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* Created using Colaboratory * [examples] reorganize files * remove run_tpu_glue.py as superseded by TPU support in Trainer * Bugfix: int, not tuple * move files around
122 lines
4.2 KiB
Python
122 lines
4.2 KiB
Python
# coding=utf-8
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# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
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# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import copy
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import csv
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import json
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class InputExample(object):
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"""
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A single training/test example for simple sequence classification.
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Args:
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guid: Unique id for the example.
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text_a: string. The untokenized text of the first sequence. For single
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sequence tasks, only this sequence must be specified.
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text_b: (Optional) string. The untokenized text of the second sequence.
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Only must be specified for sequence pair tasks.
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label: (Optional) string. The label of the example. This should be
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specified for train and dev examples, but not for test examples.
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"""
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def __init__(self, guid, text_a, text_b=None, label=None, pairID=None):
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self.guid = guid
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self.text_a = text_a
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self.text_b = text_b
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self.label = label
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self.pairID = pairID
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def __repr__(self):
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return str(self.to_json_string())
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def to_dict(self):
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"""Serializes this instance to a Python dictionary."""
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output = copy.deepcopy(self.__dict__)
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return output
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def to_json_string(self):
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"""Serializes this instance to a JSON string."""
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return json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"
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class InputFeatures(object):
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"""
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A single set of features of data.
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Args:
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input_ids: Indices of input sequence tokens in the vocabulary.
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attention_mask: Mask to avoid performing attention on padding token indices.
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Mask values selected in ``[0, 1]``:
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Usually ``1`` for tokens that are NOT MASKED, ``0`` for MASKED (padded) tokens.
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token_type_ids: Segment token indices to indicate first and second portions of the inputs.
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label: Label corresponding to the input
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"""
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def __init__(self, input_ids, attention_mask, token_type_ids, label, pairID=None):
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self.input_ids = input_ids
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self.attention_mask = attention_mask
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self.token_type_ids = token_type_ids
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self.label = label
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self.pairID = pairID
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def __repr__(self):
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return str(self.to_json_string())
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def to_dict(self):
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"""Serializes this instance to a Python dictionary."""
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output = copy.deepcopy(self.__dict__)
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return output
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def to_json_string(self):
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"""Serializes this instance to a JSON string."""
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return json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"
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class DataProcessor(object):
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"""Base class for data converters for sequence classification data sets."""
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def get_example_from_tensor_dict(self, tensor_dict):
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"""Gets an example from a dict with tensorflow tensors
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Args:
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tensor_dict: Keys and values should match the corresponding Glue
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tensorflow_dataset examples.
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"""
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raise NotImplementedError()
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def get_train_examples(self, data_dir):
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"""Gets a collection of `InputExample`s for the train set."""
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raise NotImplementedError()
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def get_dev_examples(self, data_dir):
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"""Gets a collection of `InputExample`s for the dev set."""
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raise NotImplementedError()
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def get_labels(self):
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"""Gets the list of labels for this data set."""
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raise NotImplementedError()
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@classmethod
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def _read_tsv(cls, input_file, quotechar=None):
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"""Reads a tab separated value file."""
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with open(input_file, "r", encoding="utf-8-sig") as f:
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reader = csv.reader(f, delimiter="\t", quotechar=quotechar)
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lines = []
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for line in reader:
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lines.append(line)
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return lines
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