提交 2928d02a authored 作者: Frédéric Bastien's avatar Frédéric Bastien

Merge pull request #3507 from nouiz/mixed3

Mixed: warning, error msg, tests fix, clean up, crash
......@@ -580,7 +580,7 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
print_view_map=False, order=None, ids='CHAR',
stop_on_name=False, prefix_child=None,
scan_ops=None, profile=None,
scan_inner_to_outer_inputs=None):
scan_inner_to_outer_inputs=None, smap=None):
"""
Print the graph leading to `r` to given depth.
......@@ -620,7 +620,8 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
scan_inner_to_outer_inputs
A dictionary mapping a scan ops inner function inputs to the scan op
inputs (outer inputs) for printing purposes.
smap
None or the storage_map when printing an Theano function.
"""
if depth == 0:
return
......@@ -689,23 +690,21 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
already_printed = a in done # get_id_str put it in the dict
id_str = get_id_str(a)
if len(a.outputs) == 1:
idx = ""
else:
idx = ".%i" % a.outputs.index(r)
data = ""
if smap:
data = " " + str(smap.get(a.outputs[0], ''))
if profile is None or a not in profile.apply_time:
if len(a.outputs) == 1:
print('%s%s %s%s \'%s\' %s %s %s' % (prefix, a.op,
id_str,
type_str,
print('%s%s%s %s%s \'%s\' %s %s %s%s' % (prefix, a.op,
idx,
id_str, type_str,
r_name,
destroy_map_str,
view_map_str,
o), file=file)
else:
print('%s%s.%i %s%s \'%s\' %s %s %s' % (prefix, a.op,
a.outputs.index(r),
id_str, type_str,
r_name,
destroy_map_str,
view_map_str,
o), file=file)
o, data), file=file)
else:
op_time = profile.apply_time[a]
op_time_percent = (op_time / profile.fct_call_time) * 100
......@@ -714,31 +713,22 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
tot_time_percent = (tot_time_dict[a] / profile.fct_call_time) * 100
if len(a.outputs) == 1:
print("%s%s %s%s '%s' %s %s %s --> "
"%8.2es %4.1f%% %8.2es %4.1f%%"
% (prefix, a.op,
id_str,
type_str,
r_name,
destroy_map_str,
view_map_str,
o, op_time,
op_time_percent,
tot_time,
tot_time_percent), file=file)
idx = ""
else:
print("%s%s.%i %s%s '%s' %s %s %s --> "
"%8.2es %4.1f%% %8.2es %4.1f%%"
% (prefix, a.op,
a.outputs.index(r),
id_str, type_str,
r_name,
destroy_map_str,
view_map_str,
o, op_time,
op_time_percent,
tot_time,
tot_time_percent), file=file)
idx = ".%i" % a.outputs.index(r)
print("%s%s%s %s%s '%s' %s %s %s%s --> "
"%8.2es %4.1f%% %8.2es %4.1f%%"
% (prefix, a.op,
idx,
id_str, type_str,
r_name,
destroy_map_str,
view_map_str,
o, data,
op_time,
op_time_percent,
tot_time,
tot_time_percent), file=file)
if not already_printed:
if (not stop_on_name or
......@@ -761,7 +751,8 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
ids=ids, stop_on_name=stop_on_name,
prefix_child=new_prefix_child, scan_ops=scan_ops,
profile=profile,
scan_inner_to_outer_inputs=scan_inner_to_outer_inputs)
scan_inner_to_outer_inputs=scan_inner_to_outer_inputs,
smap=smap)
else:
if scan_inner_to_outer_inputs is not None and\
r in scan_inner_to_outer_inputs:
......@@ -777,8 +768,13 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
outer_id_str), file=file)
else:
# this is an input variable
data = ""
if smap:
data = " " + str(smap.get(r, ''))
id_str = get_id_str(r)
print('%s%s %s%s' % (prefix, r, id_str, type_str), file=file)
print('%s%s %s%s%s' % (prefix, r, id_str,
type_str, data),
file=file)
return file
......
......@@ -91,6 +91,8 @@ exclude = []
if not theano.config.cxx:
exclude = ['cxx_only']
OPT_NONE = gof.Query(include=[], exclude=exclude)
# Even if multiple merge optimizer call will be there, this shouldn't
# impact performance.
OPT_MERGE = gof.Query(include=['merge'], exclude=exclude)
OPT_FAST_RUN = gof.Query(include=['fast_run'], exclude=exclude)
OPT_FAST_RUN_STABLE = OPT_FAST_RUN.requiring('stable')
......@@ -113,7 +115,7 @@ OPT_STABILIZE.name = 'OPT_STABILIZE'
predefined_optimizers = {
None: OPT_NONE,
'None': OPT_NONE,
'merge': gof.MergeOptimizer(),
'merge': OPT_MERGE,
'fast_run': OPT_FAST_RUN,
'fast_run_stable': OPT_FAST_RUN_STABLE,
'fast_compile': OPT_FAST_COMPILE,
......
......@@ -25,3 +25,8 @@ def test_no_output_from_implace():
fct_opt = theano.function([x, y], b, mode=mode_opt)
op = fct_opt.maker.fgraph.outputs[0].owner.op
assert (not hasattr(op, 'destroy_map') or 0 not in op.destroy_map)
def test_including():
mode = theano.Mode(optimizer='merge')
mode.including('fast_compile')
......@@ -32,7 +32,7 @@ class TestPyDotFormatter(unittest.TestCase):
expected = 11
if th.config.mode == "FAST_COMPILE":
expected = 12
self.assertEqual(len(graph.get_nodes()), 12)
self.assertEqual(len(graph.get_nodes()), expected)
nc = self.node_counts(graph)
if th.config.mode == "FAST_COMPILE":
......
......@@ -547,9 +547,7 @@ class CLinker(link.Linker):
if no_recycling is None:
no_recycling = []
if self.fgraph is not None and self.fgraph is not fgraph:
return type(self)().accept(fgraph, no_recycling)
# raise Exception("Cannot accept from a Linker that is already"
# " tied to another FunctionGraph.")
return type(self)(self.schedule).accept(fgraph, no_recycling)
self.fgraph = fgraph
self.fetch_variables()
self.no_recycling = no_recycling
......@@ -1755,7 +1753,8 @@ class OpWiseCLinker(link.LocalLinker):
return type(self)(
fallback_on_perform=self.fallback_on_perform,
allow_gc=self.allow_gc,
nice_errors=self.nice_errors
nice_errors=self.nice_errors,
schedule=self.schedule,
).accept(fgraph, no_recycling)
# raise Exception("Cannot accept from a Linker that is
# already tied to another FunctionGraph.")
......@@ -1908,7 +1907,8 @@ class DualLinker(link.Linker):
if no_recycling is None:
no_recycling = []
if self.fgraph is not None and self.fgraph is not fgraph:
return type(self)(self.checker).accept(fgraph, no_recycling)
return type(self)(self.checker, self.schedule).accept(
fgraph, no_recycling)
self.fgraph = fgraph
self.no_recycling = no_recycling
return self
......
......@@ -17,6 +17,7 @@ import tempfile
import time
import platform
import distutils.sysconfig
import warnings
import numpy.distutils # TODO: TensorType should handle this
......@@ -324,7 +325,10 @@ def dlimport(fullpath, suffix=None):
if hasattr(importlib, "invalidate_caches"):
importlib.invalidate_caches()
t0 = time.time()
rval = __import__(module_name, {}, {}, [module_name])
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message="numpy.ndarray size changed")
rval = __import__(module_name, {}, {}, [module_name])
t1 = time.time()
import_time += t1 - t0
if not rval:
......
......@@ -48,7 +48,7 @@ VALID_ASSOC = set(['left', 'right', 'either'])
def debugprint(obj, depth=-1, print_type=False,
file=None, ids='CHAR', stop_on_name=False,
done=None):
done=None, print_storage=False):
"""Print a computation graph as text to stdout or a file.
:type obj: Variable, Apply, or Function instance
......@@ -70,6 +70,10 @@ def debugprint(obj, depth=-1, print_type=False,
:type done: None or dict
:param done: A dict where we store the ids of printed node.
Useful to have multiple call to debugprint share the same ids.
:type print_storage: bool
:param print_storage: If True, this will print the storage map
for Theano functions. Combined with allow_gc=False, after the
execution of a Theano function, we see the intermediate result.
:returns: string if `file` == 'str', else file arg
......@@ -101,7 +105,8 @@ def debugprint(obj, depth=-1, print_type=False,
done = dict()
results_to_print = []
profile_list = []
order = []
order = [] # Toposort
smap = [] # storage_map
if isinstance(obj, (list, tuple, set)):
lobj = obj
else:
......@@ -110,24 +115,41 @@ def debugprint(obj, depth=-1, print_type=False,
if isinstance(obj, gof.Variable):
results_to_print.append(obj)
profile_list.append(None)
smap.append(None)
order.append(None)
elif isinstance(obj, gof.Apply):
results_to_print.extend(obj.outputs)
profile_list.extend([None for item in obj.outputs])
smap.extend([None for item in obj.outputs])
order.extend([None for item in obj.outputs])
elif isinstance(obj, Function):
results_to_print.extend(obj.maker.fgraph.outputs)
profile_list.extend(
[obj.profile for item in obj.maker.fgraph.outputs])
order = obj.maker.fgraph.toposort()
if print_storage:
smap.extend(
[obj.fn.storage_map for item in obj.maker.fgraph.outputs])
else:
smap.extend(
[None for item in obj.maker.fgraph.outputs])
topo = obj.maker.fgraph.toposort()
order.extend(
[topo for item in obj.maker.fgraph.outputs])
elif isinstance(obj, gof.FunctionGraph):
results_to_print.extend(obj.outputs)
profile_list.extend([getattr(obj, 'profile', None)
for item in obj.outputs])
order = obj.toposort()
smap.extend([getattr(obj, 'storage_map', None)
for item in obj.outputs])
topo = obj.toposort()
order.extend([topo for item in obj.outputs])
elif isinstance(obj, (integer_types, float, np.ndarray)):
print(obj)
elif isinstance(obj, (theano.In, theano.Out)):
results_to_print.append(obj.variable)
profile_list.append(None)
smap.append(None)
order.append(None)
else:
raise TypeError("debugprint cannot print an object of this type",
obj)
......@@ -152,16 +174,16 @@ N.B.:
to remove when optimizing a graph because their <total time> is very low.
""", file=_file)
for r, p in zip(results_to_print, profile_list):
for r, p, s, o in zip(results_to_print, profile_list, smap, order):
# Add the parent scan op to the list as well
if (hasattr(r.owner, 'op') and
isinstance(r.owner.op, theano.scan_module.scan_op.Scan)):
scan_ops.append(r)
debugmode.debugprint(r, depth=depth, done=done, print_type=print_type,
file=_file, order=order, ids=ids,
file=_file, order=o, ids=ids,
scan_ops=scan_ops, stop_on_name=stop_on_name,
profile=p)
profile=p, smap=s)
if len(scan_ops) > 0:
print("", file=_file)
......@@ -996,7 +1018,11 @@ def pydotprint(fct, outfile=None,
else:
new_name = basename + '_' + str(idx)
new_name = os.path.join(path, new_name + ext)
pydotprint(scan_op.op.fn, new_name, compact, format, with_ids,
if hasattr(scan_op.op, 'fn'):
to_print = scan_op.op.fn
else:
to_print = scan_op.op.outputs
pydotprint(to_print, new_name, compact, format, with_ids,
high_contrast, cond_highlight, colorCodes,
max_label_size, scan_graphs)
......
......@@ -1765,10 +1765,6 @@ def dnn_pool(img, ws, stride=(1, 1), mode='max', pad=(0, 0)):
bottom borders.
pad_w is the number of zero-valued pixels added to each of the left
and right borders.
nd
Number of dimensions of pooling, can be 2 or 3 for 2d or 3d pooling
If set to 3 all other params (except mode) must have an extra
dimension to match. 3 is only available for cudnn v3
.. warning:: The cuDNN library only works with GPU that have a compute
capability of 3.0 or higer. This means that older GPU will not
......
......@@ -279,8 +279,7 @@ def test_pooling():
a = f1(data).__array__()
b = f2(data).__array__()
assert numpy.allclose(a, b,
atol=numpy.finfo(numpy.float32).eps)
utt.assert_allclose(a, b)
# Test the grad
for shp in [(1, 1, 2, 2),
......@@ -338,7 +337,7 @@ def test_pooling():
assert any([isinstance(node.op, AveragePoolGrad)
for node in fc.maker.fgraph.toposort()])
c_out = fc(data)
assert numpy.allclose(c_out, g_out)
utt.assert_allclose(c_out, g_out)
def test_pooling3d():
......@@ -443,7 +442,7 @@ def test_pooling3d():
fc = theano.function([x], theano.grad(out.sum(), x),
mode=mode_without_gpu)
c_out = fc(data)
assert numpy.allclose(c_out, g_out)
utt.assert_allclose(c_out, g_out)
def test_pooling_opt():
......@@ -1357,8 +1356,10 @@ def test_conv3d_bwd():
# Compare the results of the two implementations
res_ref = f_ref()
res = f()
utt.assert_allclose(res_ref[0], res[0])
utt.assert_allclose(res_ref[1], res[1])
# Needed for big size for some seed
# raise rtol to make the test pass with more seed.
utt.assert_allclose(res_ref[0], res[0], rtol=2e-5)
utt.assert_allclose(res_ref[1], res[1], rtol=2e-5)
test_cases = get_conv3d_test_cases()
for (i_shape, f_shape, subsample), border_mode, conv_mode in test_cases:
......
......@@ -132,5 +132,10 @@ except ImportError:
# Release lock on compilation directory.
release_lock()
from scan_perform.scan_perform import *
# This is caused as cython use the old NumPy C-API but we use the new one.
# To fix it completly, we would need to modify Cython to use the new API.
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message="numpy.ndarray size changed")
from scan_perform.scan_perform import *
assert version == get_version()
......@@ -2654,14 +2654,20 @@ class Alloc(gof.Op):
sh = [as_tensor_variable(s) for s in shape]
bcast = []
for i, s in enumerate(sh):
if config.exception_verbosity == 'high':
s_as_str = '\n' + min_informative_str(s)
else:
s_as_str = str(s)
if s.type.dtype[:3] not in ('int', 'uin'):
if config.exception_verbosity == 'high':
s_as_str = '\n' + min_informative_str(s)
else:
s_as_str = str(s)
raise TypeError('Shape arguments to Alloc must be integers, '
'but argument %s is not for apply node: %s' %
(i, s_as_str))
if s.ndim != 0:
raise TypeError(
"Each shape dimension to Alloc must be a scalar, ",
'but dimension %s have %d dimensions for apply node: %s' %
(i, s.ndim, s_as_str))
# if s is constant 1, then we're broadcastable in that dim
try:
const_shp = get_scalar_constant_value(s)
......
......@@ -782,22 +782,24 @@ class MakeVector(T.Op):
# So there will be (1 * nb_dtype) + ((nb len(inp) - 1 ))
# different c code with the following algo
out_shape = len(inp)
out_dtype = numpy.dtype(node.outputs[0].dtype).num
out_num = numpy.dtype(node.outputs[0].dtype).num
# don't use dtype_%(out)s as when check_input=False, it isn't defined.
out_dtype = node.outputs[0].type.dtype_specs()[1]
if len(inp) > 0:
assert self.dtype == node.inputs[0].dtype
out_dtype = 'PyArray_TYPE(%s)' % inp[0]
out_num = 'PyArray_TYPE(%s)' % inp[0]
ret = """
npy_intp dims[1];
dims[0] = %(out_shape)s;
if(!%(out)s || PyArray_DIMS(%(out)s)[0] != %(out_shape)s){
Py_XDECREF(%(out)s);
%(out)s = (PyArrayObject*)PyArray_EMPTY(1, dims, %(out_dtype)s, 0);
%(out)s = (PyArrayObject*)PyArray_EMPTY(1, dims, %(out_num)s, 0);
}
""" % locals()
for idx, i in enumerate(inp):
ret += """
*((dtype_%(out)s *)PyArray_GETPTR1(%(out)s, %(idx)s)) = *((dtype_%(out)s *) PyArray_DATA(%(i)s));
*((%(out_dtype)s *)PyArray_GETPTR1(%(out)s, %(idx)s)) = *((%(out_dtype)s *) PyArray_DATA(%(i)s));
""" % locals()
return ret
......@@ -3468,7 +3470,6 @@ def local_mul_switch_sink(node):
return False
for idx, i in enumerate(node.inputs):
if i.owner and i.owner.op == T.switch:
# import ipdb;ipdb.set_trace()
switch = i.owner
try:
if (get_scalar_constant_value(
......@@ -4904,9 +4905,10 @@ register_canonicalize(local_inv_canon)
@gof.local_optimizer([T.pow])
def local_pow_canonicalize(node):
if node.op == T.pow:
if local_mul_canonizer.get_constant(node.inputs[1]) == 0:
cst = local_mul_canonizer.get_constant(node.inputs[1])
if cst == 0:
return [broadcast_like(1, node.outputs[0], node.fgraph)]
if local_mul_canonizer.get_constant(node.inputs[1]) == 1:
if cst == 1:
return [broadcast_like(node.inputs[0], node.outputs[0], node.fgraph)]
else:
return False
......
......@@ -2026,6 +2026,7 @@ AllocTester = makeBroadcastTester(
bad_shape12=(rand(7), numpy.int32(7), numpy.int32(5)),
),
bad_build=dict(
vec=(rand(1), [numpy.int32(2)]),
too_big32=(rand(6, 2, 4), numpy.
int32(6), numpy.int32(2)),
too_big32b=(rand(6, 2, 4), numpy.
......
......@@ -159,7 +159,7 @@ class test_Broadcast(unittest.TestCase):
cop = Elemwise
openmp_minsize = 2*config.openmp_elemwise_minsize
openmp_minsize_sqrt = math.ceil(math.sqrt(openmp_minsize))
openmp_minsize_sqrt = int(math.ceil(math.sqrt(openmp_minsize)))
# The order is important if you change them.
linkers = [gof.PerformLinker, gof.CLinker]
......
......@@ -164,6 +164,8 @@ def test_debugprint():
F = D + E
G = C + F
mode = theano.compile.get_default_mode().including('fusion')
g = theano.function([A, B, D, E], G, mode=mode)
# just test that it work
debugprint(G)
......@@ -249,6 +251,24 @@ def test_debugprint():
assert s == reference
# test print_storage=True
s = StringIO()
debugprint(g, file=s, ids='', print_storage=True)
s = s.getvalue()
# The additional white space are needed!
reference = '\n'.join([
"Elemwise{add,no_inplace} '' 0 [None]",
" |A [None]",
" |B [None]",
" |D [None]",
" |E [None]",
]) + '\n'
if s != reference:
print('--' + s + '--')
print('--' + reference + '--')
assert s == reference
def test_scan_debugprint1():
k = tensor.iscalar("k")
......@@ -702,3 +722,28 @@ def test_scan_debugprint5():
for truth, out in zip(expected_output.split("\n"), lines):
assert truth.strip() == out.strip()
def test_printing_scan():
# Skip test if pydot is not available.
if not theano.printing.pydot_imported:
raise SkipTest('pydot not available')
def f_pow2(x_tm1):
return 2 * x_tm1
state = theano.tensor.scalar('state')
n_steps = theano.tensor.iscalar('nsteps')
output, updates = theano.scan(f_pow2,
[],
state,
[],
n_steps=n_steps,
truncate_gradient=-1,
go_backwards=False)
f = theano.function([state, n_steps],
output,
updates=updates,
allow_input_downcast=True)
theano.printing.pydotprint(output, scan_graphs=True)
theano.printing.pydotprint(f, scan_graphs=True)
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