Merge pull request #1243 from bogatyy/master

Add license headers, fix some macOS issues

syntaxnet/dragnn/python/visualization.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 """Helper library for visualizations.
 
 TODO(googleuser): Find a more reliable way to serve stuff from IPython

syntaxnet/dragnn/python/visualization_test.py

 # -*- coding: utf-8 -*-
+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 """Tests for dragnn.python.visualization."""
 
 from __future__ import absolute_import

syntaxnet/dragnn/python/wrapped_units.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 """Network units wrapping TensorFlows' tf.contrib.rnn cells.
 
 Please put all wrapping logic for tf.contrib.rnn in this module; this will help
@@ -25,7 +40,7 @@ class BaseLSTMNetwork(dragnn.NetworkUnitInterface):
     logits: Logits associated with component actions.
   """
 
-  def __init__(self, component):
+  def __init__(self, component, additional_attr_defaults=None):
     """Initializes the LSTM base class.
 
     Parameters used:
@@ -42,15 +57,18 @@ class BaseLSTMNetwork(dragnn.NetworkUnitInterface):
 
     Args:
       component: parent ComponentBuilderBase object.
+      additional_attr_defaults: Additional attributes for use by derived class.
     """
+    attr_defaults = additional_attr_defaults or {}
+    attr_defaults.update({
+        'layer_norm': True,
+        'input_dropout_rate': -1.0,
+        'recurrent_dropout_rate': 0.8,
+        'hidden_layer_sizes': '256',
+    })
     self._attrs = dragnn.get_attrs_with_defaults(
         component.spec.network_unit.parameters,
-        defaults={
-            'layer_norm': True,
-            'input_dropout_rate': -1.0,
-            'recurrent_dropout_rate': 0.8,
-            'hidden_layer_sizes': '256',
-        })
+        defaults=attr_defaults)
 
     self._hidden_layer_sizes = map(int,
                                    self._attrs['hidden_layer_sizes'].split(','))
@@ -87,8 +105,7 @@ class BaseLSTMNetwork(dragnn.NetworkUnitInterface):
     self._params.append(
         tf.get_variable(
             'weights_softmax', [last_layer_dim, component.num_actions],
-            initializer=tf.random_normal_initializer(
-                stddev=1e-4, seed=self._seed)))
+            initializer=tf.random_normal_initializer(stddev=1e-4)))
     self._params.append(
         tf.get_variable(
             'bias_softmax', [component.num_actions],
@@ -116,14 +133,9 @@ class BaseLSTMNetwork(dragnn.NetworkUnitInterface):
     """Appends layers defined by the base class to the |hidden_layers|."""
     last_layer = hidden_layers[-1]
 
-    # TODO(googleuser): Uncomment the version that uses component.get_variable()
-    # and delete the uses of tf.get_variable().
-    # logits = tf.nn.xw_plus_b(last_layer,
-    #                          self._component.get_variable('weights_softmax'),
-    #                          self._component.get_variable('bias_softmax'))
     logits = tf.nn.xw_plus_b(last_layer,
-                             tf.get_variable('weights_softmax'),
-                             tf.get_variable('bias_softmax'))
+                             self._component.get_variable('weights_softmax'),
+                             self._component.get_variable('bias_softmax'))
     return hidden_layers + [last_layer, logits]
 
   def _create_cell(self, num_units, during_training):
@@ -321,7 +333,18 @@ class BulkBiLSTMNetwork(BaseLSTMNetwork):
   """
 
   def __init__(self, component):
-    super(BulkBiLSTMNetwork, self).__init__(component)
+    """Initializes the bulk bi-LSTM.
+
+    Parameters used:
+      parallel_iterations (1): Parallelism of the underlying tf.while_loop().
+        Defaults to 1 thread to encourage deterministic behavior, but can be
+        increased to trade memory for speed.
+
+    Args:
+      component: parent ComponentBuilderBase object.
+    """
+    super(BulkBiLSTMNetwork, self).__init__(
+        component, additional_attr_defaults={'parallel_iterations': 1})
 
     check.In('lengths', self._linked_feature_dims,
              'Missing required linked feature')
@@ -426,6 +449,7 @@ class BulkBiLSTMNetwork(BaseLSTMNetwork):
           initial_states_fw=initial_states_forward,
           initial_states_bw=initial_states_backward,
           sequence_length=lengths_s,
+          parallel_iterations=self._attrs['parallel_iterations'],
           scope=scope)
       return outputs_sxnxd
 

syntaxnet/dragnn/tools/BUILD

 package(default_visibility = ["//visibility:public"])
 
+filegroup(
+    name = "testdata",
+    srcs = glob(["testdata/**"]),
+)
+
 py_binary(
     name = "evaluator",
     srcs = ["evaluator.py"],
@@ -74,6 +79,26 @@ py_binary(
 py_binary(
     name = "segmenter_trainer",
     srcs = ["segmenter_trainer.py"],
+    deps = [
+        "//dragnn/core:dragnn_bulk_ops",
+        "//dragnn/core:dragnn_ops",
+        "//dragnn/protos:spec_py_pb2",
+        "//dragnn/python:evaluation",
+        "//dragnn/python:graph_builder",
+        "//dragnn/python:load_dragnn_cc_impl_py",
+        "//dragnn/python:sentence_io",
+        "//dragnn/python:spec_builder",
+        "//dragnn/python:trainer_lib",
+        "//syntaxnet:load_parser_ops_py",
+        "//syntaxnet:parser_ops",
+        "@org_tensorflow//tensorflow:tensorflow_py",
+        "@org_tensorflow//tensorflow/core:protos_all_py",
+    ],
+)
+
+py_binary(
+    name = "model_trainer",
+    srcs = ["model_trainer.py"],
     deps = [
         "//dragnn/core:dragnn_bulk_ops",
         "//dragnn/core:dragnn_ops",
@@ -81,7 +106,6 @@ py_binary(
         "//dragnn/python:dragnn_ops",
         "//dragnn/python:evaluation",
         "//dragnn/python:graph_builder",
-        "//dragnn/python:lexicon",
         "//dragnn/python:load_dragnn_cc_impl_py",
         "//dragnn/python:sentence_io",
         "//dragnn/python:spec_builder",
@@ -90,11 +114,24 @@ py_binary(
         "//syntaxnet:parser_ops",
         "//syntaxnet:sentence_py_pb2",
         "//syntaxnet:task_spec_py_pb2",
+        "//syntaxnet/util:check",
         "@org_tensorflow//tensorflow:tensorflow_py",
         "@org_tensorflow//tensorflow/core:protos_all_py",
     ],
 )
 
+sh_test(
+    name = "model_trainer_test",
+    size = "medium",
+    srcs = ["model_trainer_test.sh"],
+    data = [
+        ":model_trainer",
+        ":testdata",
+    ],
+    deps = [
+    ],
+)
+
 # This is meant to be run inside the Docker image. In the OSS directory, run,
 #
 #     ./build_devel.sh bazel run //dragnn/python:oss_notebook_launcher

syntaxnet/dragnn/tools/build_pip_package.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 """Builds a pip package suitable for redistribution.
 
 Adapted from tensorflow/tools/pip_package/build_pip_package.sh. This might have

syntaxnet/dragnn/tools/evaluator.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 r"""Runs a DRAGNN model on a given set of CoNLL-formatted sentences.
 
 Sample invocation:
@@ -51,6 +66,9 @@ flags.DEFINE_integer('threads', 10, 'Number of threads used for intra- and '
 flags.DEFINE_string('timeline_output_file', '', 'Path to save timeline to. '
                     'If specified, the final iteration of the evaluation loop '
                     'will capture and save a TensorFlow timeline.')
+flags.DEFINE_string('log_file', '', 'File path to write parser eval results.')
+flags.DEFINE_string('language_name', '_', 'Name of language being parsed, '
+                    'for logging.')
 
 
 def main(unused_argv):
@@ -134,6 +152,9 @@ def main(unused_argv):
     tf.logging.info('Processed %d documents in %.2f seconds.',
                     len(input_corpus), time.time() - start_time)
     pos, uas, las = evaluation.calculate_parse_metrics(input_corpus, processed)
+    if FLAGS.log_file:
+      with gfile.GFile(FLAGS.log_file, 'w') as f:
+        f.write('%s\t%f\t%f\t%f\n' % (FLAGS.language_name, pos, uas, las))
 
     if FLAGS.output_file:
       with gfile.GFile(FLAGS.output_file, 'w') as f:

syntaxnet/dragnn/tools/model_trainer.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+"""Trainer for generic DRAGNN models.
+
+This trainer uses a "model directory" for both input and output.  When invoked,
+the model directory should contain the following inputs:
+
+  <model_dir>/config.txt: A stringified dict that defines high-level
+    configuration parameters.  Unset parameters default to False.
+  <model_dir>/master.pbtxt: A text-format MasterSpec proto that defines
+    the DRAGNN network to train.
+  <model_dir>/hyperparameters.pbtxt: A text-format GridPoint proto that
+    defines training hyper-parameters.
+  <model_dir>/targets.pbtxt: (Optional) A text-format TrainingGridSpec whose
+    "target" field defines the training targets.  If missing, then default
+    training targets are used instead.
+
+On success, the model directory will contain the following outputs:
+
+  <model_dir>/checkpoints/best: The best checkpoint seen during training, as
+    measured by accuracy on the eval corpus.
+  <model_dir>/tensorboard: TensorBoard log directory.
+
+Outside of the files and subdirectories named above, the model directory should
+contain any other necessary files (e.g., pretrained embeddings).  See the model
+builders in dragnn/examples.
+"""
+
+import ast
+import collections
+import os
+import os.path
+import tensorflow as tf
+
+from google.protobuf import text_format
+
+from dragnn.protos import spec_pb2
+from dragnn.python import evaluation
+from dragnn.python import graph_builder
+from dragnn.python import sentence_io
+from dragnn.python import spec_builder
+from dragnn.python import trainer_lib
+from syntaxnet.ops import gen_parser_ops
+from syntaxnet.util import check
+
+import dragnn.python.load_dragnn_cc_impl
+import syntaxnet.load_parser_ops
+
+flags = tf.app.flags
+FLAGS = flags.FLAGS
+
+flags.DEFINE_string('tf_master', '',
+                    'TensorFlow execution engine to connect to.')
+flags.DEFINE_string('model_dir', None, 'Path to a prepared model directory.')
+
+flags.DEFINE_string(
+    'pretrain_steps', None,
+    'Comma-delimited list of pre-training steps per training target.')
+flags.DEFINE_string(
+    'pretrain_epochs', None,
+    'Comma-delimited list of pre-training epochs per training target.')
+flags.DEFINE_string(
+    'train_steps', None,
+    'Comma-delimited list of training steps per training target.')
+flags.DEFINE_string(
+    'train_epochs', None,
+    'Comma-delimited list of training epochs per training target.')
+
+flags.DEFINE_integer('batch_size', 4, 'Batch size.')
+flags.DEFINE_integer('report_every', 200,
+                     'Report cost and training accuracy every this many steps.')
+
+
+def _read_text_proto(path, proto_type):
+  """Reads a text-format instance of |proto_type| from the |path|."""
+  proto = proto_type()
+  with tf.gfile.FastGFile(path) as proto_file:
+    text_format.Parse(proto_file.read(), proto)
+  return proto
+
+
+def _convert_to_char_corpus(corpus):
+  """Converts the word-based |corpus| into a char-based corpus."""
+  with tf.Session(graph=tf.Graph()) as tmp_session:
+    conversion_op = gen_parser_ops.segmenter_training_data_constructor(corpus)
+    return tmp_session.run(conversion_op)
+
+
+def _get_steps(steps_flag, epochs_flag, corpus_length):
+  """Converts the |steps_flag| or |epochs_flag| into a list of step counts."""
+  if steps_flag:
+    return map(int, steps_flag.split(','))
+  return [corpus_length * int(epochs) for epochs in epochs_flag.split(',')]
+
+
+def main(unused_argv):
+  tf.logging.set_verbosity(tf.logging.INFO)
+
+  check.NotNone(FLAGS.model_dir, '--model_dir is required')
+  check.Ne(FLAGS.pretrain_steps is None, FLAGS.pretrain_epochs is None,
+           'Exactly one of --pretrain_steps or --pretrain_epochs is required')
+  check.Ne(FLAGS.train_steps is None, FLAGS.train_epochs is None,
+           'Exactly one of --train_steps or --train_epochs is required')
+
+  config_path = os.path.join(FLAGS.model_dir, 'config.txt')
+  master_path = os.path.join(FLAGS.model_dir, 'master.pbtxt')
+  hyperparameters_path = os.path.join(FLAGS.model_dir, 'hyperparameters.pbtxt')
+  targets_path = os.path.join(FLAGS.model_dir, 'targets.pbtxt')
+  checkpoint_path = os.path.join(FLAGS.model_dir, 'checkpoints/best')
+  tensorboard_dir = os.path.join(FLAGS.model_dir, 'tensorboard')
+
+  with tf.gfile.FastGFile(config_path) as config_file:
+    config = collections.defaultdict(bool, ast.literal_eval(config_file.read()))
+  train_corpus_path = config['train_corpus_path']
+  tune_corpus_path = config['tune_corpus_path']
+  projectivize_train_corpus = config['projectivize_train_corpus']
+
+  master = _read_text_proto(master_path, spec_pb2.MasterSpec)
+  hyperparameters = _read_text_proto(hyperparameters_path, spec_pb2.GridPoint)
+  targets = spec_builder.default_targets_from_spec(master)
+  if tf.gfile.Exists(targets_path):
+    targets = _read_text_proto(targets_path, spec_pb2.TrainingGridSpec).target
+
+  # Build the TensorFlow graph.
+  graph = tf.Graph()
+  with graph.as_default():
+    tf.set_random_seed(hyperparameters.seed)
+    builder = graph_builder.MasterBuilder(master, hyperparameters)
+    trainers = [
+        builder.add_training_from_config(target) for target in targets
+    ]
+    annotator = builder.add_annotation()
+    builder.add_saver()
+
+  # Read in serialized protos from training data.
+  train_corpus = sentence_io.ConllSentenceReader(
+      train_corpus_path, projectivize=projectivize_train_corpus).corpus()
+  tune_corpus = sentence_io.ConllSentenceReader(
+      tune_corpus_path, projectivize=False).corpus()
+  gold_tune_corpus = tune_corpus
+
+  # Convert to char-based corpora, if requested.
+  if config['convert_to_char_corpora']:
+    # NB: Do not convert the |gold_tune_corpus|, which should remain word-based
+    # for segmentation evaluation purposes.
+    train_corpus = _convert_to_char_corpus(train_corpus)
+    tune_corpus = _convert_to_char_corpus(tune_corpus)
+
+  pretrain_steps = _get_steps(FLAGS.pretrain_steps, FLAGS.pretrain_epochs,
+                              len(train_corpus))
+  train_steps = _get_steps(FLAGS.train_steps, FLAGS.train_epochs,
+                           len(train_corpus))
+  check.Eq(len(targets), len(pretrain_steps),
+           'Length mismatch between training targets and --pretrain_steps')
+  check.Eq(len(targets), len(train_steps),
+           'Length mismatch between training targets and --train_steps')
+
+  # Ready to train!
+  tf.logging.info('Training on %d sentences.', len(train_corpus))
+  tf.logging.info('Tuning on %d sentences.', len(tune_corpus))
+
+  tf.logging.info('Creating TensorFlow checkpoint dir...')
+  summary_writer = trainer_lib.get_summary_writer(tensorboard_dir)
+
+  checkpoint_dir = os.path.dirname(checkpoint_path)
+  if tf.gfile.IsDirectory(checkpoint_dir):
+    tf.gfile.DeleteRecursively(checkpoint_dir)
+  elif tf.gfile.Exists(checkpoint_dir):
+    tf.gfile.Remove(checkpoint_dir)
+  tf.gfile.MakeDirs(checkpoint_dir)
+
+  with tf.Session(FLAGS.tf_master, graph=graph) as sess:
+    # Make sure to re-initialize all underlying state.
+    sess.run(tf.global_variables_initializer())
+    trainer_lib.run_training(sess, trainers, annotator,
+                             evaluation.parser_summaries, pretrain_steps,
+                             train_steps, train_corpus, tune_corpus,
+                             gold_tune_corpus, FLAGS.batch_size, summary_writer,
+                             FLAGS.report_every, builder.saver, checkpoint_path)
+
+  tf.logging.info('Best checkpoint written to:\n%s', checkpoint_path)
+
+
+if __name__ == '__main__':
+  tf.app.run()

syntaxnet/dragnn/tools/model_trainer_test.sh

+#!/bin/bash
+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
+# This test runs the model trainer on a snapshotted model directory.  This is a
+# "don't crash" test, so it does not evaluate the trained model.
+
+
+
+
+set -eu
+
+readonly DRAGNN_DIR="${TEST_SRCDIR}/${TEST_WORKSPACE}/dragnn"
+readonly MODEL_TRAINER="${DRAGNN_DIR}/tools/model_trainer"
+readonly MODEL_DIR="${DRAGNN_DIR}/tools/testdata/biaffine.model"
+readonly CORPUS="${DRAGNN_DIR}/tools/testdata/small.conll"
+readonly TMP_DIR="/tmp/model_trainer_test.$$"
+readonly TMP_MODEL_DIR="${TMP_DIR}/biaffine.model"
+
+rm -rf "${TMP_DIR}"
+mkdir -p "${TMP_DIR}"
+
+# Copy all testdata files to a temp dir, so they can be modified (see below).
+cp "${CORPUS}" "${TMP_DIR}"
+mkdir -p "${TMP_MODEL_DIR}"
+for name in hyperparameters.pbtxt targets.pbtxt resources; do
+  cp -r "${MODEL_DIR}/${name}" "${TMP_MODEL_DIR}/${name}"
+done
+
+# Replace "TESTDATA" with the temp dir path in config files that contain paths.
+for name in config.txt master.pbtxt; do
+  sed "s=TESTDATA=${TMP_DIR}=" "${MODEL_DIR}/${name}" \
+    > "${TMP_MODEL_DIR}/${name}"
+done
+
+"${MODEL_TRAINER}" \
+  --model_dir="${TMP_MODEL_DIR}" \
+  --pretrain_steps='1' \
+  --train_epochs='10' \
+  --alsologtostderr
+
+echo "PASS"

syntaxnet/dragnn/tools/oss_notebook_launcher.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 """Mini OSS launcher so we can build a py_binary for OSS."""
 
 from __future__ import absolute_import

syntaxnet/dragnn/tools/parse-to-conll.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 r"""Runs a both a segmentation and parsing model on a CoNLL dataset.
 """
 

syntaxnet/dragnn/tools/parser_trainer.py

@@ -60,7 +60,6 @@ flags.DEFINE_string('dev_corpus_path', '', 'Path to development set data.')
 flags.DEFINE_bool('compute_lexicon', False, '')
 flags.DEFINE_bool('projectivize_training_set', True, '')
 
-flags.DEFINE_integer('num_epochs', 10, 'Number of epochs to train for.')
 flags.DEFINE_integer('batch_size', 4, 'Batch size.')
 flags.DEFINE_integer('report_every', 200,
                      'Report cost and training accuracy every this many steps.')

syntaxnet/dragnn/tools/segmenter-evaluator.py

+# Copyright 2017 Google Inc. 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.
+# ==============================================================================
+
 r"""Runs a DRAGNN model on a given set of CoNLL-formatted sentences.
 
 Sample invocation:

syntaxnet/dragnn/tools/testdata/biaffine.model/config.txt

+{
+  'train_corpus_path': 'TESTDATA/small.conll',
+  'tune_corpus_path': 'TESTDATA/small.conll',
+}

syntaxnet/dragnn/tools/testdata/biaffine.model/hyperparameters.pbtxt

+learning_method: "adam"
+adam_beta1: 0.9
+adam_beta2: 0.9
+adam_eps: 1e-12
+
+learning_rate: 0.002
+decay_base: 0.75
+decay_staircase: false
+decay_steps: 2500
+
+dropout_rate: 0.67
+recurrent_dropout_rate: 0.75
+
+gradient_clip_norm: 15
+l2_regularization_coefficient: 0
+use_moving_average: false
+
+seed: 1

syntaxnet/dragnn/tools/testdata/biaffine.model/resources/category-map

+6
+VERB 6
+NOUN 5
+PRON 5
+PUNCT 5
+DET 2
+CONJ 1

syntaxnet/dragnn/tools/testdata/biaffine.model/resources/char-map

+17
+o 10
+e 8
+b 6
+s 6
+. 5
+h 5
+l 5
+y 5
+k 4
+T 3
+a 3
+n 3
+u 3
+I 2
+v 2
+c 1
+d 1

syntaxnet/dragnn/tools/testdata/biaffine.model/resources/char-ngram-map

+45
+o 8
+^ b 6
+^ . $ 5
+e 5
+y $ 5
+^ bo 4
+k 4
+ks $ 4
+ok 4
+oo 4
+s $ 4
+^ T 3
+^ Th 3
+e $ 3
+ey $ 3
+h 3
+he 3
+l 3
+u 3
+^ I $ 2
+^ bu 2
+^ h 2
+^ ha 2
+^ n 2
+^ no $ 2
+^ s 2
+^ se 2
+a 2
+av 2
+el 2
+l $ 2
+ll $ 2
+o $ 2
+uy $ 2
+v 2
+ve $ 2
+^ a 1
+^ an 1
+^ c 1
+^ cl 1
+d $ 1
+lu 1
+n 1
+nd $ 1
+ue $ 1

syntaxnet/dragnn/tools/testdata/biaffine.model/resources/label-map

+7
+ROOT 5
+nsubj 5
+obj 5
+punct 5
+det 2
+cc 1
+conj 1

syntaxnet/dragnn/tools/testdata/biaffine.model/resources/lcword-map

+10
+. 5
+books 4
+they 3
+buy 2
+have 2
+i 2
+no 2
+sell 2
+and 1
+clue 1