Merge pull request #4376 from adbrebs/fix_stack_check_nnet

theano/tensor/nnet/nnet.py

@@ -905,9 +905,11 @@ def softmax_simplifier(numerators, denominators):
                                 matching_denom = denominator
                                 break
         if matching_denom:
+            softmax = softmax_op(x)
+            copy_stack_trace(numerator, softmax)
             numerators.remove(numerator)
             denominators.remove(matching_denom)
-            numerators.append(softmax_op(x))
+            numerators.append(softmax)
 
     return numerators, denominators
 opt.local_mul_canonizer.add_simplifier(softmax_simplifier, 'softmax_simplifier')

theano/tensor/nnet/sigm.py

@@ -612,6 +612,7 @@ def local_exp_over_1_plus_exp(node):
             else:
                 # case: 1/(1+exp(x))
                 sigmoids.append(sigmoid(-t))
+            copy_stack_trace(node.outputs[0], sigmoids[-1])
 
         if not sigmoids:  # we didn't find any.  abort
             return
@@ -625,12 +626,17 @@ def local_exp_over_1_plus_exp(node):
         if num_neg ^ denom_neg:
             new_num = -new_num
 
+        copy_stack_trace(num, new_num)
+
         if len(denom_rest) == 0:
             return [new_num]
         elif len(denom_rest) == 1:
-            return [new_num / denom_rest[0]]
+            out = new_num / denom_rest[0]
         else:
-            return [new_num / tensor.mul(*denom_rest)]
+            out = new_num / tensor.mul(*denom_rest)
+
+        copy_stack_trace(node.outputs[0], out)
+        return [out]
 
 
 def parse_mul_tree(root):
@@ -923,6 +929,7 @@ def local_sigm_times_exp(node):
     exp(x) * sigm(-x) -> sigm(x)
     exp(-x) * sigm(x) -> sigm(-x)
 
+    todo: add stack traces to the intermediate variables
     """
     # Bail early if it is not a multiplication.
     if node.op != tensor.mul:

theano/tensor/nnet/tests/test_abstract_conv.py

@@ -7,6 +7,7 @@ from nose.tools import assert_raises
 
 import theano
 from theano import tensor
+from theano.gof.opt import check_stack_trace
 from theano.tests import unittest_tools as utt
 from theano.tensor.nnet import corr, abstract_conv as conv
 from theano.tensor.nnet.abstract_conv import get_conv_output_shape
@@ -98,7 +99,7 @@ class BaseTestConv2d(unittest.TestCase):
     def run_fwd(self, inputs_shape, filters_shape, ref=conv_corr,
                 subsample=(1, 1), verify_grad=True, mode=None,
                 border_mode='valid', filter_flip=True, provide_shape=False,
-                target_op=None):
+                target_op=None, check_trace=False):
         inputs_val = numpy.random.random(inputs_shape).astype('float32')
         filters_val = numpy.random.random(filters_shape).astype('float32')
 
@@ -133,8 +134,9 @@ class BaseTestConv2d(unittest.TestCase):
         if target_op is not None:
             assert any([isinstance(n.op, target_op) for n
                         in f.maker.fgraph.toposort()])
+            if check_trace:
+                self.assertTrue(check_stack_trace(f, ops_to_check=target_op))
 
-        self.assertTrue(hasattr(f.maker.fgraph.outputs[0].tag, 'trace'))
         res_ref = numpy.array(f_ref())
         res = numpy.array(f())
         utt.assert_allclose(res_ref, res)
@@ -148,7 +150,7 @@ class BaseTestConv2d(unittest.TestCase):
     def run_gradweight(self, inputs_shape, filters_shape, output_shape,
                        ref=conv_corr_gw, subsample=(1, 1), filter_flip=True,
                        verify_grad=True, mode=None, border_mode='valid',
-                       provide_shape=False, target_op=None):
+                       provide_shape=False, target_op=None, check_trace=False):
 
         inputs_val = numpy.random.random(inputs_shape).astype('float32')
         output_val = numpy.random.random(output_shape).astype('float32')
@@ -177,12 +179,13 @@ class BaseTestConv2d(unittest.TestCase):
                     subsample=subsample,
                     conv_mode=conv_mode)
         f = theano.function([], c, mode=mode)
-        self.assertTrue(hasattr(f.maker.fgraph.outputs[0].tag, 'trace'))
         f_ref = theano.function([], c_ref, mode='FAST_RUN')
 
         if target_op is not None:
             assert any([isinstance(n.op, target_op) for n
                         in f.maker.fgraph.toposort()])
+            if check_trace:
+                self.assertTrue(check_stack_trace(f, ops_to_check=target_op))
 
         res_ref = numpy.array(f_ref())
         res = numpy.array(f())
@@ -201,7 +204,7 @@ class BaseTestConv2d(unittest.TestCase):
     def run_gradinput(self, inputs_shape, filters_shape, output_shape,
                       ref=conv_corr_gi, subsample=(1, 1), filter_flip=True,
                       verify_grad=True, mode=None, border_mode='valid',
-                      provide_shape=False, target_op=None):
+                      provide_shape=False, target_op=None, check_trace=False):
 
         output_val = numpy.random.random(output_shape).astype('float32')
         filters_val = numpy.random.random(filters_shape).astype('float32')
@@ -227,12 +230,13 @@ class BaseTestConv2d(unittest.TestCase):
                     border_mode=border_mode, subsample=subsample,
                     conv_mode=conv_mode)
         f = theano.function([], c, mode=mode)
-        self.assertTrue(hasattr(f.maker.fgraph.outputs[0].tag, 'trace'))
         f_ref = theano.function([], c_ref, mode='FAST_RUN')
 
         if target_op is not None:
             assert any([isinstance(n.op, target_op) for n
                         in f.maker.fgraph.toposort()])
+            if check_trace:
+                self.assertTrue(check_stack_trace(f, ops_to_check=target_op))
 
         res_ref = numpy.array(f_ref())
         res = numpy.array(f())
@@ -291,15 +295,18 @@ class TestCorrConv2d(BaseTestConv2d):
             raise SkipTest("Need blas to test conv2d")
         self.run_fwd(inputs_shape=i, filters_shape=f, subsample=s,
                      verify_grad=True, provide_shape=provide_shape,
-                     border_mode=b, filter_flip=flip, target_op=CorrMM)
+                     border_mode=b, filter_flip=flip, target_op=CorrMM,
+                     check_trace=True)
         self.run_gradweight(inputs_shape=i, filters_shape=f,
                             output_shape=o, subsample=s, verify_grad=True,
                             provide_shape=provide_shape, border_mode=b,
-                            filter_flip=flip, target_op=CorrMM_gradWeights)
+                            filter_flip=flip, target_op=CorrMM_gradWeights,
+                            check_trace=True)
         self.run_gradinput(inputs_shape=i, filters_shape=f,
                            output_shape=o, subsample=s, verify_grad=True,
                            provide_shape=provide_shape, border_mode=b,
-                           filter_flip=flip, target_op=CorrMM_gradInputs)
+                           filter_flip=flip, target_op=CorrMM_gradInputs,
+                           check_trace=True)
 
 
 class TestCpuConv2d(BaseTestConv2d):
@@ -343,7 +350,8 @@ class TestCpuConv2d(BaseTestConv2d):
             self.run_fwd(inputs_shape=i, filters_shape=f, subsample=s,
                          verify_grad=(gradweight_OK and gradinput_OK),
                          mode=mode, provide_shape=provide_shape,
-                         border_mode=b, filter_flip=flip, target_op=ConvOp)
+                         border_mode=b, filter_flip=flip, target_op=ConvOp,
+                         check_trace=True)
         else:
             self.assertRaises(AssertionError,
                               self.run_fwd,
@@ -354,7 +362,8 @@ class TestCpuConv2d(BaseTestConv2d):
                               mode=mode,
                               provide_shape=provide_shape,
                               border_mode=b,
-                              filter_flip=flip)
+                              filter_flip=flip,
+                              check_trace=True)
 
         if gradweight_OK:
             if not theano.config.blas.ldflags:
@@ -364,7 +373,8 @@ class TestCpuConv2d(BaseTestConv2d):
                                 verify_grad=False, mode=mode,
                                 provide_shape=provide_shape, border_mode=b,
                                 filter_flip=flip,
-                                target_op=(ConvOp, ConvGrad3D))
+                                target_op=(ConvOp, ConvGrad3D),
+                                check_trace=True)
         else:
             self.assertRaises(AssertionError,
                               self.run_gradweight,
@@ -376,7 +386,8 @@ class TestCpuConv2d(BaseTestConv2d):
                               mode=mode,
                               provide_shape=provide_shape,
                               border_mode=b,
-                              filter_flip=flip)
+                              filter_flip=flip,
+                              check_trace=True)
 
         if gradinput_OK:
             if not theano.config.blas.ldflags:
@@ -386,7 +397,8 @@ class TestCpuConv2d(BaseTestConv2d):
                                verify_grad=False, mode=mode,
                                provide_shape=provide_shape, border_mode=b,
                                filter_flip=flip,
-                               target_op=(ConvOp, ConvTransp3D))
+                               target_op=(ConvOp, ConvTransp3D),
+                               check_trace=True)
         else:
             self.assertRaises(AssertionError,
                               self.run_gradinput,
@@ -398,7 +410,8 @@ class TestCpuConv2d(BaseTestConv2d):
                               mode=mode,
                               provide_shape=provide_shape,
                               border_mode=b,
-                              filter_flip=flip)
+                              filter_flip=flip,
+                              check_trace=True)
 
 
 def test_constant_shapes():

theano/tensor/nnet/tests/test_conv3d2d.py

@@ -10,6 +10,7 @@ except ImportError:
 from six.moves import xrange
 
 import theano
+from theano.gof.opt import check_stack_trace
 from theano.tensor.nnet.conv3d2d import *
 import theano.tests.unittest_tools as utt
 
@@ -73,10 +74,11 @@ def pyconv3d(signals, filters):
                 r_i += o_i[Tf2:o_i_sh0-Tf2, Hf2:-Hf2, Wf2:-Wf2]
     return rval
 
+
 def check_diagonal_subtensor_view_traces(fn):
-    for apply_node in fn.maker.fgraph.apply_nodes:
-        if isinstance(apply_node.op, (DiagonalSubtensor, IncDiagonalSubtensor)):
-            assert hasattr(apply_node.outputs[0].tag, 'trace')
+    assert check_stack_trace(
+        fn, ops_to_check=(DiagonalSubtensor, IncDiagonalSubtensor))
+
 
 def test_conv3d(mode=mode_without_gpu, shared=theano.tensor._shared):
     if ndimage is None:
@@ -150,7 +152,6 @@ def test_conv3d(mode=mode_without_gpu, shared=theano.tensor._shared):
     newconv3d = theano.function([], [],
                                 updates={s_output: out},
                                 mode=mode)
-    check_diagonal_subtensor_view_traces(newconv3d)
 
     t0 = time.time()
     newconv3d()
@@ -162,7 +163,6 @@ def test_conv3d(mode=mode_without_gpu, shared=theano.tensor._shared):
                                           (s_signals, gsignals)],
                                  mode=mode,
                                  name='grad')
-    check_diagonal_subtensor_view_traces(gnewconv3d)
 
     t0 = time.time()
     gnewconv3d()

theano/tensor/nnet/tests/test_opt.py

 from __future__ import absolute_import, print_function, division
 import theano
 from theano import tensor
-from theano.tensor.nnet.blocksparse import sparse_block_dot
+from theano.gof.opt import check_stack_trace
+from theano.tensor.nnet.blocksparse import (
+    sparse_block_dot, sparse_block_gemv_inplace, sparse_block_outer_inplace,
+    sparse_block_gemv, sparse_block_outer)
 
 
 def test_blocksparse_inplace_gemv_opt():
@@ -14,12 +17,13 @@ def test_blocksparse_inplace_gemv_opt():
     o = sparse_block_dot(W, h, iIdx, b, oIdx)
 
     f = theano.function([W, h, iIdx, b, oIdx], o)
-    assert hasattr(f.maker.fgraph.outputs[0].tag, 'trace')
 
     if theano.config.mode == "FAST_COMPILE":
         assert not f.maker.fgraph.toposort()[-1].op.inplace
+        assert check_stack_trace(f, ops_to_check=[sparse_block_gemv])
     else:
         assert f.maker.fgraph.toposort()[-1].op.inplace
+        assert check_stack_trace(f, ops_to_check=[sparse_block_gemv_inplace])
 
 
 def test_blocksparse_inplace_outer_opt():
@@ -31,13 +35,12 @@ def test_blocksparse_inplace_outer_opt():
 
     o = sparse_block_dot(W, h, iIdx, b, oIdx)
 
-    theano.printing.debugprint(tensor.grad(o.sum(), wrt=W))
-
     f = theano.function([W, h, iIdx, b, oIdx],
                         [o, tensor.grad(o.sum(), wrt=W)])
-    assert hasattr(f.maker.fgraph.outputs[0].tag, 'trace')
 
     if theano.config.mode == "FAST_COMPILE":
         assert not f.maker.fgraph.toposort()[-1].op.inplace
+        assert check_stack_trace(f, ops_to_check=sparse_block_outer)
     else:
         assert f.maker.fgraph.toposort()[-1].op.inplace
+        assert check_stack_trace(f, ops_to_check=sparse_block_outer_inplace)