docker image is specified '
                           'in `image_id`. The login configs will be '
                           f'ignored.{colorama.Style.RESET_ALL}')
            return resources
        # Already checked in extract_docker_image
        assert resources.image_id is not None and len(
            resources.image_id) == 1, resources.image_id
        region = list(resources.image_id.keys())[0]
        return resources.copy(image_id={region: 'docker:' + docker_image},
                              _docker_login_config=docker_login_config)

    new_resources = []
    for r in resources:
        new_resources.append(_add_docker_login_config(r))
    return type(resources)(new_resources)


def _with_docker_username_for_runpod(
    resources: Union[Set['resources_lib.Resources'],
                     List['resources_lib.Resources']],
    task_envs: Dict[str, str],
) -> Union[Set['resources_lib.Resources'], List['resources_lib.Resources']]:
    docker_username_for_runpod = task_envs.get(
        constants.RUNPOD_DOCKER_USERNAME_ENV_VAR)

    # We should not call r.copy() if docker_username_for_runpod is None,
    # to prevent `DummyResources` instance becoming a `Resources` instance.
    if docker_username_for_runpod is None:
        return resources
    return (type(resources)(
        r.copy(_docker_username_for_runpod=docker_username_for_runpod)
        for r in resources))


class Task:
    """Task: a computation to be run on the cloud."""

    def __init__(
        self,
        name: Optional[str] = None,
        *,
        setup: Optional[str] = None,
        run: Optional[CommandOrCommandGen] = None,
        envs: Optional[Dict[str, str]] = None,
        workdir: Optional[str] = None,
        num_nodes: Optional[int] = None,
        # Advanced:
        docker_image: Optional[str] = None,
        event_callback: Optional[str] = None,
        blocked_resources: Optional[Iterable['resources_lib.Resources']] = None,
        # Internal use only.
        file_mounts_mapping: Optional[Dict[str, str]] = None,
    ):
        """Initializes a Task.

        All fields are optional.  ``Task.run`` is the actual program: either a
        shell command to run (str) or a command generator for different nodes
        (lambda; see below).

        Optionally, call ``Task.set_resources()`` to set the resource
        requirements for this task.  If not set, a default CPU-only requirement
        is assumed (the same as ``sky launch``).

        All setters of this class, ``Task.set_*()``, return ``self``, i.e.,
        they are fluent APIs and can be chained together.

        Example:
            .. code-block:: python

                # A Task that will sync up local workdir '.', containing
                # requirements.txt and train.py.
                sky.Task(setup='pip install requirements.txt',
                         run='python train.py',
                         workdir='.')

                # An empty Task for provisioning a cluster.
                task = sky.Task(num_nodes=n).set_resources(...)

                # Chaining setters.
                sky.Task().set_resources(...).set_file_mounts(...)

        Args:
          name: A string name for the Task for display purposes.
          setup: A setup command, which will be run before executing the run
            commands ``run``, and executed under ``workdir``.
          run: The actual command for the task. If not None, either a shell
            command (str) or a command generator (callable).  If latter, it
            must take a node rank and a list of node addresses as input and
            return a shell command (str) (valid to return None for some nodes,
            in which case no commands are run on them).  Run commands will be
            run under ``workdir``. Note the command generator should be a
            self-contained lambda.
          envs: A dictionary of environment variables to set before running the
            setup and run commands.
          workdir: The local working directory.  This directory will be synced
            to a location on the remote VM(s), and ``setup`` and ``run``
            commands will be run under that location (thus, they can rely on
            relative paths when invoking binaries).
          num_nodes: The number of nodes to provision for this Task.  If None,
            treated as 1 node.  If > 1, each node will execute its own
            setup/run command, where ``run`` can either be a str, meaning all
            nodes get the same command, or a lambda, with the semantics
            documented above.
          docker_image: (EXPERIMENTAL: Only in effect when LocalDockerBackend
            is used.) The base docker image that this Task will be built on.
            Defaults to 'gpuci/miniforge-cuda:11.4-devel-ubuntu18.04'.
          blocked_resources: A set of resources that this task cannot run on.
        """
        self.name = name
        self.run = run
        self.storage_mounts: Dict[str, storage_lib.Storage] = {}
        self.storage_plans: Dict[storage_lib.Storage,
                                 storage_lib.StoreType] = {}
        self.setup = setup
        self._envs = envs or {}
        self.workdir = workdir
        self.docker_image = (docker_image if docker_image else
                             'gpuci/miniforge-cuda:11.4-devel-ubuntu18.04')
        self.event_callback = event_callback
        # Ignore type error due to a mypy bug.
        # https://github.com/python/mypy/issues/3004
        self._num_nodes = 1
        self.num_nodes = num_nodes  # type: ignore

        self.inputs: Optional[str] = None
        self.outputs: Optional[str] = None
        self.estimated_inputs_size_gigabytes: Optional[float] = None
        self.estimated_outputs_size_gigabytes: Optional[float] = None
        # Default to CPU VM
        self.resources: Union[List[sky.Resources],
                              Set[sky.Resources]] = {sky.Resources()}
        self._service: Optional[service_spec.SkyServiceSpec] = None
        # The priority of the managed job running this task.
        self._job_priority: Optional[int] = None
        # Resources that this task cannot run on.
        self.blocked_resources = blocked_resources

        self.time_estimator_func: Optional[Callable[['sky.Resources'],
                                                    int]] = None
        self.file_mounts: Optional[Dict[str, str]] = None

        # Only set when 'self' is a jobs controller task: 'self.managed_job_dag'
        # is the underlying managed job dag (sky.Dag object).
        self.managed_job_dag: Optional['sky.Dag'] = None

        # Only set when 'self' is a sky serve controller task.
        self.service_name: Optional[str] = None

        # Filled in by the optimizer.  If None, this Task is not planned.
        self.best_resources: Optional[sky.Resources] = None

        # For internal use only.
        self.file_mounts_mapping = file_mounts_mapping

        dag = sky.dag.get_current_dag()
        if dag is not None:
            dag.add(self)

    def validate(self,
                 skip_file_mounts: bool = False,
                 skip_workdir: bool = False):
        """Validate all fields of the task.

        Args:
            skip_file_mounts: Whether to skip validating file mounts.
            skip_workdir: Whether to skip validating workdir.
        """
        self.validate_name()
        self.validate_run()
        if not skip_workdir:
            self.expand_and_validate_workdir()
        if not skip_file_mounts:
            self.expand_and_validate_file_mounts()
        for r in self.resources:
            r.validate()

    def validate_name(self):
        """Validates if the task name is valid."""
        if not _is_valid_name(self.name):
            with ux_utils.print_exception_no_traceback():
                raise ValueError(f'Invalid task name {self.name}. Valid name: '
                                 f'{_VALID_NAME_DESCR}')

    def validate_run(self):
        """Validates if the run command is valid."""
        if callable(self.run):
            run_sig = inspect.signature(self.run)
            # Check that run is a function with 2 arguments.
            if len(run_sig.parameters) != 2:
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(_RUN_FN_CHECK_FAIL_MSG.format(run_sig))

            type_list = [int, List[str]]
            # Check annotations, if exists
            for i, param in enumerate(run_sig.parameters.values()):
                if param.annotation != inspect.Parameter.empty:
                    if param.annotation != type_list[i]:
                        with ux_utils.print_exception_no_traceback():
                            raise ValueError(
                                _RUN_FN_CHECK_FAIL_MSG.format(run_sig))

            # Check self containedness.
            run_closure = inspect.getclosurevars(self.run)
            if run_closure.nonlocals:
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        'run command generator must be self contained. '
                        f'Found nonlocals: {run_closure.nonlocals}')
            if run_closure.globals:
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        'run command generator must be self contained. '
                        f'Found globals: {run_closure.globals}')
            if run_closure.unbound:
                # Do not raise an error here. Import statements, which are
                # allowed, will be considered as unbounded.
                pass
        elif self.run is not None and not isinstance(self.run, str):
            with ux_utils.print_exception_no_traceback():
                raise ValueError('run must be either a shell script (str) or '
                                 f'a command generator ({CommandGen}). '
                                 f'Got {type(self.run)}')

    def expand_and_validate_file_mounts(self):
        """Expand file_mounts paths to absolute paths and validate them.

        Note: if this function is called on a remote SkyPilot API server,
        it must be after the client side has sync-ed all files to the
        remote server.
        """
        if self.file_mounts is None:
            return
        for target, source in self.file_mounts.items():
            if target.endswith('/') or source.endswith('/'):
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        'File mount paths cannot end with a slash '
                        '(try "/mydir: /mydir" or "/myfile: /myfile"). '
                        f'Found: target={target} source={source}')
            if data_utils.is_cloud_store_url(target):
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        'File mount destination paths cannot be cloud storage')
            if not data_utils.is_cloud_store_url(source):
                self.file_mounts[target] = os.path.abspath(
                    os.path.expanduser(source))
                if not os.path.exists(self.file_mounts[target]
                                     ) and not source.startswith('skypilot:'):
                    with ux_utils.print_exception_no_traceback():
                        raise ValueError(
                            f'File mount source {source!r} does not exist '
                            'locally. To fix: check if it exists, and correct '
                            'the path.')
            # TODO(zhwu): /home/username/sky_workdir as the target path need
            # to be filtered out as well.
            if (target == constants.SKY_REMOTE_WORKDIR and
                    self.workdir is not None):
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        f'Cannot use {constants.SKY_REMOTE_WORKDIR!r} as a '
                        'destination path of a file mount, as it will be used '
                        'by the workdir. If uploading a file/folder to the '
                        'workdir is needed, please specify the full path to '
                        'the file/folder.')

    def expand_and_validate_workdir(self):
        """Expand workdir to absolute path and validate it.

        Note: if this function is called on a remote SkyPilot API server,
        it must be after the client side has sync-ed all files to the
        remote server.
        """
        if self.workdir is None:
            return
        user_workdir = self.workdir
        self.workdir = os.path.abspath(os.path.expanduser(user_workdir))
        if not os.path.isdir(self.workdir):
            # Symlink to a dir is legal (isdir() follows symlinks).
            with ux_utils.print_exception_no_traceback():
                raise ValueError(
                    'Workdir must be a valid directory (or '
                    f'a symlink to a directory). {user_workdir} not found.')

    @staticmethod
    def from_yaml_config(
        config: Dict[str, Any],
        env_overrides: Optional[List[Tuple[str, str]]] = None,
    ) -> 'Task':
        # More robust handling for 'envs': explicitly convert keys and values to
        # str, since users may pass '123' as keys/values which will get parsed
        # as int causing validate_schema() to fail.
        envs = config.get('envs')
        if envs is not None and isinstance(envs, dict):
            new_envs: Dict[str, Optional[str]] = {}
            for k, v in envs.items():
                if v is not None:
                    new_envs[str(k)] = str(v)
                else:
                    new_envs[str(k)] = None
            config['envs'] = new_envs
        common_utils.validate_schema(config, schemas.get_task_schema(),
                                     'Invalid task YAML: ')
        if env_overrides is not None:
            # We must override env vars before constructing the Task, because
            # the Storage object creation is eager and it (its name/source
            # fields) may depend on env vars.
            #
            # FIXME(zongheng): The eagerness / how we construct Task's from
            # entrypoint (YAML, CLI args) should be fixed.
            new_envs = config.get('envs', {})
            new_envs.update(env_overrides)
            config['envs'] = new_envs

        for k, v in config.get('envs', {}).items():
            if v is None:
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        f'Environment variable {k!r} is None. Please set a '
                        'value for it in task YAML or with --env flag. '
                        f'To set it to be empty, use an empty string ({k}: "" '
                        f'in task YAML or --env {k}="" in CLI).')

        # Fill in any Task.envs into file_mounts (src/dst paths, storage
        # name/source).
        if config.get('file_mounts') is not None:
            config['file_mounts'] = _fill_in_env_vars(config['file_mounts'],
                                                      config.get('envs', {}))

        # Fill in any Task.envs into service (e.g. MODEL_NAME).
        if config.get('service') is not None:
            config['service'] = _fill_in_env_vars(config['service'],
                                                  config.get('envs', {}))

        # Fill in any Task.envs into workdir
        if config.get('workdir') is not None:
            config['workdir'] = _fill_in_env_vars(config['workdir'],
                                                  config.get('envs', {}))

        task = Task(
            config.pop('name', None),
            run=config.pop('run', None),
            workdir=config.pop('workdir', None),
            setup=config.pop('setup', None),
            num_nodes=config.pop('num_nodes', None),
            envs=config.pop('envs', None),
            event_callback=config.pop('event_callback', None),
            file_mounts_mapping=config.pop('file_mounts_mapping', None),
        )

        # Create lists to store storage objects inlined in file_mounts.
        # These are retained in dicts in the YAML schema and later parsed to
        # storage objects with the storage/storage_mount objects.
        fm_storages = []
        file_mounts = config.pop('file_mounts', None)
        volumes = []
        if file_mounts is not None:
            copy_mounts = {}
            for dst_path, src in file_mounts.items():
                # Check if it is str path
                if isinstance(src, str):
                    copy_mounts[dst_path] = src
                # If the src is not a str path, it is likely a dict. Try to
                # parse storage object.
                elif isinstance(src, dict):
                    if (src.get('store') ==
                            storage_lib.StoreType.VOLUME.value.lower()):
                        # Build the volumes config for resources.
                        volume_config = {
                            'path': dst_path,
                        }
                        if src.get('name'):
                            volume_config['name'] = src.get('name')
                        persistent = src.get('persistent', False)
                        volume_config['auto_delete'] = not persistent
                        volume_config_detail = src.get('config', {})
                        volume_config.update(volume_config_detail)
                        volumes.append(volume_config)
                        source_path = src.get('source')
                        if source_path:
                            # For volume, copy the source path to the
                            # data directory of the volume mount point.
                            copy_mounts[
                                f'{dst_path.rstrip("/")}/data'] = source_path
                    else:
                        fm_storages.append((dst_path, src))
                else:
                    with ux_utils.print_exception_no_traceback():
                        raise ValueError(f'Unable to parse file_mount '
                                         f'{dst_path}:{src}')
            task.set_file_mounts(copy_mounts)

        task_storage_mounts: Dict[str, storage_lib.Storage] = {}
        all_storages = fm_storages
        for storage in all_storages:
            mount_path = storage[0]
            assert mount_path, 'Storage mount path cannot be empty.'
            try:
                storage_obj = storage_lib.Storage.from_yaml_config(storage[1])
            except exceptions.StorageSourceError as e:
                # Patch the error message to include the mount path, if included
                e.args = (e.args[0].replace('<destination_path>',
                                            mount_path),) + e.args[1:]
                raise e
            task_storage_mounts[mount_path] = storage_obj
        task.set_storage_mounts(task_storage_mounts)

        if config.get('inputs') is not None:
            inputs_dict = config.pop('inputs')
            assert len(inputs_dict) == 1, 'Only one input is allowed.'
            inputs = list(inputs_dict.keys())[0]
            estimated_size_gigabytes = list(inputs_dict.values())[0]
            # TODO: allow option to say (or detect) no download/egress cost.
            task.set_inputs(inputs=inputs,
                            estimated_size_gigabytes=estimated_size_gigabytes)

        if config.get('outputs') is not None:
            outputs_dict = config.pop('outputs')
            assert len(outputs_dict) == 1, 'Only one output is allowed.'
            outputs = list(outputs_dict.keys())[0]
            estimated_size_gigabytes = list(outputs_dict.values())[0]
            task.set_outputs(outputs=outputs,
                             estimated_size_gigabytes=estimated_size_gigabytes)

        # Experimental configs.
        experimental_configs = config.pop('experimental', None)

        # Handle the top-level config field
        config_override = config.pop('config', None)

        # Handle backward compatibility with experimental.config_overrides
        # TODO: Remove experimental.config_overrides in 0.11.0.
        if experimental_configs is not None:
            exp_config_override = experimental_configs.pop(
                'config_overrides', None)
            if exp_config_override is not None:
                logger.warning(
                    f'{colorama.Fore.YELLOW}`experimental.config_overrides` '
                    'field is deprecated in the task YAML. Use the `config` '
                    f'field to set config overrides.{colorama.Style.RESET_ALL}')
                if config_override is not None:
                    logger.warning(
                        f'{colorama.Fore.YELLOW}Both top-level `config` and '
                        f'`experimental.config_overrides` are specified. '
                        f'Using top-level `config`.{colorama.Style.RESET_ALL}')
                else:
                    config_override = exp_config_override
            logger.debug('Overriding skypilot config with task-level config: '
                         f'{config_override}')
            assert not experimental_configs, ('Invalid task args: '
                                              f'{experimental_configs.keys()}')

        # Store the final config override for use in resource setup
        cluster_config_override = config_override

        # Parse resources field.
        resources_config = config.pop('resources', {})
        if cluster_config_override is not None:
            assert resources_config.get('_cluster_config_overrides') is None, (
                'Cannot set _cluster_config_overrides in both resources and '
                'experimental.config_overrides')
            resources_config[
                '_cluster_config_overrides'] = cluster_config_override
        if volumes:
            resources_config['volumes'] = volumes
        task.set_resources(sky.Resources.from_yaml_config(resources_config))

        service = config.pop('service', None)
        if service is not None:
            service = service_spec.SkyServiceSpec.from_yaml_config(service)
        task.set_service(service)

        job = config.pop('job', None)
        if job is not None and 'priority' in job:
            task.set_job_priority(job['priority'])

        assert not config, f'Invalid task args: {config.keys()}'
        return task

    @staticmethod
    def from_yaml(yaml_path: str) -> 'Task':
        """Initializes a task from a task YAML.

        Example:
            .. code-block:: python

                task = sky.Task.from_yaml('/path/to/task.yaml')

        Args:
          yaml_path: file path to a valid task yaml file.

        Raises:
          ValueError: if the path gets loaded into a str instead of a dict; or
            if there are any other parsing errors.
        """
        with open(os.path.expanduser(yaml_path), 'r', encoding='utf-8') as f:
            # TODO(zongheng): use
            #  https://github.com/yaml/pyyaml/issues/165#issuecomment-430074049
            # to raise errors on duplicate keys.
            config = yaml.safe_load(f)

        if isinstance(config, str):
            with ux_utils.print_exception_no_traceback():
                raise ValueError('YAML loaded as str, not as dict. '
                                 f'Is it correct? Path: {yaml_path}')

        if config is None:
            config = {}
        return Task.from_yaml_config(config)

    @property
    def num_nodes(self) -> int:
        return self._num_nodes

    @num_nodes.setter
    def num_nodes(self, num_nodes: Optional[int]) -> None:
        if num_nodes is None:
            num_nodes = 1
        if not isinstance(num_nodes, int) or num_nodes <= 0:
            with ux_utils.print_exception_no_traceback():
                raise ValueError(
                    f'num_nodes should be a positive int. Got: {num_nodes}')
        self._num_nodes = num_nodes

    @property
    def envs(self) -> Dict[str, str]:
        return self._envs

    def update_envs(
            self, envs: Union[None, List[Tuple[str, str]],
                              Dict[str, str]]) -> 'Task':
        """Updates environment variables for use inside the setup/run commands.

        Args:
          envs: (optional) either a list of ``(env_name, value)`` or a dict
            ``{env_name: value}``.

        Returns:
          self: The current task, with envs updated.

        Raises:
          ValueError: if various invalid inputs errors are detected.
        """
        if envs is None:
            envs = {}
        if isinstance(envs, (list, tuple)):
            keys = set(env[0] for env in envs)
            if len(keys) != len(envs):
                with ux_utils.print_exception_no_traceback():
                    raise ValueError('Duplicate env keys provided.')
            envs = dict(envs)
        if isinstance(envs, dict):
            for key in envs:
                if not isinstance(key, str):
                    with ux_utils.print_exception_no_traceback():
                        raise ValueError('Env keys must be strings.')
                if not common_utils.is_valid_env_var(key):
                    with ux_utils.print_exception_no_traceback():
                        raise ValueError(f'Invalid env key: {key}')
        else:
            with ux_utils.print_exception_no_traceback():
                raise ValueError(
                    'envs must be List[Tuple[str, str]] or Dict[str, str]: '
                    f'{envs}')
        self._envs.update(envs)
        # If the update_envs() is called after set_resources(), we need to
        # manually update docker login config in task resources, in case the
        # docker login envs are newly added.
        if _check_docker_login_config(self._envs):
            self.resources = _with_docker_login_config(self.resources,
                                                       self._envs)
        self.resources = _with_docker_username_for_runpod(
            self.resources, self._envs)
        return self

    @property
    def use_spot(self) -> bool:
        return any(r.use_spot for r in self.resources)

    def set_inputs(self, inputs: str,
                   estimated_size_gigabytes: float) -> 'Task':
        # E.g., 's3://bucket', 'gs://bucket', or None.
        self.inputs = inputs
        self.estimated_inputs_size_gigabytes = estimated_size_gigabytes
        return self

    def get_inputs(self) -> Optional[str]:
        return self.inputs

    def get_estimated_inputs_size_gigabytes(self) -> Optional[float]:
        return self.estimated_inputs_size_gigabytes

    def get_inputs_cloud(self):
        """EXPERIMENTAL: Returns the cloud my inputs live in."""
        assert isinstance(self.inputs, str), self.inputs
        if self.inputs.startswith('s3:'):
            return clouds.AWS()
        elif self.inputs.startswith('gs:'):
            return clouds.GCP()
        elif self.inputs.startswith('cos:'):
            return clouds.IBM()
        else:
            with ux_utils.print_exception_no_traceback():
                raise ValueError(f'cloud path not supported: {self.inputs}')

    def set_outputs(self, outputs: str,
                    estimated_size_gigabytes: float) -> 'Task':
        self.outputs = outputs
        self.estimated_outputs_size_gigabytes = estimated_size_gigabytes
        return self

    def get_outputs(self) -> Optional[str]:
        return self.outputs

    def get_estimated_outputs_size_gigabytes(self) -> Optional[float]:
        return self.estimated_outputs_size_gigabytes

    def set_resources(
        self, resources: Union['resources_lib.Resources',
                               List['resources_lib.Resources'],
                               Set['resources_lib.Resources']]
    ) -> 'Task':
        """Sets the required resources to execute this task.

        If this function is not called for a Task, default resource
        requirements will be used (8 vCPUs).

        Args:
          resources: either a sky.Resources, a set of them, or a list of them.
            A set or a list of resources asks the optimizer to "pick the
            best of these resources" to run this task.
        Returns:
          self: The current task, with resources set.
        """
        if isinstance(resources, sky.Resources):
            resources = {resources}
        # TODO(woosuk): Check if the resources are None.
        self.resources = _with_docker_login_config(resources, self.envs)
        # Only have effect on RunPod.
        self.resources = _with_docker_username_for_runpod(
            self.resources, self.envs)

        # Evaluate if the task requires FUSE and set the requires_fuse flag
        for _, storage_obj in self.storage_mounts.items():
            if storage_obj.mode in storage_lib.MOUNTABLE_STORAGE_MODES:
                for r in self.resources:
                    r.set_requires_fuse(True)
                break

        return self

    def set_resources_override(self, override_params: Dict[str, Any]) -> 'Task':
        """Sets the override parameters for the resources."""
        new_resources_list = []
        for res in list(self.resources):
            new_resources = res.copy(**override_params)
            new_resources_list.append(new_resources)

        self.set_resources(type(self.resources)(new_resources_list))
        return self

    @property
    def service(self) -> Optional[service_spec.SkyServiceSpec]:
        return self._service

    def set_service(self,
                    service: Optional[service_spec.SkyServiceSpec]) -> 'Task':
        """Sets the service spec for this task.

        Args:
          service: a SkyServiceSpec object.

        Returns:
          self: The current task, with service set.
        """
        self._service = service
        return self

    @property
    def job_priority(self) -> Optional[int]:
        """The priority of the managed job running this task."""
        return self._job_priority

    def set_job_priority(self, priority: int) -> 'Task':
        """Sets the job priority for this task.

        Args:
          priority: an integer between 0 and 1000.

        Returns:
          self: The current task, with job priority set.
        """
        self._job_priority = priority
        return self

    def set_time_estimator(self, func: Callable[['sky.Resources'],
                                                int]) -> 'Task':
        """Sets a func mapping resources to estimated time (secs).

        This is EXPERIMENTAL.
        """
        self.time_estimator_func = func
        return self

    def estimate_runtime(self, resources):
        """Returns a func mapping resources to estimated time (secs).

        This is EXPERIMENTAL.
        """
        if self.time_estimator_func is None:
            raise NotImplementedError(
                f'Node [{self}] does not have a cost model set; '
                'call set_time_estimator() first')
        return self.time_estimator_func(resources)

    def set_file_mounts(self, file_mounts: Optional[Dict[str, str]]) -> 'Task':
        """Sets the file mounts for this task.

        Useful for syncing datasets, dotfiles, etc.

        File mounts are a dictionary: ``{remote_path: local_path/cloud URI}``.
        Local (or cloud) files/directories will be synced to the specified
        paths on the remote VM(s) where this Task will run.

        Neither source or destimation paths can end with a slash.

        Example:
            .. code-block:: python

                task.set_file_mounts({
                    '~/.dotfile': '/local/.dotfile',
                    # /remote/dir/ will contain the contents of /local/dir/.
                    '/remote/dir': '/local/dir',
                })

        Args:
          file_mounts: an optional dict of ``{remote_path: local_path/cloud
            URI}``, where remote means the VM(s) on which this Task will
            eventually run on, and local means the node from which the task is
            launched.

        Returns:
          self: the current task, with file mounts set.
        """
        self.file_mounts = file_mounts
        return self

    def update_file_mounts(self, file_mounts: Dict[str, str]) -> 'Task':
        """Updates the file mounts for this task.

        Different from set_file_mounts(), this function updates into the
        existing file_mounts (calls ``dict.update()``), rather than
        overwritting it.

        This should be called before provisioning in order to take effect.

        Example:
            .. code-block:: python

                task.update_file_mounts({
                    '~/.config': '~/Documents/config',
                    '/tmp/workdir': '/local/workdir/cnn-cifar10',
                })

        Args:
          file_mounts: a dict of ``{remote_path: local_path/cloud URI}``, where
            remote means the VM(s) on which this Task will eventually run on,
            and local means the node from which the task is launched.

        Returns:
          self: the current task, with file mounts updated.

        Raises:
          ValueError: if input paths are invalid.
        """
        if self.file_mounts is None:
            self.file_mounts = {}
        assert self.file_mounts is not None
        self.file_mounts.update(file_mounts)
        self.expand_and_validate_file_mounts()
        return self

    def set_storage_mounts(
        self,
        storage_mounts: Optional[Dict[str, storage_lib.Storage]],
    ) -> 'Task':
        """Sets the storage mounts for this task.

        Storage mounts are a dictionary: ``{mount_path: sky.Storage object}``,
        each of which mounts a sky.Storage object (a cloud object store bucket)
        to a path inside the remote cluster.

        A sky.Storage object can be created by uploading from a local directory
        (setting ``source``), or backed by an existing cloud bucket (setting
        ``name`` to the bucket name; or setting ``source`` to the bucket URI).

        Example:
            .. code-block:: python

                task.set_storage_mounts({
                    '/remote/imagenet/': sky.Storage(name='my-bucket',
                                                     source='/local/imagenet'),
                })

        Args:
          storage_mounts: an optional dict of ``{mount_path: sky.Storage
            object}``, where mount_path is the path inside the remote VM(s)
            where the Storage object will be mounted on.

        Returns:
          self: The current task, with storage mounts set.

        Raises:
          ValueError: if input paths are invalid.
        """
        if storage_mounts is None:
            self.storage_mounts = {}
            # Clear the requires_fuse flag if no storage mounts are set.
            for r in self.resources:
                r.set_requires_fuse(False)
            return self
        for target, storage_obj in storage_mounts.items():
            # TODO(zhwu): /home/username/sky_workdir as the target path need
            # to be filtered out as well.
            if (target == constants.SKY_REMOTE_WORKDIR and
                    self.workdir is not None):
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        f'Cannot use {constants.SKY_REMOTE_WORKDIR!r} as a '
                        'destination path of a file mount, as it will be used '
                        'by the workdir. If uploading a file/folder to the '
                        'workdir is needed, please specify the full path to '
                        'the file/folder.')

            if data_utils.is_cloud_store_url(target):
                with ux_utils.print_exception_no_traceback():
                    raise ValueError(
                        'Storage mount destination path cannot be cloud storage'
                    )

            if storage_obj.mode in storage_lib.MOUNTABLE_STORAGE_MODES:
                # If any storage is using MOUNT mode, we need to enable FUSE in
                # the resources.
                for r in self.resources:
                    r.set_requires_fuse(True)
        # Storage source validation is done in Storage object
        self.storage_mounts = storage_mounts
        return self

    def update_storage_mounts(
            self, storage_mounts: Dict[str, storage_lib.Storage]) -> 'Task':
        """Updates the storage mounts for this task.

        Different from set_storage_mounts(), this function updates into the
        existing storage_mounts (calls ``dict.update()``), rather than
        overwriting it.

        This should be called before provisioning in order to take effect.

        Args:
          storage_mounts: an optional dict of ``{mount_path: sky.Storage
            object}``, where mount_path is the path inside the remote VM(s)
            where the Storage object will be mounted on.

        Returns:
          self: The current task, with storage mounts updated.

        Raises:
          ValueError: if input paths are invalid.
        """
        if not storage_mounts:
            return self
        task_storage_mounts = self.storage_mounts if self.storage_mounts else {}
        task_storage_mounts.update(storage_mounts)
        return self.set_storage_mounts(task_storage_mounts)

    def _get_preferred_store(
            self) -> Tuple[storage_lib.StoreType, Optional[str]]:
        """Returns the preferred store type and region for this task."""
        # TODO(zhwu, romilb): The optimizer should look at the source and
        #  destination to figure out the right stores to use. For now, we
        #  use a heuristic solution to find the store type by the following
        #  order:
        #  1. cloud/region decided in best_resources.
        #  2. cloud/region specified in the task resources.
        #  3. if not specified or the task's cloud does not support storage,
        #     use the first enabled storage cloud with default region.
        # This should be refactored and moved to the optimizer.

        # This check is not needed to support multiple accelerators;
        # We just need to get the storage_cloud.
        # assert len(self.resources) == 1, self.resources
        storage_cloud = None

        enabled_storage_cloud_names = (
            storage_lib.get_cached_enabled_storage_cloud_names_or_refresh(
                raise_if_no_cloud_access=True))

        if self.best_resources is not None:
            storage_cloud = self.best_resources.cloud
            storage_region = self.best_resources.region
        else:
            resources = list(self.resources)[0]
            storage_cloud = resources.cloud
            storage_region = resources.region

        if storage_cloud is not None:
            if str(storage_cloud) not in enabled_storage_cloud_names:
                storage_cloud = None

        storage_cloud_str = None
        if storage_cloud is None:
            storage_cloud_str = enabled_storage_cloud_names[0]
            assert storage_cloud_str is not None, enabled_storage_cloud_names[0]
            storage_region = None  # Use default region in the Store class
        else:
            storage_cloud_str = str(storage_cloud)

        store_type = storage_lib.StoreType.from_cloud(storage_cloud_str)
        return store_type, storage_region

    def sync_storage_mounts(self) -> None:
        """(INTERNAL) Eagerly syncs storage mounts to cloud storage.

        After syncing up, COPY-mode storage mounts are translated into regular
        file_mounts of the form ``{ /remote/path: {s3,gs,..}://<bucket path>
        }``.
        """
        # The same storage can be used multiple times, and we should construct
        # the storage with stores first, so that the storage will be created on
        # the correct cloud.
        name_to_storage = collections.defaultdict(list)
        for storage in self.storage_mounts.values():
            name_to_storage[storage.name].append(storage)
        for storages in name_to_storage.values():
            # Place the storage with most stores first, so that the storage will
            # be created on the correct cloud.
            storage_to_construct = sorted(storages,
                                          key=lambda x: len(x.stores),
                                          reverse=True)
            for storage in storage_to_construct:
                storage.construct()
                assert storage.name is not None, storage
                if not storage.stores:
                    store_type, store_region = self._get_preferred_store()
                    self.storage_plans[storage] = store_type
                    storage.add_store(store_type, store_region)
                else:
                    # We don't need to sync the storage here as if the stores
                    # are not empty, it measn the storage has been synced during
                    # construct() above.
                    # We will download the first store that is added to remote.
                    assert all(store is not None
                               for store in storage.stores.values()), storage
                    self.storage_plans[storage] = list(storage.stores.keys())[0]

        # The following logic converts the storage mounts with COPY mode into
        # inline file mounts with cloud URIs, so that the _execute_file_mounts()
        # in cloud_vm_ray_backend.py can correctly download from the specific
        # cloud storage on the remote cluster.
        # Note that this will cause duplicate destination paths in file_mounts,
        # and storage_mounts, which should be fine as our to_yaml_config() will
        # only dump the storage mount version, i.e. what user specified.
        storage_mounts = self.storage_mounts
        storage_plans = self.storage_plans
        for mnt_path, storage in storage_mounts.items():
            assert storage.name is not None, storage

            if storage.mode == storage_lib.StorageMode.COPY:
                store_type = storage_plans[storage]
                if store_type is storage_lib.StoreType.S3:
                    # TODO: allow for Storage mounting of different clouds
                    if isinstance(storage.source,
                                  str) and storage.source.startswith('s3://'):
                        blob_path = storage.source
                    else:
                        assert storage.name is not None, storage
                        blob_path = 's3://' + storage.name
                    blob_path = storage.get_bucket_sub_path_prefix(blob_path)
                    self.update_file_mounts({
                        mnt_path: blob_path,
                    })
                elif store_type is storage_lib.StoreType.GCS:
                    if isinstance(storage.source,
                                  str) and storage.source.startswith('gs://'):
                        blob_path = storage.source
                    else:
                        assert storage.name is not None, storage
                        blob_path = 'gs://' + storage.name
                    blob_path = storage.get_bucket_sub_path_prefix(blob_path)
                    self.update_file_mounts({
                        mnt_path: blob_path,
                    })
                elif store_type is storage_lib.StoreType.AZURE:
                    if (isinstance(storage.source, str) and
                            data_utils.is_az_container_endpoint(
                                storage.source)):
                        blob_path = storage.source
                    else:
                        assert storage.name is not None, storage
                        store_object = storage.stores[
                            storage_lib.StoreType.AZURE]
                        assert isinstance(store_object,
                                          storage_lib.AzureBlobStore)
                        storage_account_name = store_object.storage_account_name
                        blob_path = data_utils.AZURE_CONTAINER_URL.format(
                            storage_account_name=storage_account_name,
                            container_name=storage.name)
                    blob_path = storage.get_bucket_sub_path_prefix(blob_path)
                    self.update_file_mounts({
                        mnt_path: blob_path,
                    })
                elif store_type is storage_lib.StoreType.R2:
                    if storage.source is not None and not isinstance(
                            storage.source,
                            list) and storage.source.startswith('r2://'):
                        blob_path = storage.source
                    else:
                        blob_path = 'r2://' + storage.name
                    blob_path = storage.get_bucket_sub_path_prefix(blob_path)
                    self.update_file_mounts({
                        mnt_path: blob_path,
                    })
                elif store_type is storage_lib.StoreType.NEBIUS:
                    if storage.source is not None and not isinstance(
                            storage.source,
                            list) and storage.source.startswith('nebius://'):
                        blob_path = storage.source
                    else:
                        blob_path = 'nebius://' + storage.name
                    blob_path = storage.get_bucket_sub_path_prefix(blob_path)
                    self.update_file_mounts({
                        mnt_path: blob_path,
                    })
                elif store_type is storage_lib.StoreType.IBM:
                    if isinstance(storage.source,
                                  str) and storage.source.startswith('cos://'):
                        # source is a cos bucket's uri
                        blob_path = storage.source
                    else:
                        # source is a bucket name.
                        assert storage.name is not None, storage
                        # extract region from rclone.conf
                        cos_region = data_utils.Rclone.get_region_from_rclone(
                            storage.name, data_utils.Rclone.RcloneStores.IBM)
                        blob_path = f'cos://{cos_region}/{storage.name}'
                    blob_path = storage.get_bucket_sub_path_prefix(blob_path)
                    self.update_file_mounts({mnt_path: blob_path})
                elif store_type is storage_lib.StoreType.OCI:
                    if storage.source is not None and not isinstance(
                            storage.source,
                            list) and storage.source.startswith('oci://'):
                        blob_path = storage.source
                    else:
                        blob_path = 'oci://' + storage.name
                    self.update_file_mounts({
                        mnt_path: blob_path,
                    })
                else:
                    with ux_utils.print_exception_no_traceback():
                        raise ValueError(f'Storage Type {store_type} '
                                         'does not exist!')

                # TODO: Delete from storage_mounts, now that the storage is
                # translated into file_mounts. Note: as is, this will break
                # controller_utils.
                # _maybe_translate_local_file_mounts_and_sync_up(), which still
                # needs the storage, but not the file_mounts.

    def get_local_to_remote_file_mounts(self) -> Optional[Dict[str, str]]:
        """Returns file mounts of the form (dst=VM path, src=local path).

        Any cloud object store URIs (gs://, s3://, etc.), either as source or
        destination, are not included.

        INTERNAL: this method is internal-facing.
        """
        if self.file_mounts is None:
            return None
        d = {}
        for k, v in self.file_mounts.items():
            if not data_utils.is_cloud_store_url(
                    k) and not data_utils.is_cloud_store_url(v):
                d[k] = v
        return d

    def is_controller_task(self) -> bool:
        """Returns whether this task is a jobs/serve controller process."""
        return self.managed_job_dag is not None or self.service_name is not None

    def get_cloud_to_remote_file_mounts(self) -> Optional[Dict[str, str]]:
        """Returns file mounts of the form (dst=VM path, src=cloud URL).

        Local-to-remote file mounts are excluded (handled by
        get_local_to_remote_file_mounts()).

        INTERNAL: this method is internal-facing.
        """
        if self.file_mounts is None:
            return None
        d = {}
        for k, v in self.file_mounts.items():
            if not data_utils.is_cloud_store_url(
                    k) and data_utils.is_cloud_store_url(v):
                d[k] = v
        return d

    def to_yaml_config(self) -> Dict[str, Any]:
        """Returns a yaml-style dict representation of the task.

        INTERNAL: this method is internal-facing.
        """
        config = {}

        def add_if_not_none(key, value, no_empty: bool = False):
            if no_empty and not value:
                return
            if value is not None:
                config[key] = value

        add_if_not_none('name', self.name)

        tmp_resource_config: Union[Dict[str, Union[str, int]],
                                   Dict[str, List[Dict[str, Union[str, int]]]]]
        if len(self.resources) > 1:
            resource_list = []
            for r in self.resources:
                resource_list.append(r.to_yaml_config())
            key = 'ordered' if isinstance(self.resources, list) else 'any_of'
            tmp_resource_config = {key: resource_list}
        else:
            tmp_resource_config = list(self.resources)[0].to_yaml_config()

        add_if_not_none('resources', tmp_resource_config)

        if self.service is not None:
            add_if_not_none('service', self.service.to_yaml_config())

        if self.job_priority is not None:
            add_if_not_none('job', {'priority': self.job_priority})

        add_if_not_none('num_nodes', self.num_nodes)

        if self.inputs is not None:
            add_if_not_none('inputs',
                            {self.inputs: self.estimated_inputs_size_gigabytes})
        if self.outputs is not None:
            add_if_not_none(
                'outputs',
                {self.outputs: self.estimated_outputs_size_gigabytes})

        add_if_not_none('setup', self.setup)
        add_if_not_none('workdir', self.workdir)
        add_if_not_none('event_callback', self.event_callback)
        add_if_not_none('run', self.run)
        add_if_not_none('envs', self.envs, no_empty=True)

        add_if_not_none('file_mounts', {})

        if self.file_mounts is not None:
            config['file_mounts'].update(self.file_mounts)

        if self.storage_mounts is not None:
            config['file_mounts'].update({
                mount_path: storage.to_yaml_config()
                for mount_path, storage in self.storage_mounts.items()
            })

        add_if_not_none('file_mounts_mapping', self.file_mounts_mapping)
        return config

    def get_required_cloud_features(
            self) -> Set[clouds.CloudImplementationFeatures]:
        """Returns the required features for this task (but not for resources).

        Features required by the resources are checked separately in
        cloud.get_feasible_launchable_resources().

        INTERNAL: this method is internal-facing.
        """
        required_features = set()

        # Multi-node
        if self.num_nodes > 1:
            required_features.add(clouds.CloudImplementationFeatures.MULTI_NODE)

        # Storage mounting
        for _, storage_mount in self.storage_mounts.items():
            if storage_mount.mode in storage_lib.MOUNTABLE_STORAGE_MODES:
                required_features.add(
                    clouds.CloudImplementationFeatures.STORAGE_MOUNTING)
                break

        return required_features

    def __rshift__(self, b):
        sky.dag.get_current_dag().add_edge(self, b)

    def __repr__(self):
        if isinstance(self.run, str):
            run_msg = self.run.replace('\n', '\\n')
            if len(run_msg) > 20:
                run_msg = f'run=\'{run_msg[:20]}...\''
            else:
                run_msg = f'run=\'{run_msg}\''
        elif self.run is None:
            run_msg = 'run=<empty>'
        else:
            run_msg = 'run=<fn>'

        name_str = ''
        if self.name is not None:
            name_str = f'<name={self.name}>'
        s = f'Task{name_str}({run_msg})'
        if self.inputs is not None:
            s += f'\n  inputs: {self.inputs}'
        if self.outputs is not None:
            s += f'\n  outputs: {self.outputs}'
        if self.num_nodes > 1:
            s += f'\n  nodes: {self.num_nodes}'
        if len(self.resources) > 1:
            resources_str = ('{' + ', '.join(
                r.repr_with_region_zone for r in self.resources) + '}')
            s += f'\n  resources: {resources_str}'
        elif (len(self.resources) == 1 and
              not list(self.resources)[0].is_empty()):
            s += (f'\n  resources: '
                  f'{list(self.resources)[0].repr_with_region_zone}')
        else:
            s += '\n  resources: default instances'
        return s
