moved dialog specific axesc andctypes to nlp/neural_types.py, refacto…

…red the modules

Signed-off-by: nvidia <tkornuta@nvidia.com>

nemo/collections/nlp/__init__.py

@@ -14,7 +14,5 @@
 # limitations under the License.
 # =============================================================================
 
-import nemo
 from nemo.collections.nlp import callbacks, data, nm, utils
-
-backend = nemo.core.Backend.PyTorch
+from nemo.collections.nlp.neural_types import *

nemo/collections/nlp/neural_types.py

@@ -0,0 +1,73 @@
+# ! /usr/bin/python
+# -*- coding: utf-8 -*-
+
+# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from nemo.core.neural_types import AxisKindAbstract, ElementType, StringType
+
+__all__ = [
+    'DialogAxisKind',
+    'Utterance',
+    'UserUtterance',
+    'SystemUtterance',
+    'AgentUtterance',
+    'SlotValue',
+    'MultiWOZBeliefState',
+]
+
+
+class DialogAxisKind(AxisKindAbstract):
+    """ Class containing definitions of axis kinds specialized for the dialog problem domain. """
+
+    Domain = 7
+
+
+class Utterance(StringType):
+    """Element type representing an utterance (e.g. "Is there a train from Ely to Cambridge on Tuesday ?")."""
+
+
+class UserUtterance(Utterance):
+    """Element type representing a utterance expresesd by the user."""
+
+
+class SystemUtterance(Utterance):
+    """Element type representing an utterance produced by the system."""
+
+
+class AgentUtterance(ElementType):
+    """Element type representing utterance returned by an agent (user or system) participating in a dialog."""
+
+    # def __str__(self):
+    #    return "Utterance returned by an agent (user or system) participating in a dialog."
+
+    # def fields(self):
+    #    return ("agent", "utterance")
+
+
+class SlotValue(ElementType):
+    """Element type representing slot-value pair."""
+
+    # def __str__(self):
+    #    return "Slot-value pair"
+
+    # def fields(self):
+    #    return ("slot", "value")
+
+
+class MultiWOZBeliefState(SlotValue):
+    """Element type representing MultiWOZ belief state - one per domain."""
+
+    # def fields(self):
+    #    return ("book", "semi")

nemo/collections/nlp/nm/non_trainables/dialogue_state_tracking/rule_based_dpm_multiwoz.py

@@ -33,6 +33,7 @@
 from nemo.collections.nlp.data.datasets.multiwoz_dataset.dbquery import Database
 from nemo.collections.nlp.data.datasets.multiwoz_dataset.multiwoz_slot_trans import REF_SYS_DA, REF_USR_DA
 from nemo.core.neural_types import *
+from nemo.collections.nlp.neural_types import *
 from nemo.utils.decorators import add_port_docs
 
 __all__ = ['RuleBasedDPMMultiWOZ']
@@ -120,10 +121,10 @@ def input_ports(self):
                 axes=[
                     AxisType(kind=AxisKind.Batch, is_list=True),
                     AxisType(
-                        kind=AxisKind.MultiWOZDomain, is_list=True
+                        kind=DialogAxisKind.Domain, is_list=True
                     ),  # always 7 domains - but cannot set size with is_list!
                 ],
-                elements_type=MultiWOZDomainState(),
+                elements_type=MultiWOZBeliefState(),
             ),
             'request_state': NeuralType(
                 axes=[AxisType(kind=AxisKind.Batch, is_list=True), AxisType(kind=AxisKind.Sequence, is_list=True)],
@@ -143,10 +144,10 @@ def output_ports(self):
                 axes=[
                     AxisType(kind=AxisKind.Batch, is_list=True),
                     AxisType(
-                        kind=AxisKind.MultiWOZDomain, is_list=True
+                        kind=DialogAxisKind.Domain, is_list=True
                     ),  # always 7 domains - but cannot set size with is_list!
                 ],
-                elements_type=MultiWOZDomainState(),
+                elements_type=MultiWOZBeliefState(),
             ),
             'system_acts': NeuralType(
                 axes=[AxisType(kind=AxisKind.Batch, is_list=True), AxisType(kind=AxisKind.Sequence, is_list=True)],

nemo/collections/nlp/nm/non_trainables/dialogue_state_tracking/system_utterance_history_update.py

@@ -21,6 +21,7 @@
 
 from nemo.backends.pytorch.nm import NonTrainableNM
 from nemo.core.neural_types import *
+from nemo.collections.nlp.neural_types import *
 from nemo.utils import logging
 from nemo.utils.decorators import add_port_docs
 

nemo/collections/nlp/nm/non_trainables/dialogue_state_tracking/template_nlg_multiwoz.py

@@ -25,6 +25,7 @@
 
 from nemo.backends.pytorch.nm import NonTrainableNM
 from nemo.core.neural_types import *
+from nemo.collections.nlp.neural_types import *
 from nemo.utils import logging
 from nemo.utils.decorators import add_port_docs
 

nemo/collections/nlp/nm/non_trainables/dialogue_state_tracking/trade_state_update_nm.py

@@ -28,6 +28,7 @@
 from nemo.collections.nlp.data.datasets.multiwoz_dataset.multiwoz_slot_trans import REF_SYS_DA
 from nemo.collections.nlp.utils.callback_utils import tensor2numpy
 from nemo.core.neural_types import *
+from nemo.collections.nlp.neural_types import *
 from nemo.utils import logging
 from nemo.utils.decorators import add_port_docs
 
@@ -52,9 +53,9 @@ def input_ports(self):
             'belief_state': NeuralType(
                 axes=[
                     AxisType(kind=AxisKind.Batch, is_list=True),
-                    AxisType(kind=AxisKind.MultiWOZDomain, is_list=True),  # 7 domains
+                    AxisType(kind=DialogAxisKind.Domain, is_list=True),  # 7 domains
                 ],
-                elements_type=MultiWOZDomainState(),
+                elements_type=MultiWOZBeliefState(),
             ),
             'user_uttr': NeuralType(axes=[AxisType(kind=AxisKind.Batch, is_list=True)], elements_type=Utterance()),
         }
@@ -68,9 +69,9 @@ def output_ports(self):
             'belief_state': NeuralType(
                 axes=[
                     AxisType(kind=AxisKind.Batch, is_list=True),
-                    AxisType(kind=AxisKind.MultiWOZDomain, is_list=True),  # 7 domains
+                    AxisType(kind=DialogAxisKind.Domain, is_list=True),  # 7 domains
                 ],
-                elements_type=MultiWOZDomainState(),
+                elements_type=MultiWOZBeliefState(),
             ),
             'request_state': NeuralType(
                 axes=[AxisType(kind=AxisKind.Batch, is_list=True), AxisType(kind=AxisKind.Sequence, is_list=True)],

nemo/collections/nlp/nm/non_trainables/dialogue_state_tracking/user_utterance_encoder.py

@@ -22,6 +22,7 @@
 
 from nemo.backends.pytorch.nm import NonTrainableNM
 from nemo.core.neural_types import *
+from nemo.collections.nlp.neural_types import *
 from nemo.utils import logging
 from nemo.utils.decorators import add_port_docs
 

nemo/core/neural_types/axes.py

@@ -45,8 +45,6 @@ class AxisKind(AxisKindAbstract):
     Height = 4
     Any = 5
     Sequence = 6
-    DialogDomain = 7
-    MultiWOZDomain = 8  # A specialized DialogDomain axis?
 
     def __repr__(self):
         return self.__str__()

nemo/core/neural_types/elements.py

@@ -43,14 +43,8 @@
     'NormalizedImageValue',
     'StringLabel',
     'StringType',
-    'Utterance',
-    'UserUtterance',
-    'SystemUtterance',
-    'AgentUtterance',
     'TokenIndex',
     'Length',
-    'SlotValue',
-    'MultiWOZDomainState',
 ]
 
 import abc
@@ -256,28 +250,6 @@ class StringLabel(StringType):
     """
 
 
-class Utterance(StringType):
-    """Element type representing an utterance (e.g. "Is there a train from Ely to Cambridge on Tuesday ?")."""
-
-
-class UserUtterance(Utterance):
-    """Element type representing a utterance expresesd by the user."""
-
-
-class SystemUtterance(Utterance):
-    """Element type representing an utterance produced by the system."""
-
-
-class AgentUtterance(ElementType):
-    """Element type representing utterance returned by an agent (user or system) participating in a dialog."""
-
-    # def __str__(self):
-    #    return "Utterance returned by an agent (user or system) participating in a dialog."
-
-    # def fields(self):
-    #    return ("agent", "utterance")
-
-
 class IntType(ElementType):
     """Element type representing a single integer"""
 
@@ -288,20 +260,3 @@ class TokenIndex(IntType):
 
 class Length(IntType):
     """Type representing an element storing a "length" (e.g. length of a list)."""
-
-
-class SlotValue(ElementType):
-    """Element type representing slot-value pair."""
-
-    # def __str__(self):
-    #    return "Slot-value pair"
-
-    # def fields(self):
-    #    return ("slot", "value")
-
-
-class MultiWOZDomainState(SlotValue):
-    """Element type representing MultiWOZ slot-value pair."""
-
-    # def fields(self):
-    #    return ("book", "semi")