foscat.backend
==============

.. py:module:: foscat.backend


Classes
-------

.. autoapisummary::

   foscat.backend.foscat_backend


Module Contents
---------------

.. py:class:: foscat_backend(name, mpi_rank=0, all_type='float64', gpupos=0, silent=False)

   .. py:attribute:: TENSORFLOW
      :value: 1



   .. py:attribute:: TORCH
      :value: 2



   .. py:attribute:: NUMPY
      :value: 3



   .. py:attribute:: BACKEND


   .. py:attribute:: float64


   .. py:attribute:: float32


   .. py:attribute:: int64


   .. py:attribute:: int32


   .. py:attribute:: complex64


   .. py:attribute:: complex128


   .. py:attribute:: gpulist


   .. py:attribute:: ngpu
      :value: 1



   .. py:method:: tf_loc_function(func)


   .. py:method:: calc_iso_orient(norient)


   .. py:method:: calc_fft_orient(norient, nharm, imaginary)


   .. py:method:: bk_SparseTensor(indice, w, dense_shape=[])


   .. py:method:: bk_stack(list, axis=0)


   .. py:method:: bk_sparse_dense_matmul(smat, mat)


   .. py:method:: periodic_pad(x, pad_height, pad_width)

      Applies periodic ('wrap') padding to a 4D TensorFlow tensor (N, H, W, C).

      Args:
      x (tf.Tensor): Input tensor with shape (batch_size, height, width, channels).
          pad_height (tuple): Tuple (top, bottom) defining the vertical padding size.
          pad_width (tuple): Tuple (left, right) defining the horizontal padding size.

      Returns:
          tf.Tensor: Tensor with periodic padding applied.



   .. py:method:: conv2d(x, w, strides=[1, 1, 1, 1], padding='SAME')


   .. py:method:: conv1d(x, w, strides=[1, 1, 1], padding='SAME')


   .. py:method:: bk_threshold(x, threshold, greater=True)


   .. py:method:: bk_maximum(x1, x2)


   .. py:method:: bk_device(device_name)


   .. py:method:: bk_ones(shape, dtype=None)


   .. py:method:: bk_conv1d(x, w)


   .. py:method:: bk_flattenR(x)


   .. py:method:: bk_flatten(x)


   .. py:method:: bk_resize_image(x, shape)


   .. py:method:: bk_L1(x)


   .. py:method:: bk_square_comp(x)


   .. py:method:: bk_reduce_sum(data, axis=None)


   .. py:method:: bk_size(data)


   .. py:method:: iso_mean(x, use_2D=False)


   .. py:method:: fft_ang(x, nharm=1, imaginary=False, use_2D=False)


   .. py:method:: constant(data)


   .. py:method:: bk_reduce_mean(data, axis=None)


   .. py:method:: bk_reduce_min(data, axis=None)


   .. py:method:: bk_random_seed(value)


   .. py:method:: bk_random_uniform(shape)


   .. py:method:: bk_reduce_std(data, axis=None)


   .. py:method:: bk_sqrt(data)


   .. py:method:: bk_abs(data)


   .. py:method:: bk_is_complex(data)


   .. py:method:: bk_distcomp(data)


   .. py:method:: bk_norm(data)


   .. py:method:: bk_square(data)


   .. py:method:: bk_log(data)


   .. py:method:: bk_matmul(a, b)


   .. py:method:: bk_tensor(data)


   .. py:method:: bk_shape_tensor(shape)


   .. py:method:: bk_complex(real, imag)


   .. py:method:: bk_exp(data)


   .. py:method:: bk_min(data)


   .. py:method:: bk_argmin(data)


   .. py:method:: bk_tanh(data)


   .. py:method:: bk_max(data)


   .. py:method:: bk_argmax(data)


   .. py:method:: bk_reshape(data, shape)


   .. py:method:: bk_repeat(data, nn, axis=0)


   .. py:method:: bk_tile(data, nn, axis=0)


   .. py:method:: bk_roll(data, nn, axis=0)


   .. py:method:: bk_expand_dims(data, axis=0)


   .. py:method:: bk_transpose(data, thelist)


   .. py:method:: bk_concat(data, axis=None)


   .. py:method:: bk_zeros(shape, dtype=None)


   .. py:method:: bk_gather(data, idx)


   .. py:method:: bk_reverse(data, axis=0)


   .. py:method:: bk_fft(data)


   .. py:method:: bk_fftn(data, dim=None)


   .. py:method:: bk_ifftn(data, dim=None, norm=None)


   .. py:method:: bk_rfft(data)


   .. py:method:: bk_irfft(data)


   .. py:method:: bk_conjugate(data)


   .. py:method:: bk_real(data)


   .. py:method:: bk_imag(data)


   .. py:method:: bk_relu(x)


   .. py:method:: bk_clip_by_value(x, xmin, xmax)


   .. py:method:: bk_cast(x)


   .. py:method:: bk_variable(x)


   .. py:method:: bk_assign(x, y)


   .. py:method:: bk_constant(x)


   .. py:method:: to_numpy(x)