Fix imports

scheme/constraint/amr.py

@@ -1,4 +1,4 @@
-from util.amr import *
+from scheme.util.amr import *
 
 
 class Constraints(constraints.Constraints):

scheme/conversion/amr.py

@@ -1,9 +1,8 @@
-from collections import defaultdict, namedtuple, OrderedDict
-
 import penman
+from collections import defaultdict, namedtuple, OrderedDict
 from ucca import layer0, layer1, convert
 
-from util.amr import *
+from scheme.util.amr import *
 
 DELETE_PATTERN = re.compile("\\\\|(?<=(?<!<)<)[^<>]+(?=>(?!>))")  # Delete text inside single angle brackets
 

scheme/convert.py

@@ -2,14 +2,15 @@
 
 import argparse
 import glob
-import os
-import re
 import sys
 
-from conversion.amr import CONVERTERS
+import os
+import re
 from ucca.convert import split2sentences
 from ucca.ioutil import passage2file, file2passage
 
+from scheme.conversion.amr import CONVERTERS
+
 desc = """Parses files in the specified format, and writes as the specified format.
 Each passage is written to the file: <outdir>/<prefix><passage_id>.<extension> """
 

scheme/convert_and_evaluate.py

@@ -2,14 +2,15 @@
 
 import argparse
 import glob
-import os
 import sys
 
-from conversion.amr import from_amr, to_amr
-from evaluation.amr import evaluate, Scores
-from tupa.config import VAction
+import os
 from ucca.ioutil import passage2file
 
+from scheme.conversion.amr import from_amr, to_amr
+from scheme.evaluation.amr import evaluate, Scores
+from tupa.config import VAction
+
 desc = """Parses files in AMR format, converts to UCCA standard format,
 converts back to the original format and evaluates using smatch.
 """

scheme/evaluate.py

@@ -2,7 +2,7 @@
 
 import argparse
 
-from evaluation.amr import evaluate
+from scheme.evaluation.amr import evaluate
 from tupa.config import VAction
 
 desc = """Parses files in AMR format, and evaluates using smatch.

scheme/evaluation/amr.py

@@ -1,6 +1,6 @@
 import sys
 
-from util.amr import *
+from scheme.util.amr import *
 
 sys.path.insert(0, os.path.dirname(importlib.util.find_spec("smatch.smatch").origin))  # to find amr.py from smatch
 from smatch import smatch

scheme/split.py

@@ -1,10 +1,9 @@
 #!/usr/bin/env python3
 import argparse
-import sys
-
 import glob
+import sys
 
-from util.amr import *
+from scheme.util.amr import *
 
 desc = """Split AMRs to separate files (important for shuffling before training the parser)"""
 

setup.py

@@ -87,6 +87,6 @@ def run(self):
           "src": os.path.join("scheme", "amr", "src"),
           "smatch": os.path.join("scheme", "smatch"),
       },
-      package_data={"src": ["amr.peg"], "util": ["resources/*.txt"]},
+      package_data={"src": ["amr.peg"], "scheme.util": ["resources/*.txt"]},
       cmdclass={"install": install},
       )

tests/test_amr.py

@@ -2,10 +2,11 @@
 
 import unittest
 
-from conversion.amr import from_amr, to_amr
-from evaluation.amr import evaluate
 from ucca.convert import split2sentences
 
+from scheme.conversion.amr import from_amr, to_amr
+from scheme.evaluation.amr import evaluate
+
 
 class ConversionTests(unittest.TestCase):
     """Tests conversion module correctness and API."""

tests/test_parser.py

@@ -2,12 +2,13 @@
 
 import unittest
 
-from states.state import State
+from ucca import convert, evaluation, ioutil
+
 from tupa.action import Actions
 from tupa.config import Config, SPARSE, MLP_NN, BILSTM_NN, NOOP
 from tupa.oracle import Oracle
 from tupa.parse import Parser
-from ucca import convert, evaluation, ioutil
+from tupa.states.state import State
 
 NUM_PASSAGES = 2
 

tupa/action.py

@@ -1,4 +1,4 @@
-from tupa.config import Config, COMPOUND
+from .config import Config, COMPOUND
 
 
 class Action(object):

tupa/classifiers/linear/perceptron.py

@@ -1,6 +1,6 @@
 import time
 
-from classifiers.classifier import Classifier, ClassifierProperty
+from tupa.classifiers.classifier import Classifier, ClassifierProperty
 
 
 class Perceptron(Classifier):

tupa/classifiers/linear/sparse_perceptron.py

@@ -1,9 +1,8 @@
-from collections import defaultdict
-
 import numpy as np
+from collections import defaultdict
 
-from linear.perceptron import Perceptron
 from tupa.config import Config, SPARSE
+from .perceptron import Perceptron
 
 
 class FeatureWeights(object):

tupa/classifiers/nn/bilstm.py

@@ -1,9 +1,9 @@
 import dynet as dy
 
-from classifiers.classifier import ClassifierProperty
-from features.feature_params import MISSING_VALUE
-from nn.neural_network import NeuralNetwork
+from tupa.classifiers.classifier import ClassifierProperty
 from tupa.config import Config, BILSTM_NN
+from tupa.features.feature_params import MISSING_VALUE
+from .neural_network import NeuralNetwork
 
 
 class BiLSTM(NeuralNetwork):

tupa/classifiers/nn/feedforward.py

@@ -1,5 +1,5 @@
-from nn.neural_network import NeuralNetwork
 from tupa.config import MLP_NN
+from .neural_network import NeuralNetwork
 
 
 class MLP(NeuralNetwork):

tupa/classifiers/nn/neural_network.py

@@ -1,15 +1,15 @@
-import os
 import sys
 import time
-from collections import OrderedDict
 
 import dynet as dy
 import numpy as np
+import os
+from collections import OrderedDict
 
-from classifiers.classifier import Classifier
-from classifiers.classifier import ClassifierProperty
-from features.feature_params import MISSING_VALUE
+from tupa.classifiers.classifier import Classifier
+from tupa.classifiers.classifier import ClassifierProperty
 from tupa.config import Config
+from tupa.features.feature_params import MISSING_VALUE
 
 TRAINERS = {
     "sgd": (dy.SimpleSGDTrainer, "e0"),

tupa/classifiers/noop.py

@@ -1,7 +1,7 @@
 import numpy as np
 
-from classifiers.classifier import Classifier
 from tupa.config import NOOP
+from .classifier import Classifier
 
 
 class NoOp(Classifier):

tupa/config.py

@@ -3,10 +3,10 @@
 import sys
 
 import numpy as np
-from conversion.amr import CONVERTERS
 from ucca import evaluation, constructions
 
-from tupa import constraints
+from scheme.conversion.amr import CONVERTERS
+from . import constraints
 
 
 class Singleton(type):
@@ -181,8 +181,8 @@ def __init__(self, *args):
                 self.args.max_node_labels = 1000
             self.args.max_action_labels = max(self.args.max_action_labels, 600)
             self.args.max_edge_labels = max(self.args.max_edge_labels, 500)
-            from evaluation.amr import evaluate, Scores, LABEL_ATTRIB, UNKNOWN_LABEL
-            from constraint.amr import Constraints
+            from scheme.evaluation.amr import evaluate, Scores, LABEL_ATTRIB, UNKNOWN_LABEL
+            from scheme.constraint.amr import Constraints
             self.evaluate, self.Scores = evaluate, Scores
             self.args.node_label_attrib = LABEL_ATTRIB
             self.args.unknown_label = UNKNOWN_LABEL

tupa/features/dense_features.py

@@ -1,5 +1,5 @@
-from features.feature_extractor import FeatureExtractor
-from features.feature_params import MISSING_VALUE
+from .feature_extractor import FeatureExtractor
+from .feature_params import MISSING_VALUE
 
 NON_NUMERIC_FEATURE_SUFFIXES = "wtdenpAT"
 FEATURE_TEMPLATES = (

tupa/features/empty_features.py

@@ -1,4 +1,4 @@
-from features.feature_extractor import FeatureExtractor
+from .feature_extractor import FeatureExtractor
 
 
 class EmptyFeatureExtractor(FeatureExtractor):

tupa/features/enumerator.py

@@ -1,9 +1,9 @@
 import numpy as np
 
-from features.feature_extractor_wrapper import FeatureExtractorWrapper
-from features.feature_params import MISSING_VALUE
-from features.feature_params import NumericFeatureParameters
 from tupa.model_util import DropoutDict
+from .feature_extractor_wrapper import FeatureExtractorWrapper
+from .feature_params import MISSING_VALUE
+from .feature_params import NumericFeatureParameters
 
 
 class FeatureEnumerator(FeatureExtractorWrapper):

tupa/features/feature_extractor_wrapper.py

@@ -1,8 +1,9 @@
-from features.feature_extractor import FeatureExtractor
-from features.feature_params import copy_params, NumericFeatureParameters
-from tupa.model_util import load_dict, save_dict, UnknownDict
 from ucca.textutil import get_word_vectors
 
+from tupa.model_util import load_dict, save_dict, UnknownDict
+from .feature_extractor import FeatureExtractor
+from .feature_params import copy_params, NumericFeatureParameters
+
 
 class FeatureExtractorWrapper(FeatureExtractor):
     def __init__(self, feature_extractor, params):

tupa/features/indexer.py

@@ -1,4 +1,4 @@
-from features.feature_extractor_wrapper import FeatureExtractorWrapper
+from .feature_extractor_wrapper import FeatureExtractorWrapper
 
 INDEXED_FEATURES = "W", "w", "t", "d", "T"  # external word embeddings, learned word embeddings, POS tags, dep rels, entity type
 

tupa/features/sparse_features.py

@@ -1,4 +1,4 @@
-from features.feature_extractor import FeatureExtractor
+from .feature_extractor import FeatureExtractor
 
 FEATURE_TEMPLATES = (
     # unigrams (Zhang and Clark 2009):

tupa/model.py

@@ -1,9 +1,9 @@
-from features.enumerator import FeatureEnumerator
-from features.feature_params import FeatureParameters
-from features.indexer import FeatureIndexer
-from tupa.action import Actions
-from tupa.config import Config, SPARSE, MLP_NN, BILSTM_NN, NOOP
-from tupa.model_util import UnknownDict
+from .action import Actions
+from .config import Config, SPARSE, MLP_NN, BILSTM_NN, NOOP
+from .features.enumerator import FeatureEnumerator
+from .features.feature_params import FeatureParameters
+from .features.indexer import FeatureIndexer
+from .model_util import UnknownDict
 
 ACTION_AXIS = 0
 LABEL_AXIS = 1
@@ -48,23 +48,23 @@ def __init__(self, model_type, filename, feature_extractor=None, model=None):
             max_values.append(Config().args.max_node_labels)
 
         if model_type == SPARSE:
-            from features.sparse_features import SparseFeatureExtractor
-            from linear.sparse_perceptron import SparsePerceptron
+            from .features.sparse_features import SparseFeatureExtractor
+            from .classifiers.linear.sparse_perceptron import SparsePerceptron
             self.feature_extractor = SparseFeatureExtractor()
             self.model = SparsePerceptron(filename, values)
         elif model_type == MLP_NN:
-            from nn.feedforward import MLP
-            from features.dense_features import DenseFeatureExtractor
+            from .classifiers.nn.feedforward import MLP
+            from .features.dense_features import DenseFeatureExtractor
             self.feature_extractor = FeatureEnumerator(DenseFeatureExtractor(), self.feature_params)
             self.model = MLP(filename, values, self.feature_extractor.params, max_num_labels=max_values)
         elif model_type == BILSTM_NN:
-            from nn.bilstm import BiLSTM
-            from features.dense_features import DenseFeatureExtractor
+            from .classifiers.nn.bilstm import BiLSTM
+            from .features.dense_features import DenseFeatureExtractor
             self.feature_extractor = FeatureIndexer(FeatureEnumerator(DenseFeatureExtractor(), self.feature_params))
             self.model = BiLSTM(filename, values, self.feature_extractor.params, max_num_labels=max_values)
         elif model_type == NOOP:
-            from features.empty_features import EmptyFeatureExtractor
-            from classifiers.noop import NoOp
+            from .features.empty_features import EmptyFeatureExtractor
+            from .classifiers.noop import NoOp
             self.feature_extractor = EmptyFeatureExtractor()
             self.model = NoOp(filename, values)
         else:

tupa/model_util.py

@@ -1,13 +1,13 @@
-import os
 import pickle
 import pprint as pp
 import sys
 import time
-from collections import OrderedDict, Counter
 
 import numpy as np
+import os
+from collections import OrderedDict, Counter
 
-from features.feature_params import UNKNOWN_VALUE
+from .features.feature_params import UNKNOWN_VALUE
 
 
 class DefaultOrderedDict(OrderedDict):

tupa/oracle.py

@@ -1,8 +1,9 @@
-from states.state import InvalidActionError
-from tupa.action import Actions
-from tupa.config import Config, COMPOUND
 from ucca import layer1
 
+from .action import Actions
+from .config import Config, COMPOUND
+from .states.state import InvalidActionError
+
 # Constants for readability, used by Oracle.action
 RIGHT = PARENT = NODE = 0
 LEFT = CHILD = EDGE = 1

tupa/parse.py

@@ -1,15 +1,16 @@
-import os
 import time
-from collections import defaultdict
 from enum import Enum
 
-from classifiers.classifier import ClassifierProperty
-from states.state import State
+import os
+from collections import defaultdict
+from ucca import diffutil, ioutil, textutil, layer1
+from ucca.convert import FROM_FORMAT, TO_FORMAT, from_text, to_text
+
+from tupa.classifiers.classifier import ClassifierProperty
 from tupa.config import Config
 from tupa.model import Model, ACTION_AXIS, LABEL_AXIS
 from tupa.oracle import Oracle
-from ucca import diffutil, ioutil, textutil, layer1
-from ucca.convert import FROM_FORMAT, TO_FORMAT, from_text, to_text
+from tupa.states.state import State
 
 
 class ParserException(Exception):

tupa/states/node.py

@@ -1,10 +1,10 @@
 from collections import deque
 from operator import attrgetter
-
-from tupa.config import Config
 from ucca import core, layer0
 from ucca.layer1 import EdgeTags
 
+from tupa.config import Config
+
 
 class Node(object):
     """