The rest of the library has comments with exactly this same format and this isn't even flagged by the pep8 script. I think you're holding me to an unfair standard and wasting my time on something that's just your aesthetic opinion.

theano/tensor/opt.py:    #always a good idea to replace an alloc with multiple op.
theano/tensor/opt.py:    unary(x)[idx] -> unary(x[idx])#any broadcast pattern.
theano/tensor/opt.py:#after priority 50 Destructive inplace operations
theano/tensor/opt.py:    #aaron value
theano/tensor/blas.py:            #at the very least, move the alpha inside the gemm_no_inplace
theano/tensor/deprecated/rmodule.py:            #and seeds each subcomponent that is an RModule
theano/tensor/nnet/nnet.py:            #add the bias vector to the i'th row of x
theano/tensor/nnet/conv.py:    #accept Constant value for image_shape and filter_shape.
theano/tensor/basic.py:        #and have the fct infer_shape() implemented in the op that convert
theano/tensor/basic.py:#alias to sqr, included to maintain similarity with numpy interface
theano/tensor/basic.py:        #a == [0,1,2]
theano/tensor/basic.py:# docs.scipy.org/doc/numpy/reference/arrays.indexing.html#advanced-indexing
theano/scalar/basic_scipy.py:#as scipy is not always available, we put threat them separatly
theano/sandbox/test_theano_object.py:        self.c = 100 #a constant
theano/sandbox/cuda/basic_ops.py:        #alloc an output
theano/sandbox/cuda/tests/test_conv_cuda_ndarray.py:            , ((60,20,28,28), (10,20,5,5), (1, 1), (2,2), (1, 1))#added a test case that fail from test_nnet.py.test_conv_nnet2
theano/sandbox/cuda/tests/test_basic_ops.py:                #and this cause small rounding difference with some seed
theano/sandbox/cuda/tests/test_basic_ops.py:                    #assert that the test was done on the gpu.
theano/sandbox/cuda/tests/test_basic_ops.py:                    #assert that the test was done on the gpu.
theano/sandbox/cuda/tests/test_memory.py:        #assert mem2 == freemem(), (mem2, freemem())
theano/sandbox/cuda/tests/test_bench_loopfusion.py:        rval.input = input #add the input to the returned object
theano/sandbox/cuda/tests/test_cuda_ndarray.py:        #a[0, :, :] = mat
theano/sandbox/cuda/tests/test_cuda_ndarray.py:        #assert numpy.allclose(numpy.asarray(_a), a)
theano/sandbox/cuda/type.py:        #a sparce matrix, numpy.may_share_memory fail.
theano/sandbox/cuda/opt.py:                #as we currently only support float32, this can fail.
theano/sandbox/test_neighbours.py:            #assert numpy.allclose(images.get_value(borrow=True), g())
theano/sandbox/test_neighbours.py:            #assert numpy.allclose(images.get_value(borrow=True), g())
theano/sandbox/rng_mrg.py:    #and the second half by B with a modulo of m2
theano/sandbox/test_rng_mrg.py:            #avg_std = numpy.std(ival)
theano/sandbox/test_rng_mrg.py:            #avg_std = alpha * numpy.std(ival) + (1-alpha)*avg_std
theano/sandbox/symbolic_module.py:    #at this point there is a neural_net module all built and compiled,
theano/sandbox/symbolic_module.py:    #at this point there is a neural_net module all built and compiled,
theano/sandbox/symbolic_module.py:    #nnet_on_pca.include(PCA) #an already-instantiated Module
theano/scan_module/tests/test_scan.py:        ##assert numpy.allclose( theano_x0 , vu2)
theano/scan_module/tests/test_scan.py:        #assert not numpy.allclose( theano_x0 , vu2[1:4])
theano/scan_module/tests/test_scan.py:        #assert numpy.allclose( theano_x1 , vu1[0:3])
theano/scan_module/scan_op.py:        #assert len(inputs) >= len(self.inputs)
theano/scan_module/scan_op.py:                       #args[-len(other_args):]    )
theano/misc/check_blas.py:#a,b scalar
theano/misc/#check_blas.py#:#a,b scalar
theano/sparse/sandbox/test_sp.py:                        #abspos = 0
theano/sparse/sandbox/test_sp.py:                                    #abspos+=1
theano/sparse/sandbox/test_sp.py:                    #assert numpy.all(visref==visval)
theano/sparse/basic.py:        #are.
theano/sparse/basic.py:        #any gradient anywhere. but we know that at least one of
theano/gof/destroyhandler.py:                #add_impact(input_root, self.view_o, input_impact)
theano/gof/optdb.py:    #add all opt with this tag
theano/gof/cc.py:            #add the signature for this node
theano/gof/cc.py:            #already tied to another FunctionGraph.")
theano/gof/opt.py:        #added to override the list's __eq__ implementation
theano/gof/opt.py:        #added to override the list's __neq__ implementation
theano/gof/opt.py:            #apply global optimizer
theano/gof/opt.py:            #apply local optimizer
theano/gof/fg.py:        #a "workalike" so we could do actual error checking