How to use load_files method in yandex-tank

Best Python code snippet using yandex-tank

mt_inference.py

Source:mt_inference.py

...9    10    word2idx_input_path = confFile.WORD2IDX_INPUTS11    word2idx_output_path = confFile.WORD2IDX_TARGET12    13    word2idx_input = load_files(word2idx_input_path)14    word2idx_target = load_files(word2idx_output_path)15    idx2word_input = {v:k for k, v in word2idx_input.items()}16    idx2word_trans = {v:k for k, v in word2idx_target.items()}17    enc_out = encoder_model.predict(input_sequence)18    target_seq = np.zeros((1, 1))19    target_seq[0, 0] = word2idx_target['sos']20    eos = word2idx_target['eos']21    22    s = np.zeros((1, confFile.LATENT_DIM))23    c = np.zeros((1, confFile.LATENT_DIM))24    output_sentence = []25    for _ in range(max_len_target):26        o, s, c = decoder_model.predict([target_seq, enc_out, s, c])27        idx = np.argmax(o.flatten())28        # End sentence of EOS29        if eos == idx:30            break31        word = ''32        if idx > 0:33            word = idx2word_trans[idx]34            output_sentence.append(word)35        target_seq[0, 0] = idx36    return ' '.join(output_sentence)37    38def test(string, infrence_models):39    tokenizerpath = confFile.TOKENIZER_INPUT_PATH40    max_len_input_path = confFile.MAX_LEN_INPUT41    max_len_input = load_files(max_len_input_path)42    tokenizer_input = load_files(tokenizerpath)43    string_seq=tokenizer_input.texts_to_sequences([string])44    string_seq=pad_sequences(string_seq,maxlen=max_len_input)45    translation=decode_sequence(string_seq, infrence_models[0], infrence_models[1])46    47    return translation48Model = ModelBuilding()49embedding_matrix = load_files(confFile.EMBEDDING_MATRIX_PATH)50max_len_target_path = confFile.MAX_LEN_TARGET51max_len_input_path = confFile.MAX_LEN_INPUT52model_weights_path = confFile.WEIGHTS_PATH53max_len_target = load_files(max_len_target_path)54max_len_input = load_files(max_len_input_path)55num_words = load_files(confFile.NUM_WORDS)56num_words_output = load_files(confFile.NUM_WORDS_OUTPUT)57model = Model.EncDecbuild(num_words, confFile.LATENT_DIM, confFile.EMBEDDING_DIM, embedding_matrix, max_len_input, max_len_target, num_words_output)58model.load_weights(model_weights_path)59infrence_models = Model.encoderDecoderModel(max_len_input, confFile.LATENT_DIM)60translation = test("tom is laughing", infrence_models)61print(translation)...

prolog.py

Source:prolog.py

...4def yap(action,load_files,outfile=None,timeout=None):5    call('yap',action,load_files,outfile,timeout)6def call(prolog_version,action,load_files,outfile=None,timeout=None):7    load_files = map(lambda x: "'{}'".format(x),load_files)8    cmd = "load_files([{}],[silent(true)]). ".format(','.join(load_files))9    cmd+=action10    if outfile == None:11        p = subprocess.Popen([prolog_version,'-q'], stdin=subprocess.PIPE)12        call_p(p,cmd,timeout)13    else:14        with open(outfile, 'w') as outf:15            p = subprocess.Popen([prolog_version,'-q','-G8g'], stdin=subprocess.PIPE, stdout=outf)16            call_p(p,cmd,timeout)17def call_p(p,cmd,timeout):18    try:19        print(cmd)20        p.stdin.write(cmd.encode())21        p.communicate(timeout=timeout)22    except Exception as e:...

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