102 lines
4.5 KiB
Python
102 lines
4.5 KiB
Python
# -*- coding: utf-8 -*-
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from unittest import TestCase
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import json
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import logging
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import os
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import shutil
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import subprocess
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import tempfile
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logger = logging.getLogger(__name__)
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class TorchtextTestCase(TestCase):
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def setUp(self):
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logging.basicConfig(format=('%(asctime)s - %(levelname)s - '
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'%(name)s - %(message)s'),
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level=logging.INFO)
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# Directory where everything temporary and test-related is written
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self.project_root = os.path.abspath(os.path.realpath(os.path.join(
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os.path.dirname(os.path.realpath(__file__)), os.pardir, os.pardir)))
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self.test_dir = tempfile.mkdtemp()
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self.test_ppid_dataset_path = os.path.join(self.test_dir, "test_ppid_dataset")
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self.test_numerical_features_dataset_path = os.path.join(
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self.test_dir, "test_numerical_features_dataset")
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def tearDown(self):
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try:
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shutil.rmtree(self.test_dir)
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except:
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subprocess.call(["rm", "-rf", self.test_dir])
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def write_test_ppid_dataset(self, data_format="csv"):
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data_format = data_format.lower()
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if data_format == "csv":
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delim = ","
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elif data_format == "tsv":
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delim = "\t"
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dict_dataset = [
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{"id": "0", "question1": "When do you use シ instead of し?",
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"question2": "When do you use \"&\" instead of \"and\"?",
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"label": "0"},
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{"id": "1", "question1": "Where was Lincoln born?",
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"question2": "Which location was Abraham Lincoln born?",
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"label": "1"},
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{"id": "2", "question1": "What is 2+2",
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"question2": "2+2=?",
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"label": "1"},
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]
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with open(self.test_ppid_dataset_path, "w") as test_ppid_dataset_file:
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for example in dict_dataset:
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if data_format == "json":
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test_ppid_dataset_file.write(json.dumps(example) + "\n")
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elif data_format == "csv" or data_format == "tsv":
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test_ppid_dataset_file.write("{}\n".format(
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delim.join([example["id"], example["question1"],
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example["question2"], example["label"]])))
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else:
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raise ValueError("Invalid format {}".format(data_format))
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def write_test_numerical_features_dataset(self):
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with open(self.test_numerical_features_dataset_path,
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"w") as test_numerical_features_dataset_file:
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test_numerical_features_dataset_file.write("0.1\t1\tteststring1\n")
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test_numerical_features_dataset_file.write("0.5\t12\tteststring2\n")
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test_numerical_features_dataset_file.write("0.2\t0\tteststring3\n")
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test_numerical_features_dataset_file.write("0.4\t12\tteststring4\n")
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test_numerical_features_dataset_file.write("0.9\t9\tteststring5\n")
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def verify_numericalized_example(field, test_example_data,
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test_example_numericalized,
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test_example_lengths=None,
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batch_first=False, train=True):
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"""
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Function to verify that numericalized example is correct
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with respect to the Field's Vocab.
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"""
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if isinstance(test_example_numericalized, tuple):
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test_example_numericalized, lengths = test_example_numericalized
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assert test_example_lengths == lengths.tolist()
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if batch_first:
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test_example_numericalized.data.t_()
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# Transpose numericalized example so we can compare over batches
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for example_idx, numericalized_single_example in enumerate(
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test_example_numericalized.t()):
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assert len(test_example_data[example_idx]) == len(numericalized_single_example)
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assert numericalized_single_example.volatile is not train
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for token_idx, numericalized_token in enumerate(
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numericalized_single_example):
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# Convert from Variable to int
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numericalized_token = numericalized_token.data[0]
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test_example_token = test_example_data[example_idx][token_idx]
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# Check if the numericalized example is correct, taking into
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# account unknown tokens.
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if field.vocab.stoi[test_example_token] != 0:
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# token is in-vocabulary
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assert (field.vocab.itos[numericalized_token] ==
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test_example_token)
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else:
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# token is OOV and <unk> always has an index of 0
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assert numericalized_token == 0
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