pymllm.ffi
==========

.. py:module:: pymllm.ffi


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/pymllm/ffi/base/index


Attributes
----------

.. autoapisummary::

   pymllm.ffi.MLLM_FIND_TORCH_AVAILABLE
   pymllm.ffi.MLLM_FIND_NUMPY_AVAILABLE
   pymllm.ffi.float32
   pymllm.ffi.float16
   pymllm.ffi.bfloat16
   pymllm.ffi.cpu
   pymllm.ffi.cuda
   pymllm.ffi.qnn


Classes
-------

.. autoapisummary::

   pymllm.ffi.Device
   pymllm.ffi.DType
   pymllm.ffi.Tensor
   pymllm.ffi.Session


Functions
---------

.. autoapisummary::

   pymllm.ffi.echo
   pymllm.ffi.initialize_context
   pymllm.ffi.shutdown_context
   pymllm.ffi.float32_
   pymllm.ffi.float16_
   pymllm.ffi.bfloat16_
   pymllm.ffi.cpu_
   pymllm.ffi.cuda_
   pymllm.ffi.qnn_
   pymllm.ffi.device
   pymllm.ffi.empty
   pymllm.ffi.zeros
   pymllm.ffi.ones
   pymllm.ffi.arange
   pymllm.ffi.random
   pymllm.ffi.is_torch_available
   pymllm.ffi.is_numpy_available
   pymllm.ffi.from_torch
   pymllm.ffi.from_numpy


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

.. py:data:: MLLM_FIND_TORCH_AVAILABLE

.. py:data:: MLLM_FIND_NUMPY_AVAILABLE

.. py:function:: echo(rec)

.. py:function:: initialize_context()

.. py:function:: shutdown_context()

.. py:class:: Device

   Bases: :py:obj:`tvm_ffi.Object`


   .. py:method:: to_pod()


.. py:class:: DType

   Bases: :py:obj:`tvm_ffi.Object`


   .. py:method:: to_pod()


.. py:function:: float32_()

.. py:function:: float16_()

.. py:function:: bfloat16_()

.. py:function:: cpu_()

.. py:function:: cuda_()

.. py:function:: qnn_()

.. py:class:: Tensor

   Bases: :py:obj:`tvm_ffi.Object`


   .. py:method:: __str__()


   .. py:property:: shape
      :type: tvm_ffi.Shape



   .. py:property:: dtype
      :type: DType



   .. py:property:: device
      :type: Device



   .. py:method:: tobytes()


   .. py:method:: __add__(other)


   .. py:method:: __sub__(other)


   .. py:method:: __mul__(other)


   .. py:method:: __div__(other)


   .. py:method:: __neg__(other)


   .. py:method:: abs()


   .. py:method:: clip(min_val, max_val)


   .. py:method:: min(dim = -1, keep_dim = False)


   .. py:method:: max(dim = -1, keep_dim = False)


   .. py:method:: sum(dim = -1, keep_dim = False)


   .. py:method:: mean(dim = -1, keep_dim = False)


   .. py:method:: transpose(dim0, dim1)


   .. py:property:: T
      :type: Tensor



   .. py:method:: view(shape)


   .. py:method:: unsqueeze(dim)


   .. py:method:: squeeze(dim)


   .. py:method:: permute(dims)


   .. py:method:: contiguous()


   .. py:method:: clone()


   .. py:method:: repeat(multiplier, dim)


   .. py:method:: to(dd)


   .. py:method:: cpu()


   .. py:method:: cuda()


   .. py:property:: name


   .. py:method:: set_name(name)


   .. py:method:: numel()


   .. py:property:: rank


   .. py:method:: is_contiguous()


.. py:data:: float32
   :type:  DType

.. py:data:: float16
   :type:  DType

.. py:data:: bfloat16
   :type:  DType

.. py:data:: cpu
   :type:  Device

.. py:data:: cuda
   :type:  Device

.. py:data:: qnn
   :type:  Device

.. py:function:: device(device_type)

.. py:function:: empty(shape, dtype = float32, device_type = cpu)

.. py:function:: zeros(shape, dtype = float32, device_type = cpu)

.. py:function:: ones(shape, dtype = float32, device_type = cpu)

.. py:function:: arange(start, end, step = 1, dtype = float32, device_type = cpu)

.. py:function:: random(shape, start = -1.0, end = 1.0, dtype = float32, device_type = cpu)

.. py:function:: is_torch_available()

.. py:function:: is_numpy_available()

.. py:function:: from_torch(torch_tensor)

.. py:function:: from_numpy(numpy_tensor)

.. py:class:: Session

   Bases: :py:obj:`tvm_ffi.Object`