Merge pull request #3030 from abergeron/flake8_temp

theano/compile/function_module.py

@@ -1417,8 +1417,7 @@ def _pickle_FunctionMaker(self):
         accept_inplace=self.accept_inplace,
         function_builder=self.function_builder,
         profile=self.profile,
-        on_unused_input=self.on_unused_input,
-        )
+        on_unused_input=self.on_unused_input)
     return (_constructor_FunctionMaker, (kwargs,))
 
 

theano/compile/mode.py

@@ -71,8 +71,7 @@ predefined_linkers = {
     'vm': gof.vm.VM_Linker(use_cloop=False),  # Use allow_gc Theano flag
     'cvm': gof.vm.VM_Linker(use_cloop=True),  # Use allow_gc Theano flag
     'vm_nogc': gof.vm.VM_Linker(allow_gc=False, use_cloop=False),
-    'cvm_nogc': gof.vm.VM_Linker(allow_gc=False, use_cloop=True),
-    }
+    'cvm_nogc': gof.vm.VM_Linker(allow_gc=False, use_cloop=True)}
 
 
 def register_linker(name, linker):
@@ -115,8 +114,7 @@ predefined_optimizers = {
     'fast_run': OPT_FAST_RUN,
     'fast_run_stable': OPT_FAST_RUN_STABLE,
     'fast_compile': OPT_FAST_COMPILE,
-    'stabilize': OPT_STABILIZE
-    }
+    'stabilize': OPT_STABILIZE}
 
 
 def register_optimizer(name, opt):

theano/gof/compiledir.py

@@ -63,8 +63,7 @@ compiledir_format_dict = {
     "theano_version": theano.__version__,
     "numpy_version": numpy.__version__,
     "gxx_version": gcc_version_str.replace(" ", "_"),
-    "hostname": socket.gethostname(),
-    }
+    "hostname": socket.gethostname()}
 
 
 def short_platform(r=None, p=None):

theano/gof/compilelock.py

@@ -108,7 +108,7 @@ def _get_lock(lock_dir=None, **kw):
                 raise Exception("For some unknow reason, the lock was already "
                                 "taken, but no start time was registered.")
             now = time.time()
-            if now - get_lock.start_time > config.compile.timeout/2:
+            if now - get_lock.start_time > config.compile.timeout / 2:
                 lockpath = os.path.join(get_lock.lock_dir, 'lock')
                 _logger.info('Refreshing lock %s', str(lockpath))
                 refresh_lock(lockpath)

theano/gof/optdb.py

@@ -312,7 +312,7 @@ class SequenceDB(DB):
         positions = list(self.__position__.items())
 
         def c(a, b):
-            return cmp(a[1], b[1])
+            return ((a[1] > b[1]) - (a[1] < b[1]))
         positions.sort(c)
 
         print("  position", positions, file=stream)

theano/gof/tests/test_vm.py

@@ -46,7 +46,7 @@ class TestCallbacks(unittest.TestCase):
 
     def test_callback_with_ifelse(self):
         a, b, c = tensor.scalars('abc')
-        f = function([a, b, c], ifelse(a, 2*b, 2*c),
+        f = function([a, b, c], ifelse(a, 2 * b, 2 * c),
                      mode=Mode(
                          optimizer=None,
                          linker=vm.VM_Linker(callback=self.callback)))
@@ -62,7 +62,7 @@ def test_c_thunks():
     if theano.config.cxx:
         cases.append(True)
     for c_thunks in cases:
-        f = function([a, b, c], ifelse(a, a*b, b*c),
+        f = function([a, b, c], ifelse(a, a * b, b * c),
                      mode=Mode(
                          optimizer=None,
                          linker=vm.VM_Linker(c_thunks=c_thunks,
@@ -86,7 +86,7 @@ def test_speed():
     def numpy_version(x, depth):
         z = x
         for d in xrange(depth):
-            z = (z+z)
+            z = (z + z)
         return z
 
     def time_numpy():
@@ -136,7 +136,7 @@ def test_speed():
 
         print("%s takes %f s/Kop" % (
             name,
-            (1000*(t_b-t_a) / (steps_b - steps_a))))
+            (1000 * (t_b - t_a) / (steps_b - steps_a))))
 
     time_linker('c|py', OpWiseCLinker)
     time_linker('vmLinker', vm.VM_Linker)
@@ -185,7 +185,7 @@ def test_speed_lazy():
 
         print("%s takes %f s/Kop" % (
             name,
-            (1000*(t_b-t_a) / (steps_b - steps_a))))
+            (1000 * (t_b - t_a) / (steps_b - steps_a))))
 
     time_linker('vmLinker', vm.VM_Linker)
     time_linker('vmLinker_nogc', lambda: vm.VM_Linker(allow_gc=False))
@@ -230,6 +230,8 @@ if run_memory_usage_tests:
             a = cuda.CudaNdarray(n)
             a.sum()
             assert c == sys.getrefcount(n)
+            # This is to confuse flake8
+            a = a
             del a
             if not i % 1000:
                 print('.', end=' ')

theano/gof/type.py

@@ -282,11 +282,7 @@ class PureType(object):
                 'Cannot convert Type %(othertype)s '
                 '(of Variable %(other)s) into Type %(self)s. '
                 'You can try to manually convert %(other)s into a %(self)s.'
-                % dict(
-                    othertype=other.type,
-                    other=other,
-                    self=self)
-                )
+                % dict(othertype=other.type, other=other, self=self))
         return other
 
     def is_valid_value(self, a):

theano/misc/elemwise_time_test.py

@@ -35,7 +35,7 @@ def ElemwiseOpTime(N, script=False, loops=1000):
     x = T.vector('x')
     np.random.seed(1235)
     v = np.random.random(N).astype(theano.config.floatX)
-    f = theano.function([x], 2*x + x*x)
+    f = theano.function([x], 2 * x + x * x)
     f1 = theano.function([x], T.tanh(x))
     if not script:
         if theano.config.openmp:

theano/sandbox/cuda/tests/test_fftconv.py

@@ -194,7 +194,7 @@ class TestConv3dFFT(unittest.TestCase):
 
         res_ref = f_ref()
         res_fft = f_fft()
-        utt.assert_allclose(res_ref, res_fft,  rtol=1e-05, atol=1e-05)
+        utt.assert_allclose(res_ref, res_fft, rtol=1e-05, atol=1e-05)
 
     def run_conv_full(self, inputs_shape, filters_shape, pad=False):
         inputs_val = numpy.random.random(inputs_shape).astype('float32')
@@ -220,7 +220,7 @@ class TestConv3dFFT(unittest.TestCase):
 
         res_ref = f_ref()
         res_fft = f_fft()
-        utt.assert_allclose(res_ref, res_fft,  rtol=1e-04, atol=1e-04)
+        utt.assert_allclose(res_ref, res_fft, rtol=1e-04, atol=1e-04)
 
     def test_valid(self):
         self.run_conv_valid(inputs_shape=(16, 20, 32, 16, 1),
@@ -299,7 +299,7 @@ class TestConv3dFFT(unittest.TestCase):
         res_ref = f_ref()
         res_fft = f_fft()
 
-        utt.assert_allclose(res_ref, res_fft,  rtol=1e-04, atol=1e-04)
+        utt.assert_allclose(res_ref, res_fft, rtol=1e-04, atol=1e-04)
 
     def test_opt_convtransp3d_fft(self):
         inputs_shape = (2, 9, 16, 12, 10)

theano/sandbox/cuda/tests/test_type.py

-import six.moves.cPickle as pickle
 import os.path
-import sys
 
 from nose.tools import assert_raises
 import numpy

theano/sandbox/gpuarray/opt.py

@@ -255,7 +255,7 @@ def local_gpu_elemwise(node):
     scal_op = op.scalar_op
     name = op.name
     if name:
-        name = 'Gpu'+name
+        name = 'Gpu' + name
     res = GpuElemwise(scal_op, name=name,
                       inplace_pattern=copy.copy(op.inplace_pattern),
                       nfunc_spec=op.nfunc_spec)
@@ -349,7 +349,7 @@ def local_gpu_pdbbreakpoint_op(node):
         nb_monitored_vars = len(node.outputs)
         for i in range(nb_monitored_vars):
 
-            inp = old_inputs[i+1]
+            inp = old_inputs[i + 1]
             out = old_outputs[i]
 
             input_is_from_gpu = (inp.owner and

theano/scalar/tests/test_basic_sympy.py

@@ -25,12 +25,12 @@ def test_grad():
     op = SymPyCCode([xs], xs**2)
     zt = op(xt)
     ztprime = theano.grad(zt, xt)
-    assert ztprime.owner.op.expr == 2*xs
+    assert ztprime.owner.op.expr == 2 * xs
 
 
 def test_multivar_grad():
-    op = SymPyCCode([xs, ys], xs**2 + ys**3)
+    op = SymPyCCode([xs, ys], xs ** 2 + ys ** 3)
     zt = op(xt, yt)
     dzdx, dzdy = theano.grad(zt, [xt, yt])
-    assert dzdx.owner.op.expr == 2*xs
-    assert dzdy.owner.op.expr == 3*ys**2
+    assert dzdx.owner.op.expr == 2 * xs
+    assert dzdy.owner.op.expr == 3 * ys ** 2

theano/tensor/inplace.py

@@ -29,9 +29,6 @@ def _scal_inplace(symbol):
         if not r.owner:
             return False
         op = r.owner.op
-#         print op, rval, r.owner and op == rval
-#         print op.inplace_pattern, rval.inplace_pattern, op.inplace_pattern == rval.inplace_pattern
-#         print op.scalar_op, rval.scalar_op, op.scalar_op == rval.scalar_op
         return r.owner.op == rval
 
     pprint.assign(chk, printing.FunctionPrinter(symbolname.replace('_inplace', '=')))
@@ -348,17 +345,13 @@ def conj_inplace(a):
 pprint.assign(add_inplace, printing.OperatorPrinter('+=', -2, 'either'))
 pprint.assign(mul_inplace, printing.OperatorPrinter('*=', -1, 'either'))
 pprint.assign(sub_inplace, printing.OperatorPrinter('-=', -2, 'left'))
-pprint.assign(neg_inplace, printing.OperatorPrinter('-=',  0, 'either'))
+pprint.assign(neg_inplace, printing.OperatorPrinter('-=', 0, 'either'))
 pprint.assign(true_div_inplace, printing.OperatorPrinter('/=', -1, 'left'))
 pprint.assign(int_div_inplace, printing.OperatorPrinter('//=', -1, 'left'))
 pprint.assign(pow_inplace, printing.OperatorPrinter('**=', 1, 'right'))
 
 
 def transpose_inplace(x, **kwargs):
-    """Perform a transpose on a tensor without copying the underlying storage"""
+    "Perform a transpose on a tensor without copying the underlying storage"
     dims = list(range(x.ndim - 1, -1, -1))
     return elemwise.DimShuffle(x.broadcastable, dims, inplace=True)(x)
-
-#pprint.assign(transpose_inplace, printing.MemberPrinter('T'))
-
-

theano/tensor/shared_randomstreams.py

@@ -24,11 +24,11 @@ def randomstate_constructor(value, name=None, strict=False,
     if not borrow:
         value = copy.deepcopy(value)
     return RandomStateSharedVariable(
-            type=raw_random.random_state_type,
-            value=value,
-            name=name,
-            strict=strict,
-            allow_downcast=allow_downcast)
+        type=raw_random.random_state_type,
+        value=value,
+        name=name,
+        strict=strict,
+        allow_downcast=allow_downcast)
 
 
 class RandomStreams(raw_random.RandomStreamsBase):

theano/tensor/slinalg.py

@@ -25,15 +25,14 @@ except ImportError:
     imported_scipy = False
 
 MATRIX_STRUCTURES = (
-        'general',
-        'symmetric',
-        'lower_triangular',
-        'upper_triangular',
-        'hermitian',
-        'banded',
-        'diagonal',
-        'toeplitz',
-        )
+    'general',
+    'symmetric',
+    'lower_triangular',
+    'upper_triangular',
+    'hermitian',
+    'banded',
+    'diagonal',
+    'toeplitz')
 
 
 class Cholesky(Op):
@@ -168,8 +167,8 @@ class Solve(Op):
         assert A.ndim == 2
         assert b.ndim in [1, 2]
         otype = tensor.tensor(
-                broadcastable=b.broadcastable,
-                dtype=(A * b).dtype)
+            broadcastable=b.broadcastable,
+            dtype=(A * b).dtype)
         return Apply(self, [A, b], [otype])
 
     def perform(self, node, inputs, output_storage):
@@ -294,7 +293,7 @@ class EigvalshGrad(Op):
         (a, b, gw) = inputs
         w, v = scipy.linalg.eigh(a, b, lower=self.lower)
         gA = v.dot(numpy.diag(gw).dot(v.T))
-        gB = - v.dot(numpy.diag(gw*w).dot(v.T))
+        gB = - v.dot(numpy.diag(gw * w).dot(v.T))
 
         # See EighGrad comments for an explanation of these lines
         out1 = self.tri0(gA) + self.tri1(gA).T

theano/tensor/subtensor.py

@@ -155,16 +155,16 @@ def get_canonical_form_slice(theslice, length):
                                   1), 1)
                 stop_plus_len = stop + length
                 stop = switch(
-                        lt(stop, 0),
-                        # stop < 0
-                        switch(
-                            lt(stop_plus_len, 0),
-                            # stop + len < 0
-                            0,
-                            # stop + len >= 0
-                            stop_plus_len),
-                        # stop >= 0: use min(stop, length)
-                        switch(lt(stop, length), stop, length))
+                    lt(stop, 0),
+                    # stop < 0
+                    switch(
+                        lt(stop_plus_len, 0),
+                        # stop + len < 0
+                        0,
+                        # stop + len >= 0
+                        stop_plus_len),
+                    # stop >= 0: use min(stop, length)
+                    switch(lt(stop, length), stop, length))
                 return slice(0, stop, 1), 1
             elif is_stop_length:
                 # start:length:1
@@ -173,16 +173,16 @@ def get_canonical_form_slice(theslice, length):
                                  length, 1), 1
                 start_plus_len = start + length
                 start = switch(
-                        lt(start, 0),
-                        # start < 0
-                        switch(
-                            lt(start_plus_len, 0),
-                            # start + len < 0
-                            0,
-                            # start + len >= 0
-                            start_plus_len),
-                        # start >= 0: use min(start, length)
-                        switch(lt(start, length), start, length))
+                    lt(start, 0),
+                    # start < 0
+                    switch(
+                        lt(start_plus_len, 0),
+                        # start + len < 0
+                        0,
+                        # start + len >= 0
+                        start_plus_len),
+                    # start >= 0: use min(start, length)
+                    switch(lt(start, length), start, length))
                 return slice(start, length, 1), 1
 
         # This is the generic case.
@@ -614,10 +614,8 @@ class Subtensor(Op):
         helper_c_code
         """
 
-        return {
-            "c_prefix": "PyArray",
-            "strides_mul": 1,
-            }
+        return {"c_prefix": "PyArray",
+                "strides_mul": 1}
 
     @staticmethod
     def helper_c_code(node, name, inputs, outputs, sub, idx_list, view_ndim,

theano/tensor/var.py

@@ -389,17 +389,15 @@ class _tensor_py_operators:
                     axis = i
 
         if advanced:
-            if (axis is not None
-                and all(isinstance(a, slice) and
-                        equal_slices(a, slice(None)) for a in args[:axis])
-                and all(isinstance(a, slice) and
-                        equal_slices(a, slice(None)) for a in args[axis + 1:])
-                and isinstance(args[axis], (
-                    numpy.ndarray,
-                    list,
-                    TensorVariable,
-                    TensorConstant,
-                    theano.tensor.sharedvar.TensorSharedVariable))):
+            if (axis is not None and
+                all(isinstance(a, slice) and
+                    equal_slices(a, slice(None)) for a in args[:axis]) and
+                all(isinstance(a, slice) and
+                    equal_slices(a, slice(None)) for a in args[axis + 1:]) and
+                isinstance(args[axis],
+                           (numpy.ndarray, list,
+                            TensorVariable, TensorConstant,
+                            theano.tensor.sharedvar.TensorSharedVariable))):
                 return self.take(args[axis], axis)
             else:
                 return theano.tensor.subtensor.advanced_subtensor(self, *args)

theano/tests/breakpoint.py

@@ -88,7 +88,7 @@ class PdbBreakpoint(Op):
         for i in range(len(monitored_vars)):
             # Every output i is a view of the input i+1 because of the input
             # condition.
-            new_op.view_map[i] = [i+1]
+            new_op.view_map[i] = [i + 1]
             new_op.inp_types.append(monitored_vars[i].type)
 
         # Build the Apply node
@@ -125,7 +125,7 @@ class PdbBreakpoint(Op):
         else:
             # Simply return views on the monitored variables
             for i in range(len(output_storage)):
-                output_storage[i][0] = inputs[i+1]
+                output_storage[i][0] = inputs[i + 1]
 
     def grad(self, inputs, output_gradients):
         return ([DisconnectedType()()] + output_gradients)

theano/tests/disturb_mem.py

@@ -20,4 +20,4 @@ def disturb_mem():
     ms = int(ms)
     n = ms % 1000
     m = ms // 1000
-    l = [[0]*m for i in xrange(n)]
+    l = [[0] * m for i in xrange(n)]

theano/tests/test_dictionary_output.py

@@ -12,8 +12,8 @@ class dictionary_output_checker(unittest.TestCase):
         '''
 
         x = T.scalar()
-        f = theano.function([x], outputs={'a': x, 'c': x*2,
-                                          'b': x*3, '1': x*4})
+        f = theano.function([x], outputs={'a': x, 'c': x * 2,
+                                          'b': x * 3, '1': x * 4})
 
         outputs = f(10.0)
 

theano/tests/test_flake8.py

@@ -6,7 +6,6 @@ from nose.plugins.skip import SkipTest
 import os
 from fnmatch import fnmatch
 import theano
-from theano.compat import PY3
 try:
     import flake8.engine
     import flake8.main
@@ -18,6 +17,10 @@ __authors__ = ("Saizheng Zhang")
 __copyright__ = "(c) 2015, Universite de Montreal"
 __contact__ = "Saizheng Zhang <saizhenglisa..at..gmail.com>"
 
+# This corresponds to "line too long" and it's too much of a pain with
+# all of the C code
+ignore = ('E501',)
+
 whitelist_flake8 = [
     "compat/six.py",  # This is bundled code that will be deleted, don't fix it
     "__init__.py",
@@ -74,7 +77,6 @@ whitelist_flake8 = [
     "tensor/extra_ops.py",
     "tensor/nlinalg.py",
     "tensor/blas_c.py",
-    "tensor/io.py",
     "tensor/elemwise_cgen.py",
     "tensor/raw_random.py",
     "tensor/blas_scipy.py",
@@ -93,7 +95,6 @@ whitelist_flake8 = [
     "tensor/tests/test_merge.py",
     "tensor/tests/test_gc.py",
     "tensor/tests/test_complex.py",
-    "tensor/tests/test_type_other.py",
     "tensor/tests/test_io.py",
     "tensor/tests/test_sharedvar.py",
     "tensor/tests/test_fourier.py",
@@ -160,8 +161,6 @@ whitelist_flake8 = [
     "sandbox/cuda/opt.py",
     "sandbox/cuda/blas.py",
     "sandbox/cuda/blocksparse.py",
-    "sandbox/cuda/GpuConv3D.py",
-    "sandbox/cuda/extra_ops.py",
     "sandbox/cuda/rng_curand.py",
     "sandbox/cuda/fftconv.py",
     "sandbox/cuda/kernel_codegen.py",
@@ -172,7 +171,6 @@ whitelist_flake8 = [
     "sandbox/cuda/tests/test_gradient.py",
     "sandbox/cuda/tests/test_neighbours.py",
     "sandbox/cuda/tests/test_conv_cuda_ndarray.py",
-    "sandbox/cuda/tests/test_type.py",
     "sandbox/cuda/tests/test_var.py",
     "sandbox/cuda/tests/test_opt.py",
     "sandbox/cuda/tests/test_blas.py",
@@ -235,7 +233,6 @@ whitelist_flake8 = [
     "misc/pycuda_utils.py",
     "misc/pycuda_example.py",
     "misc/ordered_set.py",
-    "misc/windows.py",
     "misc/strutil.py",
     "misc/gnumpy_utils.py",
     "misc/may_share_memory.py",
@@ -250,7 +247,6 @@ whitelist_flake8 = [
     "misc/tests/test_pycuda_example.py",
     "misc/hooks/reindent.py",
     "misc/hooks/check_whitespace.py",
-    "sparse/sharedvar.py",
     "sparse/type.py",
     "sparse/__init__.py",
     "sparse/opt.py",
@@ -308,15 +304,13 @@ def test_format_flake8():
     """
     if not flake8_available:
         raise SkipTest("flake8 is not installed")
-    if PY3:
-        raise SkipTest("not testing in python3 since 2to3 ran")
     total_errors = 0
     for path in list_files():
         rel_path = os.path.relpath(path, theano.__path__[0])
         if rel_path in whitelist_flake8:
             continue
         else:
-            error_num = flake8.main.check_file(path)
+            error_num = flake8.main.check_file(path, ignore=ignore)
             total_errors += error_num
     if total_errors > 0:
         raise AssertionError("FLAKE8 Format not respected")
@@ -332,7 +326,8 @@ def print_files_information_flake8():
     non_infracting_files = []
     for path in list_files():
         rel_path = os.path.relpath(path, theano.__path__[0])
-        number_of_infractions = flake8.main.check_file(path)
+        number_of_infractions = flake8.main.check_file(path,
+                                                       ignore=ignore)
         if number_of_infractions > 0:
             if rel_path not in whitelist_flake8:
                 infracting_files.append(rel_path)
@@ -359,7 +354,8 @@ def check_all_files(dir_path=theano.__path__[0], pattern='*.py'):
     for (dir, _, files) in os.walk(dir_path):
         for f in files:
             if fnmatch(f, pattern):
-                error_num = flake8.main.check_file(os.path.join(dir, f))
+                error_num = flake8.main.check_file(os.path.join(dir, f),
+                                                   ignore=ignore)
                 if error_num > 0:
                     path = os.path.relpath(os.path.join(dir, f),
                                            theano.__path__[0])

theano/tests/test_printing.py

@@ -495,17 +495,17 @@ def test_scan_debugprint3():
 def test_scan_debugprint4():
 
     def fn(a_m2, a_m1, b_m2, b_m1):
-        return a_m1+a_m2, b_m1+b_m2
+        return a_m1 + a_m2, b_m1 + b_m2
 
     a0 = theano.shared(numpy.arange(2))
     b0 = theano.shared(numpy.arange(2))
 
-    (a, b), _ = theano.scan(fn, outputs_info=[
-        {'initial': a0, 'taps': [-2, -1]},
-        {'initial': b0, 'taps': [-2, -1]}],
-                            n_steps=5)
+    (a, b), _ = theano.scan(
+        fn, outputs_info=[{'initial': a0, 'taps': [-2, -1]},
+                          {'initial': b0, 'taps': [-2, -1]}],
+        n_steps=5)
 
-    final_result = a+b
+    final_result = a + b
     output_str = theano.printing.debugprint(final_result, file='str')
     lines = []
     for line in output_str.split('\n'):