diff --git a/docs/conf.py b/docs/conf.py index 5dab84480a28d0cb1121e2c316c4763ebfd1fcf6..62d561e6949ea83f04e0311dd44a769e19962ebb 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -8,11 +8,16 @@ # All configuration values have a default; values that are commented out # serve to show the default. -import os -import sys import inspect +import os import shutil +import sys +doctest_global_setup = ''' +import pystencils +import numpy as np +import sympy +''' __location__ = os.path.join(os.getcwd(), os.path.dirname( inspect.getfile(inspect.currentframe()))) @@ -222,21 +227,21 @@ htmlhelp_basename = 'pystencils_autodiff-doc' # -- Options for LaTeX output -------------------------------------------------- latex_elements = { -# The paper size ('letterpaper' or 'a4paper'). -# 'papersize': 'letterpaper', + # The paper size ('letterpaper' or 'a4paper'). + # 'papersize': 'letterpaper', -# The font size ('10pt', '11pt' or '12pt'). -# 'pointsize': '10pt', + # The font size ('10pt', '11pt' or '12pt'). + # 'pointsize': '10pt', -# Additional stuff for the LaTeX preamble. -# 'preamble': '', + # Additional stuff for the LaTeX preamble. + # 'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass [howto/manual]). latex_documents = [ - ('index', 'user_guide.tex', u'pystencils_autodiff Documentation', - u'Stephan Seitz', 'manual'), + ('index', 'user_guide.tex', u'pystencils_autodiff Documentation', + u'Stephan Seitz', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of diff --git a/tests/test_tfmad.py b/tests/test_tfmad.py index 54daabae6c9447b9163d56e1f251db5a5086c736..309ec94cf5ac920e48dfc7b8cb09a6a65ee6c08a 100644 --- a/tests/test_tfmad.py +++ b/tests/test_tfmad.py @@ -179,12 +179,10 @@ def test_tfmad_gradient_check_torch(): print('Forward output fields (to check order)') print(auto_diff.forward_input_fields) - a_tensor = torch.zeros( - *a.shape, dtype=torch.float64, requires_grad=True) - b_tensor = torch.zeros( - *b.shape, dtype=torch.float64, requires_grad=True) - function = auto_diff.create_tensorflow_op( - {a: a_tensor, b: b_tensor}, backend='torch') + a_tensor = torch.zeros(*a.shape, dtype=torch.float64, requires_grad=True) + b_tensor = torch.zeros(*b.shape, dtype=torch.float64, requires_grad=True) + + function = auto_diff.create_tensorflow_op({a: a_tensor, b: b_tensor}, backend='torch') torch.autograd.gradcheck(function.apply, [a_tensor, b_tensor])