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Use six library to ensure pycaffe.py python3 compliance #3716

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Merged
longjon merged 1 commit into from
Mar 3, 2016
Merged

Use six library to ensure pycaffe.py python3 compliance #3716

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22 changes: 12 additions & 10 deletions python/caffe/pycaffe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,8 @@
RMSPropSolver, AdaDeltaSolver, AdamSolver
import caffe.io

import six

# We directly update methods from Net here (rather than using composition or
# inheritance) so that nets created by caffe (e.g., by SGDSolver) will
# automatically have the improved interface.
Expand Down Expand Up @@ -97,7 +99,7 @@ def _Net_forward(self, blobs=None, start=None, end=None, **kwargs):
raise Exception('Input blob arguments do not match net inputs.')
# Set input according to defined shapes and make arrays single and
# C-contiguous as Caffe expects.
for in_, blob in kwargs.iteritems():
for in_, blob in six.iteritems(kwargs):
if blob.shape[0] != self.blobs[in_].shape[0]:
raise Exception('Input is not batch sized')
self.blobs[in_].data[...] = blob
Expand Down Expand Up @@ -145,7 +147,7 @@ def _Net_backward(self, diffs=None, start=None, end=None, **kwargs):
raise Exception('Top diff arguments do not match net outputs.')
# Set top diffs according to defined shapes and make arrays single and
# C-contiguous as Caffe expects.
for top, diff in kwargs.iteritems():
for top, diff in six.iteritems(kwargs):
if diff.shape[0] != self.blobs[top].shape[0]:
raise Exception('Diff is not batch sized')
self.blobs[top].diff[...] = diff
Expand Down Expand Up @@ -174,13 +176,13 @@ def _Net_forward_all(self, blobs=None, **kwargs):
all_outs = {out: [] for out in set(self.outputs + (blobs or []))}
for batch in self._batch(kwargs):
outs = self.forward(blobs=blobs, **batch)
for out, out_blob in outs.iteritems():
for out, out_blob in six.iteritems(outs):
all_outs[out].extend(out_blob.copy())
# Package in ndarray.
for out in all_outs:
all_outs[out] = np.asarray(all_outs[out])
# Discard padding.
pad = len(all_outs.itervalues().next()) - len(kwargs.itervalues().next())
pad = len(six.next(six.itervalues(all_outs))) - len(six.next(six.itervalues(kwargs)))
if pad:
for out in all_outs:
all_outs[out] = all_outs[out][:-pad]
Expand Down Expand Up @@ -215,16 +217,16 @@ def _Net_forward_backward_all(self, blobs=None, diffs=None, **kwargs):
for fb, bb in izip_longest(forward_batches, backward_batches, fillvalue={}):
batch_blobs = self.forward(blobs=blobs, **fb)
batch_diffs = self.backward(diffs=diffs, **bb)
for out, out_blobs in batch_blobs.iteritems():
for out, out_blobs in six.iteritems(batch_blobs):
all_outs[out].extend(out_blobs.copy())
for diff, out_diffs in batch_diffs.iteritems():
for diff, out_diffs in six.iteritems(batch_diffs):
all_diffs[diff].extend(out_diffs.copy())
# Package in ndarray.
for out, diff in zip(all_outs, all_diffs):
all_outs[out] = np.asarray(all_outs[out])
all_diffs[diff] = np.asarray(all_diffs[diff])
# Discard padding at the end and package in ndarray.
pad = len(all_outs.itervalues().next()) - len(kwargs.itervalues().next())
pad = len(six.next(six.itervalues(all_outs))) - len(six.next(six.itervalues(kwargs)))
if pad:
for out, diff in zip(all_outs, all_diffs):
all_outs[out] = all_outs[out][:-pad]
Expand Down Expand Up @@ -256,10 +258,10 @@ def _Net_batch(self, blobs):
------
batch: {blob name: list of blobs} dict for a single batch.
"""
num = len(blobs.itervalues().next())
batch_size = self.blobs.itervalues().next().shape[0]
num = len(six.next(six.itervalues(blobs)))
batch_size = six.next(six.itervalues(self.blobs)).shape[0]
remainder = num % batch_size
num_batches = num / batch_size
num_batches = num // batch_size

# Yield full batches.
for b in range(num_batches):
Expand Down