Merge pull request #773 from ufal/model_refactor

Model refactor

Author: jlibovicky

.pylintrc

@@ -345,7 +345,7 @@ max-branches=12
 max-statements=50
 
 # Maximum number of parents for a class (see R0901).
-max-parents=7
+max-parents=10
 
 # Maximum number of attributes for a class (see R0902).
 max-attributes=12

neuralmonkey/attention/base_attention.py

@@ -41,9 +41,10 @@
 
 import tensorflow as tf
 
-from neuralmonkey.model.stateful import TemporalStateful, SpatialStateful
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
 from neuralmonkey.attention.namedtuples import AttentionLoopState
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.stateful import TemporalStateful, SpatialStateful
 
 # pylint: disable=invalid-name
 Attendable = Union[TemporalStateful, SpatialStateful]

neuralmonkey/attention/combination.py

@@ -23,7 +23,8 @@
     get_attention_states, get_attention_mask, Attendable)
 from neuralmonkey.attention.namedtuples import HierarchicalLoopState
 from neuralmonkey.checking import assert_shape
-from neuralmonkey.model.model_part import InitializerSpecs, ModelPart
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
 from neuralmonkey.tf_utils import get_variable
 
 

neuralmonkey/attention/coverage.py

@@ -10,7 +10,8 @@
 
 from neuralmonkey.attention.base_attention import Attendable
 from neuralmonkey.attention.feed_forward import Attention
-from neuralmonkey.model.model_part import InitializerSpecs, ModelPart
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
 
 
 class CoverageAttention(Attention):

neuralmonkey/attention/feed_forward.py

@@ -13,9 +13,10 @@
     BaseAttention, AttentionLoopState, empty_attention_loop_state,
     get_attention_states, get_attention_mask, Attendable)
 from neuralmonkey.decorators import tensor
-from neuralmonkey.nn.utils import dropout
 from neuralmonkey.logging import log
-from neuralmonkey.model.model_part import InitializerSpecs, ModelPart
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.nn.utils import dropout
 from neuralmonkey.tf_utils import get_variable
 
 

neuralmonkey/attention/scaled_dot_product.py

@@ -13,7 +13,8 @@
 from typeguard import check_argument_types
 
 from neuralmonkey.nn.utils import dropout
-from neuralmonkey.model.model_part import InitializerSpecs, ModelPart
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
 from neuralmonkey.attention.base_attention import (
     BaseAttention, Attendable, get_attention_states, get_attention_mask)
 from neuralmonkey.attention.namedtuples import MultiHeadLoopState

neuralmonkey/attention/stateful_context.py

@@ -7,7 +7,8 @@
     BaseAttention, AttentionLoopState, empty_attention_loop_state)
 from neuralmonkey.model.stateful import Stateful
 from neuralmonkey.decorators import tensor
-from neuralmonkey.model.model_part import InitializerSpecs, ModelPart
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
 
 
 class StatefulContext(BaseAttention):

neuralmonkey/checking.py

@@ -24,7 +24,7 @@ def check_dataset_and_coders(dataset: Dataset,
 
     data_list = []
     for runner in runners:
-        for c in runner.all_coders:
+        for c in runner.feedables:
             if hasattr(c, "data_id"):
                 data_list.append((getattr(c, "data_id"), c))
             elif hasattr(c, "data_ids"):
@@ -53,7 +53,7 @@ def check_dataset_and_coders(dataset: Dataset,
             missing.append((coder, serie))
 
     if missing:
-        formated = ["{} ({}, {}.{})" .format(serie, cod.name,
+        formated = ["{} ({}, {}.{})" .format(serie, str(cod),
                                              cod.__class__.__module__,
                                              cod.__class__.__name__)
                     for cod, serie in missing]

neuralmonkey/decoders/autoregressive.py

@@ -12,7 +12,9 @@
 
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.decorators import tensor
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.logging import log, warn
 from neuralmonkey.model.sequence import EmbeddedSequence
 from neuralmonkey.nn.utils import dropout

neuralmonkey/decoders/classifier.py

@@ -5,7 +5,9 @@
 
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.vocabulary import Vocabulary
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import Stateful
 from neuralmonkey.nn.mlp import MultilayerPerceptron
 from neuralmonkey.decorators import tensor

neuralmonkey/decoders/ctc_decoder.py

@@ -7,7 +7,9 @@
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.decorators import tensor
 from neuralmonkey.logging import log
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import TemporalStateful
 from neuralmonkey.tf_utils import get_variable
 from neuralmonkey.vocabulary import Vocabulary, END_TOKEN

neuralmonkey/decoders/decoder.py

@@ -10,7 +10,8 @@
     Vocabulary, END_TOKEN_INDEX, PAD_TOKEN_INDEX)
 from neuralmonkey.model.sequence import EmbeddedSequence
 from neuralmonkey.model.stateful import Stateful
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.logging import log
 from neuralmonkey.nn.ortho_gru_cell import OrthoGRUCell, NematusGRUCell
 from neuralmonkey.nn.utils import dropout

neuralmonkey/decoders/sequence_labeler.py

@@ -4,7 +4,9 @@
 from typeguard import check_argument_types
 
 from neuralmonkey.dataset import Dataset
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.encoders.recurrent import RecurrentEncoder
 from neuralmonkey.encoders.facebook_conv import SentenceEncoder
 from neuralmonkey.vocabulary import Vocabulary

neuralmonkey/decoders/sequence_regressor.py

@@ -5,7 +5,9 @@
 
 from neuralmonkey.nn.projection import multilayer_projection
 from neuralmonkey.dataset import Dataset
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import Stateful
 from neuralmonkey.decorators import tensor
 

neuralmonkey/decoders/transformer.py

@@ -20,9 +20,10 @@
     AutoregressiveDecoder, LoopState, DecoderFeedables)
 from neuralmonkey.encoders.transformer import (
     TransformerLayer, position_signal)
-from neuralmonkey.model.sequence import EmbeddedSequence
 from neuralmonkey.logging import log, warn
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
+from neuralmonkey.model.sequence import EmbeddedSequence
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.nn.utils import dropout
 from neuralmonkey.vocabulary import (
     Vocabulary, PAD_TOKEN_INDEX, END_TOKEN_INDEX)

neuralmonkey/decoders/word_alignment_decoder.py

@@ -8,7 +8,9 @@
 from neuralmonkey.encoders.recurrent import RecurrentEncoder
 from neuralmonkey.decoders.decoder import Decoder
 from neuralmonkey.logging import warn
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.sequence import Sequence
 from neuralmonkey.decorators import tensor
 

neuralmonkey/encoders/attentive.py

@@ -1,10 +1,9 @@
-from typing import Set, cast
-
 import tensorflow as tf
 from typeguard import check_argument_types
 
 from neuralmonkey.model.stateful import TemporalStatefulWithOutput
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.nn.utils import dropout
 from neuralmonkey.decorators import tensor
 from neuralmonkey.attention.base_attention import (
@@ -102,13 +101,3 @@ def output(self) -> tf.Tensor:
                                      name="output_projection")
 
         return output
-
-    def get_dependencies(self) -> Set[ModelPart]:
-        deps = ModelPart.get_dependencies(self)
-
-        # feed only if needed
-        if isinstance(self.input_sequence, ModelPart):
-            feedable = cast(ModelPart, self.input_sequence)
-            deps |= feedable.get_dependencies()
-
-        return deps

neuralmonkey/encoders/cnn_encoder.py

@@ -1,14 +1,16 @@
 """CNN for image processing."""
 
-from typing import cast, Callable, List, Tuple, Set, Union
+from typing import cast, Callable, List, Tuple, Union
 from typeguard import check_argument_types
 
 import numpy as np
 import tensorflow as tf
 
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.decorators import tensor
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import (SpatialStatefulWithOutput,
                                          TemporalStatefulWithOutput)
 from neuralmonkey.nn.projection import multilayer_projection
@@ -349,6 +351,6 @@ def temporal_mask(self) -> tf.Tensor:
         summed = tf.reduce_sum(mask, axis=1)
         return tf.to_float(tf.greater(summed, 0))
 
-    def get_dependencies(self) -> Set["ModelPart"]:
-        """Collect recusively all encoders and decoders."""
-        return self._cnn.get_dependencies().union([self])
+    @property
+    def dependencies(self) -> List[str]:
+        return super().dependencies + ["_cnn"]

neuralmonkey/encoders/facebook_conv.py

@@ -7,12 +7,13 @@
 import numpy as np
 from typeguard import check_argument_types
 
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
-from neuralmonkey.logging import log
 from neuralmonkey.decorators import tensor
-from neuralmonkey.nn.projection import glu
+from neuralmonkey.logging import log
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
 from neuralmonkey.model.sequence import EmbeddedSequence
 from neuralmonkey.model.stateful import TemporalStatefulWithOutput
+from neuralmonkey.nn.projection import glu
 from neuralmonkey.tf_utils import get_variable
 
 

neuralmonkey/encoders/imagenet_encoder.py

@@ -15,7 +15,9 @@
 
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.decorators import tensor
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.model_part import ModelPart
+from neuralmonkey.model.parameterized import InitializerSpecs
 from neuralmonkey.model.stateful import SpatialStatefulWithOutput
 
 

neuralmonkey/encoders/numpy_stateful_filler.py

@@ -5,7 +5,9 @@
 
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.decorators import tensor
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import Stateful, SpatialStatefulWithOutput
 
 

neuralmonkey/encoders/pooling.py

@@ -1,14 +1,14 @@
-from typing import Set, cast
-
 import tensorflow as tf
 from typeguard import check_argument_types
 
 from neuralmonkey.model.stateful import Stateful, TemporalStateful
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.decorators import tensor
 
 
 # pylint: disable=abstract-method
+# Pylint bug: https://github.com/PyCQA/pylint/issues/179
 class SequencePooling(ModelPart, Stateful):
     """An abstract pooling layer over a sequence."""
 
@@ -31,16 +31,6 @@ def __init__(self,
                 self.input_sequence.temporal_mask, -1)
             self._masked_input = (
                 self.input_sequence.temporal_states * self._input_mask)
-
-    def get_dependencies(self) -> Set[ModelPart]:
-        deps = ModelPart.get_dependencies(self)
-
-        # feed only if needed
-        if isinstance(self.input_sequence, ModelPart):
-            feedable = cast(ModelPart, self.input_sequence)
-            deps |= feedable.get_dependencies()
-
-        return deps
 # pylint: enable=abstract-method
 
 

neuralmonkey/encoders/raw_rnn_encoder.py

@@ -8,7 +8,9 @@
 from neuralmonkey.encoders.recurrent import (
     RNNSpecTuple, _make_rnn_spec, _make_rnn_cell)
 # pylint: enable=protected-access
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import TemporalStatefulWithOutput
 from neuralmonkey.logging import log
 from neuralmonkey.nn.utils import dropout

neuralmonkey/encoders/recurrent.py

@@ -1,11 +1,12 @@
-from typing import Tuple, List, Union, Callable, cast, Set, NamedTuple
+from typing import Tuple, List, Union, Callable, NamedTuple
 
 import tensorflow as tf
 from typeguard import check_argument_types
 
 from neuralmonkey.model.stateful import (
     TemporalStatefulWithOutput, TemporalStateful)
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.logging import warn
 from neuralmonkey.nn.ortho_gru_cell import OrthoGRUCell, NematusGRUCell
 from neuralmonkey.nn.utils import dropout
@@ -194,16 +195,6 @@ def output(self) -> tf.Tensor:
         return self.rnn[1]
         # pylint: enable=unsubscriptable-object
 
-    def get_dependencies(self) -> Set[ModelPart]:
-        """Collect recusively all encoders and decoders."""
-        deps = ModelPart.get_dependencies(self)
-
-        # feed only if needed
-        if isinstance(self.input_sequence, ModelPart):
-            feedable = cast(ModelPart, self.input_sequence)
-            deps = deps.union(feedable.get_dependencies())
-        return deps
-
 
 class SentenceEncoder(RecurrentEncoder):
     # pylint: disable=too-many-arguments,too-many-locals

neuralmonkey/encoders/sentence_cnn_encoder.py

@@ -6,7 +6,8 @@
 from typeguard import check_argument_types
 
 from neuralmonkey.encoders.recurrent import RNNCellTuple
-from neuralmonkey.model.model_part import ModelPart, InitializerSpecs
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.sequence import Sequence
 from neuralmonkey.model.stateful import TemporalStatefulWithOutput
 from neuralmonkey.nn.noisy_gru_cell import NoisyGRUCell

neuralmonkey/encoders/sequence_cnn_encoder.py

@@ -7,7 +7,9 @@
 
 from neuralmonkey.dataset import Dataset
 from neuralmonkey.decorators import tensor
-from neuralmonkey.model.model_part import ModelPart, FeedDict, InitializerSpecs
+from neuralmonkey.model.feedable import FeedDict
+from neuralmonkey.model.parameterized import InitializerSpecs
+from neuralmonkey.model.model_part import ModelPart
 from neuralmonkey.model.stateful import Stateful
 from neuralmonkey.nn.utils import dropout
 from neuralmonkey.vocabulary import Vocabulary