How to use test_table_encoder method in autotest

Best Python code snippet using autotest_python

train_pairwise.py

Source: train_pairwise.py Github

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...54 if config['use_in_domain_test']:55 print('Computing In-Domain Query Embeddings...')56 indomain_sample_info_dict = test_query_encoder(data['in_domain_test_batches'], query_embedding_step)57 print('Computing Train Table Embeddings...')58 train_index_to_vec, train_id_to_index = test_table_encoder(train_headers, train_table_words, train_all_num_cols,59 train_masks, train_table_ids, table_embedding_step)60 print('Indexing Train Table Embeddings...')61 index_embeddings(train_index_to_vec, train_index, dim)62 print('Computing Dev Query Embeddings...')63 dev_sample_info_dict = test_query_encoder(data['dev_samples_batches'], query_embedding_step)64 print('Computing Dev Table Embeddings...')65 dev_index_to_vec, dev_id_to_index = test_table_encoder(dev_headers, dev_table_words, dev_all_num_cols, dev_masks,66 dev_table_ids, table_embedding_step)67 print('Indexing Dev Table Embeddings...')68 index_embeddings(dev_index_to_vec, dev_index, dim)69 print('Computing Test Query Embeddings...')70 test_sample_info_dict = test_query_encoder(data['test_samples_batches'], query_embedding_step)71 print('Computing Test Table Embeddings...')72 test_index_to_vec, test_id_to_index = test_table_encoder(test_headers, test_table_words, test_all_num_cols,73 test_masks, test_table_ids, table_embedding_step)74 print('Indexing Test Table Embeddings...')75 index_embeddings(test_index_to_vec, test_index, dim)76 print('Logging Metrics...')77 p_req = config['find_p']78 if not os.path.exists(log_path):79 os.makedirs(log_path)80 log_file = open(os.path.join(log_path, str(epoch_num) + '.tsv'), 'w', encoding='utf8')81 log_file.write('Eval Set' + '\t' + 'MRR')82 for p in p_req:83 log_file.write('\tP@' + str(p))84 log_file.write('\n')85 if config['use_in_domain_test']:86 metrics_logger(indomain_sample_info_dict, train_id_to_index, train_index, dim, 'in_domain_test', p_req,...

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csv_encoder_unittest.py

Source: csv_encoder_unittest.py Github

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...33 ',col1/​sub1,col1/​sub2,col2/​sub1',34 'row1,1 /​ 2,,',35 'row2,,,3 /​ 4 (5 incomplete)',36 '"comma,header",,,')37 def test_table_encoder(self):38 request = self._make_request('get_test_views', [['col1', 'Column 1'],39 ['col2', 'Column 2']])40 response = [{'col1' : 'foo', 'col2' : 'bar'},41 {'col1' : 'baz', 'col2' : 'asdf'}]42 self._encode_and_check_result(request, response,43 'Column 1,Column 2',44 'foo,bar',45 'baz,asdf')46 def test_grouped_table_encoder(self):47 request = self._make_request('get_group_counts',48 [['col1', 'Column 1'],49 ['group_count', 'Count in group']])50 response = {'header_values' : 'unused',51 'groups' : [{'col1' : 'foo', 'group_count' : 1},...

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prepro_ptrnet.py

Source: prepro_ptrnet.py Github

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...26dev_index = os.path.join(config['index_dir'], config['dev_tables_index'])27print('Computing Dev Query Embeddings...')28dev_sample_info_dict = test_query_encoder(data['dev_samples_batches'], query_embedding_step)29print('Computing Dev Table Embeddings...')30dev_index_to_vec, dev_id_to_index = test_table_encoder(dev_headers, dev_table_words, dev_all_num_cols, dev_masks,31 dev_table_ids, table_embedding_step)32index_embeddings(dev_index_to_vec, dev_index, dim)33print('Indexing Dev Table Embeddings...')34get_top_k_tables(dev_sample_info_dict, dev_id_to_index, dev_index, dim, k)35test_index = os.path.join(config['index_dir'], config['test_tables_index'])36print('Computing Test Query Embeddings...')37test_sample_info_dict = test_query_encoder(data['test_samples_batches'], query_embedding_step)38print('Computing Test Table Embeddings...')39test_index_to_vec, test_id_to_index = test_table_encoder(test_headers, test_table_words, test_all_num_cols, test_masks,40 test_table_ids, table_embedding_step)41index_embeddings(test_index_to_vec, test_index, dim)42print('Indexing Test Table Embeddings...')43get_top_k_tables(test_sample_info_dict, test_id_to_index, test_index, dim, k)44train_index = os.path.join(config['index_dir'], config['train_tables_index'])45print('Computing Train Query Embeddings...')46train_sample_info_dict = test_query_encoder(data['train_samples_batches'], query_embedding_step)47print('Computing Train Table Embeddings...')48train_index_to_vec, train_id_to_index = test_table_encoder(train_headers, train_table_words, train_all_num_cols,49 train_masks, train_table_ids, table_embedding_step)50index_embeddings(train_index_to_vec, train_index, dim)51print('Indexing Train Table Embeddings...')52get_top_k_tables(train_sample_info_dict, train_id_to_index, train_index, dim, k)53dev_batches = create_ptrnet_dataset(dev_sample_info_dict, batch_size)54test_batches = create_ptrnet_dataset(test_sample_info_dict, batch_size)55train_batches = create_ptrnet_dataset(train_sample_info_dict, batch_size)56all_data = {57 'train_batches': train_batches,58 'dev_batches': dev_batches,59 'test_batches': test_batches,60 'train_index_to_vec': train_index_to_vec,61 'dev_index_to_vec': dev_index_to_vec,62 'test_index_to_vec': test_index_to_vec...

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