Python3 Support

[meawoppl]

This is mostly just an issue of print statements:

build/lib/neon/models/rnn.py:140:                if self.step_print > 0 and mb_id % self.step_print == 0:
build/lib/neon/models/rnn.py:502:            For text prediction, reassemble the batches and print out a short
build/lib/neon/models/mlp.py:121:            assert self.step_print != 0
build/lib/neon/models/mlp.py:165:                if self.step_print > 0 and mb_id % self.step_print == 0:
build/lib/neon/models/model.py:416:        # print results
build/lib/neon/data/convert_imageset_batches.py:42:        print "Converting ", ifname
build/lib/neon/data/questionanswer.py:91:        print 'Preparing bAbI dataset or extracting from %s' % path
build/lib/neon/data/questionanswer.py:92:        print 'Task is %s/%s' % (subset, task)
build/lib/neon/data/imagecaption.py:77:        print "Vocab size: %d, Max sentence length: %d" % (self.vocab_size,
build/lib/neon/data/imagecaption.py:102:        print 'Reading train images and sentences from %s' % self.path
build/lib/neon/data/imagecaption.py:248:        print "Writing output and reference sents to dir %s" % self.path
build/lib/neon/data/imagecaption.py:268:        print "Executing bleu eval script: ", bleu_command
build/lib/neon/data/imagecaption.py:307:        print 'Reading test images and sentences from %s' % self.path
build/lib/neon/data/dataiterator.py:151:            print bidx, train_set.start
build/lib/neon/data/imageloader.py:258:            print '****', epoch, master.start, master.idx, master.ndata
build/lib/neon/data/imageloader.py:259:            print t.get().argmax(axis=0)[:17]
build/lib/neon/util/update_dataset_cache.py:62:    print '%s updated to new format' % cache_file
build/lib/neon/util/trace.py:112:        Tracer.logger.debug(print_str)  # print print_str
build/lib/neon/diagnostics/timing_plots.py:199:    print out soumith benchmark numers
build/lib/neon/callbacks/callbacks.py:663:        tag (string): Label to print before the bar (i.e. Train, Valid, Test )
build/lib/neon/callbacks/callbacks.py:715:            # print the new line
build/lib/neon/optimizers/optimizer.py:187:            name (str, optional): the optimizer's layer's pretty-print name.
build/lib/neon/backends/backend.py:2159:        Pretty print of the optree
build/lib/neon/backends/autodiff.py:314:            # print 'created grad_tree cache'
build/lib/neon/backends/tests/test_autodiff_extra.py:234:            # print count
build/lib/neon/backends/tests/test_backend_conv_layer.py:221:        print op
build/lib/neon/backends/tests/test_sr.py:20:    print C_host
build/lib/neon/backends/tests/test_gpu_pool_layer.py:164:                        # print idx
build/lib/neon/backends/tests/test_backend_pool_layer.py:204:        print opA
build/lib/neon/backends/util/check_gpu.py:62:        print "Found GPU(s) with compute capability:", full_version
build/lib/neon/backends/util/check_gpu.py:93:        print "Found %d GPU(s)", count
build/lib/neon/backends/util/check_gpu.py:98:    print get_compute_capability(verbose=False)
build/lib/neon/backends/layer_gpu.py:504:        # for k in self.fprop_kernels: print k
build/lib/neon/backends/layer_gpu.py:505:        # for k in self.bprop_kernels: print k
build/lib/neon/backends/layer_gpu.py:539:            # print grid_P, grid_Q
build/lib/neon/backends/layer_gpu.py:561:        # for k in self.updat_kernels: print k
build/lib/neon/backends/test_lrn.py:86:    print "== denom =="
build/lib/neon/backends/test_lrn.py:87:    print "CPU fprop"
build/lib/neon/backends/test_lrn.py:88:    print cccD.get().reshape(C*D*H*W, N)[0:4, 0:4]
build/lib/neon/backends/test_lrn.py:89:    print "GPU fprop"
build/lib/neon/backends/test_lrn.py:90:    print devD.get().reshape(C*D*H*W, N)[0:4, 0:4]
build/lib/neon/backends/test_lrn.py:92:    print "== output =="
build/lib/neon/backends/test_lrn.py:93:    print "CPU fprop"
build/lib/neon/backends/test_lrn.py:94:    print cccO.get().reshape(C*D*H*W, N)[0:4, 0:4]
build/lib/neon/backends/test_lrn.py:95:    print "GPU fprop"
build/lib/neon/backends/test_lrn.py:96:    print devO.get().reshape(C*D*H*W, N)[0:4, 0:4]
build/lib/neon/backends/test_lrn.py:102:    print "== bprop =="
build/lib/neon/backends/test_lrn.py:103:    print "CPU bprop"
build/lib/neon/backends/test_lrn.py:104:    print cccB.get().reshape(C*D*H*W, N)[0:4, 0:4]
build/lib/neon/backends/test_lrn.py:105:    print "GPU bprop"
build/lib/neon/backends/test_lrn.py:106:    print devB.get().reshape(C*D*H*W, N)[0:4, 0:4]
build/lib/neon/backends/kernels/cuda/pooling.py:842:    # print >>f, code
build/lib/neon/backends/nervanagpu.py:129:            # print "allocate!"
build/lib/neon/backends/nervanagpu.py:621:            # print ('created memoize stack')
build/lib/neon/backends/nervanagpu.py:640:        bench (bool, optional): set to True to print out performance data for
build/lib/neon/backends/nervanagpu.py:2066:#     print caller
build/lib/neon/backends/convnet-benchmarks.py:40:# print more stuff
build/lib/neon/backends/make_kernels.py:40:             help="print output of nvcc calls.")
build/lib/neon/backends/make_kernels.py:121:        print "Missing sass file: %s for kernel: %s" % (sass_file, kernel_name)
build/lib/neon/backends/make_kernels.py:165:                print cmdline
build/lib/neon/backends/make_kernels.py:167:                print proc.stderr.read()
build/lib/neon/backends/make_kernels.py:173:                print output
build/lib/neon/backends/make_kernels.py:176:        print "%d kernels compiled." % len(kernels_made)
build/lib/neon/backends/float_ew.py:112:    print tree with indentation
build/lib/neon/backends/float_ew.py:116:        print ("    " * level) + ", ".join(str(s) for s in node[0:3])
build/lib/neon/backends/float_ew.py:122:        print ("    " * level) + str(node)
build/lib/neon/backends/float_ew.py:288:    #     print stage_data[0], stage
build/lib/neon/backends/float_ew.py:289:    #     for s in stage_data[1]: print s
build/lib/neon/backends/float_ew.py:598:    # print "Compiling %s" % template_vals["name"]
build/lib/neon/backends/float_ew.py:601:    # print >>f, code
build/lib/neon/backends/float_ew.py:901:    # for s in argsprint:   print s
build/lib/neon/backends/float_ew.py:902:    # for s in kernel_args: print s
build/lib/neon/backends/float_ew.py:903:    # for s in type_args:   print s
build/lib/neon/backends/float_ew.py:921:        # for a in kernel_args: print a
build/lib/neon/backends/float_ew.py:940:        #print reduce_shape
build/lib/neon/backends/float_ew.py:1198:    # print >>f, code
doc/source/autodiff.rst:29:    print ad.get_grad_asnumpyarray([x0, x1]) # result is [2 * x0 + x1, x0]
examples/cifar10_conv.py:74:print 'Misclassification error = %.1f%%' % (mlp.eval(test, metric=Misclassification())*100)
examples/babi/demo.py:71:print "\nThe vocabulary set from this task has {} words:".format(babi.vocab_size)
examples/babi/demo.py:72:print stitch_sentence(babi.vocab)
examples/babi/demo.py:73:print "\nExample from test set:"
examples/babi/demo.py:74:print "\nStory"
examples/babi/demo.py:75:print stitch_sentence(ex_story)
examples/babi/demo.py:76:print "Question"
examples/babi/demo.py:77:print stitch_sentence(ex_question)
examples/babi/demo.py:78:print "\nAnswer"
examples/babi/demo.py:79:print ex_answer
examples/babi/demo.py:105:    print "\nAnswer:"
examples/babi/demo.py:108:        print babi.index_to_word[idx], float(probs[idx])
examples/char_lstm.py:94:print 'Misclassification error = %.1f%%' % ((1-fraction_correct)*100)
examples/timeseries_lstm.py:30:    print 'matplotlib needs to be installed manually to generate plots needed for this example'
examples/timeseries_lstm.py:303:    print 'terr = %g, verr = %g' % (terr, verr)
examples/imdb_lstm.py:58:print "Vocab size - ", vocab_size
examples/imdb_lstm.py:59:print "Sentence Length - ", sentence_length
examples/imdb_lstm.py:60:print "# of train sentences", X_train.shape[0]
examples/imdb_lstm.py:61:print "# of test sentence", X_test.shape[0]
examples/imdb_lstm.py:90:print "Test  Accuracy - ", 100 * model.eval(valid_set, metric=Accuracy())
examples/imdb_lstm.py:91:print "Train Accuracy - ", 100 * model.eval(train_set, metric=Accuracy())
examples/text_generation_lstm.py:130:print ''.join(seed_tokens + text)
examples/conv_autoencoder.py:66:print mlp.layers.layers[-1]
examples/conv_autoencoder.py:82:    print 'matplotlib needs to be manually installed to generate plots'
neon/models/model.py:416:        # print results
neon/data/convert_imageset_batches.py:42:        print "Converting ", ifname
neon/data/questionanswer.py:91:        print 'Preparing bAbI dataset or extracting from %s' % path
neon/data/questionanswer.py:92:        print 'Task is %s/%s' % (subset, task)
neon/data/imagecaption.py:77:        print "Vocab size: %d, Max sentence length: %d" % (self.vocab_size,
neon/data/imagecaption.py:102:        print 'Reading train images and sentences from %s' % self.path
neon/data/imagecaption.py:248:        print "Writing output and reference sents to dir %s" % self.path
neon/data/imagecaption.py:268:        print "Executing bleu eval script: ", bleu_command
neon/data/imagecaption.py:307:        print 'Reading test images and sentences from %s' % self.path
neon/data/dataiterator.py:151:            print bidx, train_set.start
neon/data/imageloader.py:258:            print '****', epoch, master.start, master.idx, master.ndata
neon/data/imageloader.py:259:            print t.get().argmax(axis=0)[:17]
neon/util/update_dataset_cache.py:62:    print '%s updated to new format' % cache_file
neon/callbacks/callbacks.py:663:        tag (string): Label to print before the bar (i.e. Train, Valid, Test )
neon/callbacks/callbacks.py:715:            # print the new line
neon/optimizers/optimizer.py:187:            name (str, optional): the optimizer's layer's pretty-print name.
neon/backends/backend.py:2159:        Pretty print of the optree
neon/backends/autodiff.py:314:            # print 'created grad_tree cache'
neon/backends/tests/test_autodiff_extra.py:234:            # print count
neon/backends/tests/test_backend_conv_layer.py:221:        print op
neon/backends/tests/test_sr.py:20:    print C_host
neon/backends/tests/test_gpu_pool_layer.py:164:                        # print idx
neon/backends/tests/test_backend_pool_layer.py:204:        print opA
neon/backends/util/check_gpu.py:62:        print "Found GPU(s) with compute capability:", full_version
neon/backends/util/check_gpu.py:93:        print "Found %d GPU(s)", count
neon/backends/util/check_gpu.py:98:    print get_compute_capability(verbose=False)
neon/backends/layer_gpu.py:504:        # for k in self.fprop_kernels: print k
neon/backends/layer_gpu.py:505:        # for k in self.bprop_kernels: print k
neon/backends/layer_gpu.py:539:            # print grid_P, grid_Q
neon/backends/layer_gpu.py:561:        # for k in self.updat_kernels: print k
neon/backends/test_lrn.py:86:    print "== denom =="
neon/backends/test_lrn.py:87:    print "CPU fprop"
neon/backends/test_lrn.py:88:    print cccD.get().reshape(C*D*H*W, N)[0:4, 0:4]
neon/backends/test_lrn.py:89:    print "GPU fprop"
neon/backends/test_lrn.py:90:    print devD.get().reshape(C*D*H*W, N)[0:4, 0:4]
neon/backends/test_lrn.py:92:    print "== output =="
neon/backends/test_lrn.py:93:    print "CPU fprop"
neon/backends/test_lrn.py:94:    print cccO.get().reshape(C*D*H*W, N)[0:4, 0:4]
neon/backends/test_lrn.py:95:    print "GPU fprop"
neon/backends/test_lrn.py:96:    print devO.get().reshape(C*D*H*W, N)[0:4, 0:4]
neon/backends/test_lrn.py:102:    print "== bprop =="
neon/backends/test_lrn.py:103:    print "CPU bprop"
neon/backends/test_lrn.py:104:    print cccB.get().reshape(C*D*H*W, N)[0:4, 0:4]
neon/backends/test_lrn.py:105:    print "GPU bprop"
neon/backends/test_lrn.py:106:    print devB.get().reshape(C*D*H*W, N)[0:4, 0:4]
neon/backends/kernels/cuda/pooling.py:842:    # print >>f, code
neon/backends/nervanagpu.py:129:            # print "allocate!"
neon/backends/nervanagpu.py:621:            # print ('created memoize stack')
neon/backends/nervanagpu.py:640:        bench (bool, optional): set to True to print out performance data for
neon/backends/nervanagpu.py:2066:#     print caller
neon/backends/convnet-benchmarks.py:40:# print more stuff
neon/backends/make_kernels.py:40:             help="print output of nvcc calls.")
neon/backends/make_kernels.py:121:        print "Missing sass file: %s for kernel: %s" % (sass_file, kernel_name)
neon/backends/make_kernels.py:165:                print cmdline
neon/backends/make_kernels.py:167:                print proc.stderr.read()
neon/backends/make_kernels.py:173:                print output
neon/backends/make_kernels.py:176:        print "%d kernels compiled." % len(kernels_made)
neon/backends/float_ew.py:112:    print tree with indentation
neon/backends/float_ew.py:116:        print ("    " * level) + ", ".join(str(s) for s in node[0:3])
neon/backends/float_ew.py:122:        print ("    " * level) + str(node)
neon/backends/float_ew.py:288:    #     print stage_data[0], stage
neon/backends/float_ew.py:289:    #     for s in stage_data[1]: print s
neon/backends/float_ew.py:598:    # print "Compiling %s" % template_vals["name"]
neon/backends/float_ew.py:601:    # print >>f, code
neon/backends/float_ew.py:901:    # for s in argsprint:   print s
neon/backends/float_ew.py:902:    # for s in kernel_args: print s
neon/backends/float_ew.py:903:    # for s in type_args:   print s
neon/backends/float_ew.py:921:        # for a in kernel_args: print a
neon/backends/float_ew.py:940:        #print reduce_shape
neon/backends/float_ew.py:1198:    # print >>f, code
tests/test_schedule.py:40:        # print epoch, lr, lr2
tests/grad_funcs.py:51:    print 'epsilon, max diff'
tests/grad_funcs.py:63:        print '%e %e %e' % (epsilon, max_abs, max_rel)
tests/grad_funcs.py:64:    print 'Min max diff : %e at Pert. Mag. %e' % (min_max_diff, min_max_pert)
tests/grad_funcs.py:147:    print 'Worst case diff %e, vals grad: %e, bprop: %e' % (max_abs_err,
tests/grad_funcs.py:150:    print 'Worst case diff %e, vals grad: %e, bprop: %e' % (max_rel_err,
tests/test_dataset.py:36:            print X_batch.shape, y_batch.shape
tests/serialization_check.py:38:    print 'comparing pickle files %s and %s' % (fn1, fn2)
tests/serialization_check.py:66:            print 'worst case abs diff = %e' % worst_case
tests/serialization_check.py:70:            print 'worst case rel diff = %e' % worst_case
tests/serialization_check.py:166:        print 'test failed....'
tests/test_lookuptable.py:43:        print fargs
tests/test_misc.py:33:    print d_array2.get()
tests/test_misc.py:37:    print d_array2.get()
tests/test_misc.py:40:    print d_error.get()
tests/test_misc.py:42:    print d_error.get()
tests/test_mergebroadcast_layer.py:108:    print neon_layer.nested_str()
tests/test_mergebroadcast_layer.py:163:    print np.max(np.abs(difference))
tests/test_mergebroadcast_layer.py:165:    print "Beginning Back prop"
tests/test_mergebroadcast_layer.py:183:    print np.max(np.abs(difference))
tests/test_mergebroadcast_layer.py:209:    print neon_layer.nested_str()
tests/test_mergebroadcast_layer.py:274:    print np.max(np.abs(difference))
tests/test_mergebroadcast_layer.py:280:    print np.max(np.abs(difference))
tests/test_mergebroadcast_layer.py:282:    print "Beginning Back prop"
tests/test_mergebroadcast_layer.py:310:    print np.max(np.abs(difference))
tests/test_mergebroadcast_layer.py:321:    print np.max(np.abs(difference))
tests/test_recurrent.py:153:    print '====Verifying hidden states===='
tests/test_recurrent.py:154:    print allclose_with_out(rnn.outputs.get(),
tests/test_recurrent.py:158:    print 'fprop is verified'
tests/test_recurrent.py:160:    print '====Verifying update on W and b ===='
tests/test_recurrent.py:161:    print 'dWxh'
tests/test_recurrent.py:166:    print 'dWhh'
tests/test_recurrent.py:172:    print '====Verifying update on bias===='
tests/test_recurrent.py:173:    print 'db'
tests/test_recurrent.py:179:    print 'bprop is verified'
tests/test_recurrent.py:214:    print 'Perturb mag, max grad diff'
tests/test_recurrent.py:235:        print '%e, %e' % (pert_mag, dd)
tests/test_recurrent.py:243:    print 'Worst case error %e with perturbation %e' % (min_max_err, pert_mag)
tests/test_recurrent.py:244:    print 'Threshold %e' % (threshold)
tests/utils.py:45:    # if it fails print some stats
tests/utils.py:50:        print 'abs errors: %e [%e, %e] Abs Thresh = %e' \
tests/utils.py:53:        print 'worst case: %e %e' % (x.flat[amax], y.flat[amax])
tests/utils.py:55:        print 'rel errors: %e [%e, %e] Rel Thresh = %e' \
tests/utils.py:58:        print 'worst case: %e %e' % (x.flat[amax], y.flat[amax])
tests/test_gru.py:156:    print '====Verifying hidden states===='
tests/test_gru.py:157:    print allclose_with_out(gru.outputs.get(),
tests/test_gru.py:162:    print 'fprop is verified'
tests/test_gru.py:165:    print 'Making sure neon GRU match numpy GRU in bprop'
tests/test_gru.py:196:    # print '====Verifying hidden deltas ===='
tests/test_gru.py:197:    print '====Verifying r deltas ===='
tests/test_gru.py:203:    print '====Verifying z deltas ===='
tests/test_gru.py:209:    print '====Verifying hcan deltas ===='
tests/test_gru.py:215:    print '====Verifying update on W_input===='
tests/test_gru.py:216:    print 'dWxr'
tests/test_gru.py:221:    print 'dWxz'
tests/test_gru.py:226:    print 'dWxc'
tests/test_gru.py:232:    print '====Verifying update on W_recur===='
tests/test_gru.py:234:    print 'dWrr'
tests/test_gru.py:239:    print 'dWrz'
tests/test_gru.py:244:    print 'dWrc'
tests/test_gru.py:250:    print '====Verifying update on bias===='
tests/test_gru.py:251:    print 'dbr'
tests/test_gru.py:256:    print 'dbz'
tests/test_gru.py:261:    print 'dbc'
tests/test_gru.py:267:    print 'bprop is verified'
tests/test_gru.py:302:    print 'Perturb mag, max grad diff'
tests/test_gru.py:323:        print '%e, %e' % (pert_mag, dd)
tests/test_gru.py:331:    print 'Worst case error %e with perturbation %e' % (min_max_err, pert_mag)
tests/test_gru.py:332:    print 'Threshold %e' % (threshold)
tests/lstm_ref.py:252:    print 'Making sure batched version agrees with sequential version: (should all be True)'
tests/lstm_ref.py:253:    print np.allclose(BdX, dX)
tests/lstm_ref.py:254:    print np.allclose(BdWLSTM, dWLSTM)
tests/lstm_ref.py:255:    print np.allclose(Bdc0, dc0)
tests/lstm_ref.py:256:    print np.allclose(Bdh0, dh0)
tests/lstm_ref.py:319:            # print stats
tests/lstm_ref.py:329:    print 'every line should start with OK. Have a nice day!'
tests/test_branch_layer.py:125:    print difference
tests/test_lstm.py:140:    print '====Verifying IFOG===='
tests/test_lstm.py:146:    print '====Verifying cell states===='
tests/test_lstm.py:152:    print '====Verifying hidden states===='
tests/test_lstm.py:158:    print 'fprop is verified'
tests/test_lstm.py:179:    print 'Making sure neon LSTM match numpy LSTM in bprop'
tests/test_lstm.py:180:    print '====Verifying update on W_recur===='
tests/test_lstm.py:187:    print '====Verifying update on W_input===='
tests/test_lstm.py:193:    print '====Verifying update on bias===='
tests/test_lstm.py:199:    print '====Verifying output delta===='
tests/test_lstm.py:205:    print 'bprop is verified'
tests/test_lstm.py:310:    print 'Perturb mag, max grad diff'
tests/test_lstm.py:331:        print '%e, %e' % (pert_mag, dd)
tests/test_lstm.py:339:    print 'Worst case error %e with perturbation %e' % (min_max_err, pert_mag)
tests/test_lstm.py:340:    print 'Threshold %e' % (threshold)
tests/test_conv_layer.py:262:    print 'atol on bprop dW = %e' % atol

Do you accept PR's toward python3 compatibility?

[scttl]

Yes, please see our response in #191 (closing this as a duplicate)