diff --git a/README.rst b/README.rst index 022b88ecfcd85e87f4e156df870bac8fa890d719..87a99e65e1b7814ab54da938780e746db6574ee6 100644 --- a/README.rst +++ b/README.rst @@ -92,18 +92,13 @@ You can also use the class `AutoDiffOp` to obtain both the assignments (if you a op = AutoDiffOp(forward_assignments) backward_assignments = op.backward_assignments - x_tensor = pystencils.autodiff.tf_variable_from_field(x) - y_tensor = pystencils.autodiff.tf_variable_from_field(y) - tensorflow_op = op.create_tensorflow_op({x: x_tensor, y: y_tensor}, backend='tensorflow') + tensorflow_op = op.create_tensorflow_op(backend='tensorflow_native') ... or Torch: .. code-block:: python - x_tensor = pystencils.autodiff.torch_tensor_from_field(x, cuda=False, requires_grad=True) - y_tensor = pystencils.autodiff.torch_tensor_from_field(y, cuda=False, requires_grad=True) - - z_tensor = op.create_tensorflow_op({x: x_tensor, y: y_tensor}, backend='torch') + torch_op = op.create_tensorflow_op({x: x_tensor, y: y_tensor}, backend='torch_native') Test Report and Coverage ------------------------ diff --git a/docs/index.rst b/docs/index.rst index c6a56eca09e853744a0856525ee77d67880d9b16..946234cd4d0d55f896d9eb8792adf1dfca0b5e91 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -84,18 +84,20 @@ You can also use the class :class:`pystencils_autodiff.AutoDiffOp` to obtain bot op = AutoDiffOp(forward_assignments) backward_assignments = op.backward_assignments - x_tensor = pystencils.autodiff.tf_variable_from_field(x) - y_tensor = pystencils.autodiff.tf_variable_from_field(y) - tensorflow_op = op.create_tensorflow_op({x: x_tensor, y: y_tensor}, backend='tensorflow') + tensorflow_op = op.create_tensorflow_op(backend='tensorflow_native') + +.. testoutput:: + :hide: + :options: -ELLIPSIS, +NORMALIZE_WHITESPACE + + Compiling Tensorflow module... + Linking Tensorflow module... ... or Torch: .. testcode:: - x_tensor = pystencils.autodiff.torch_tensor_from_field(x, cuda=False, requires_grad=True) - y_tensor = pystencils.autodiff.torch_tensor_from_field(y, cuda=False, requires_grad=True) - - z_tensor = op.create_tensorflow_op({x: x_tensor, y: y_tensor}, backend='torch') + torch_op = op.create_tensorflow_op(backend='torch_native') Contents