dacapo.compute_context
======================

.. py:module:: dacapo.compute_context


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/dacapo/compute_context/bsub/index
   /autoapi/dacapo/compute_context/compute_context/index
   /autoapi/dacapo/compute_context/local_torch/index


Classes
-------

.. autoapisummary::

   dacapo.compute_context.ComputeContext
   dacapo.compute_context.LocalTorch
   dacapo.compute_context.Bsub


Functions
---------

.. autoapisummary::

   dacapo.compute_context.create_compute_context


Package Contents
----------------

.. py:class:: ComputeContext



   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: distribute_workers
      :type:  Optional[bool]

      The ComputeContext class is an abstract base class for defining the context in which computations are to be done.
      It is inherited from the built-in class `ABC` (Abstract Base Classes). Other classes can inherit this class to define
      their own specific variations of the context. It requires to implement several property methods, and also includes
      additional methods related to the context design.

      .. attribute:: device

         The device on which computations are to be done.

      .. method:: _wrap_command(command)

         Wraps a command in the context specific command.

      .. method:: wrap_command(command)

         Wraps a command in the context specific command and returns it.

      .. method:: execute(command)

         Runs a command in the context specific way.

      .. note:: The class is abstract and requires to implement the abstract methods.


   .. py:property:: device
      :abstractmethod:

      Abstract property method to define the device on which computations are to be done.

      A device can be a CPU, GPU, TPU, etc. It is used to specify the context in which computations are to be done.

      :returns: The device on which computations are to be done.
      :rtype: str

      :raises NotImplementedError: If the method is not implemented in the derived class.

      .. rubric:: Examples

      >>> context = ComputeContext()
      >>> device = context.device

      .. note:: The method should be implemented in the derived class.


   .. py:method:: wrap_command(command)

      A method to wrap a command in the context specific command and return it.

      :param command: The command to be wrapped.
      :type command: List[str]

      :returns: The wrapped command.
      :rtype: List[str]

      :raises NotImplementedError: If the method is not implemented in the derived class.

      .. rubric:: Examples

      >>> context = ComputeContext()
      >>> command = ["python", "script.py"]
      >>> wrapped_command = context.wrap_command(command)

      .. note:: The method should be implemented in the derived class.



   .. py:method:: execute(command)

      A method to run a command in the context specific way.

      :param command: The command to be executed.
      :type command: List[str]

      :raises NotImplementedError: If the method is not implemented in the derived class.

      .. rubric:: Examples

      >>> context = ComputeContext()
      >>> command = ["python", "script.py"]
      >>> context.execute(command)

      .. note:: The method should be implemented in the derived class.



.. py:function:: create_compute_context() -> ComputeContext

   Create a compute context based on the global DaCapo options.

   :returns: The compute context object.
   :rtype: ComputeContext

   :raises ValueError: If the store type is unknown.

   .. rubric:: Examples

   >>> context = create_compute_context()

   .. note:: The method is implemented in the module.


.. py:class:: LocalTorch



   The LocalTorch class is a subclass of the ComputeContext class.
   It is used to specify the context in which computations are to be done.
   LocalTorch is used to specify that computations are to be done on the local machine using PyTorch.

   .. attribute:: _device

      This stores the type of device on which torch computations are to be done. It can

      :type: Optional[str]

   .. attribute:: take "cuda" for GPU or "cpu" for CPU. None value results in automatic detection of device type.

      

   .. attribute:: oom_limit

      The out of GPU memory to leave free in GB. If the free memory is below

      :type: Optional[float | int]

   .. attribute:: this limit, we will fall back on CPU.

      

   .. method:: device()

      Returns the torch device object.

   .. note:: The class is a subclass of the ComputeContext class.


   .. py:attribute:: distribute_workers
      :type:  Optional[bool]

      The ComputeContext class is an abstract base class for defining the context in which computations are to be done.
      It is inherited from the built-in class `ABC` (Abstract Base Classes). Other classes can inherit this class to define
      their own specific variations of the context. It requires to implement several property methods, and also includes
      additional methods related to the context design.

      .. attribute:: device

         The device on which computations are to be done.

      .. method:: _wrap_command(command)

         Wraps a command in the context specific command.

      .. method:: wrap_command(command)

         Wraps a command in the context specific command and returns it.

      .. method:: execute(command)

         Runs a command in the context specific way.

      .. note:: The class is abstract and requires to implement the abstract methods.


   .. py:attribute:: oom_limit
      :type:  Optional[float | int]


   .. py:property:: device
      A property method that returns the torch device object. It automatically detects and uses "cuda" (GPU) if
      available, else it falls back on using "cpu".

      :returns: The torch device object.
      :rtype: torch.device


.. py:class:: Bsub



   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: distribute_workers
      :type:  Optional[bool]

      The Bsub class is a subclass of the ComputeContext class. It is used to specify the
      context in which computations are to be done. Bsub is used to specify that
      computations are to be done on a cluster using LSF.

      .. attribute:: queue

         The queue to run on.

         :type: str

      .. attribute:: num_gpus

         The number of gpus to train on. Currently only 1 gpu can be used.

         :type: int

      .. attribute:: num_cpus

         The number of cpus to use to generate training data.

         :type: int

      .. attribute:: billing

         Project name that will be paying for this Job.

         :type: Optional[str]

      .. method:: device()

         Returns the device on which computations are to be done.

      .. method:: _wrap_command(command)

         Wraps a command in the context specific command.

      .. note:: The class is a subclass of the ComputeContext class.


   .. py:attribute:: queue
      :type:  str


   .. py:attribute:: num_gpus
      :type:  int


   .. py:attribute:: num_cpus
      :type:  int


   .. py:attribute:: billing
      :type:  Optional[str]


   .. py:property:: device
      A property method that returns the device on which computations are to be done.

      A device can be a CPU, GPU, TPU, etc. It is used to specify the context in which computations are to be done.

      :returns: The device on which computations are to be done.
      :rtype: str

      .. rubric:: Examples

      >>> context = Bsub()
      >>> device = context.device