提交 9944efc5 authored 作者: abergeron's avatar abergeron

Merge pull request #2119 from nouiz/warning

Warning
......@@ -84,7 +84,9 @@ def _atexit_print_fn():
if len(to_sum) > 1:
# Make a global profile
cum = copy.copy(to_sum[0])
cum.message = "Sum of all printed profiles at exit excluding Scan op profile."
msg = ("Sum of all(%d) printed profiles at exit excluding Scan op"
" profile." % len(to_sum))
cum.message = msg
for ps in to_sum[1:]:
for attr in ["compile_time", "fct_call_time", "fct_callcount",
"vm_call_time", "optimizer_time", "linker_time",
......@@ -655,6 +657,7 @@ class ProfileStats(object):
# track min peak memory usage
min_max_peak = 0
min_peak_time = 0
def count_running_memory(order, fgraph, nodes_mem):
"""
......@@ -981,7 +984,9 @@ class ProfileStats(object):
# Config: whether print min memory peak
if config.profiling.min_peak_memory:
node_list = fgraph.apply_nodes
ttt = time.time()
min_peak = count_minimum_peak(node_list, fgraph, nodes_mem)
min_peak_time += time.time() - ttt
min_max_peak = max(min_max_peak, min_peak)
del fgraph, nodes_mem
......@@ -1006,8 +1011,8 @@ class ProfileStats(object):
new_max_running_max_memory_size / 1024.)), int(round(
max_running_max_memory_size / 1024.)))
if min_max_peak:
print >> file, " Minimum peak from all valid apply node order is %dKB" % int(round(
min_max_peak / 1024.))
print >> file, " Minimum peak from all valid apply node order is %dKB(took %f.2s to compute)" % (int(round(
min_max_peak / 1024.)), min_peak_time)
print >> file, " Memory saved if views are used: %dKB (%dKB)" % (int(
round(new_max_node_memory_saved_by_view / 1024.)), int(
round(max_node_memory_saved_by_view / 1024.)))
......
......@@ -10,9 +10,10 @@ http://www-users.cs.umn.edu/~saad/software/SPARSKIT/paper.ps
import sys
import numpy
import theano
from numpy.lib.stride_tricks import as_strided
import scipy.sparse
import theano
from theano import gof, tensor, compile, scalar, config
from theano.gof.python25 import all
from theano.gradient import DisconnectedType
......@@ -20,7 +21,6 @@ from theano.sparse.utils import hash_from_sparse
import theano.tests.unittest_tools as utt
from theano.gradient import grad_not_implemented, grad_undefined
from theano.sparse.type import SparseType, _is_sparse
from numpy.lib.stride_tricks import as_strided
sparse_formats = ['csc', 'csr']
......@@ -689,7 +689,7 @@ class CSM(gof.Op):
# node.inputs[3] is of lenght as we only support sparse matrix.
return [(node.inputs[3][0], node.inputs[3][1])]
else:
return node.fgraph.shape_feature.default_infer_shape(node, shapes)
raise theano.tensor.basic.ShapeError("case not implemented")
CSC = CSM('csc')
......
......@@ -1890,7 +1890,7 @@ class AdvancedSubtensor(Op):
else:
return [ind1shp]
# Default case, we don't know
return node.fgraph.shape_feature.default_infer_shape(node, ishapes)
raise theano.tensor.basic.ShapeError("case not implemented")
def perform(self, node, inputs, out_):
out, = out_
......
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