# Path: cam/sgnmt/utils.py
# GO_ID = 1
# EOS_ID = 2
# UNK_ID = 0
# NOTAPPLICABLE_ID = 3
# NEG_INF = float("-inf")
# INF = float("inf")
# EPS_P = 0.00001
#     GO_ID = 0
#     EOS_ID = 2
#     UNK_ID = 3
#     GO_ID = 2 # Usually not used
#     EOS_ID = 1
#     UNK_ID = 3 # Don't rely on this: UNK not standardized in T2T
# TMP_FILENAME = '/tmp/sgnmt.%s.fst' % os.getpid()
# MESSAGE_TYPE_DEFAULT = 1
# MESSAGE_TYPE_POSTERIOR = 2
# MESSAGE_TYPE_FULL_HYPO = 3
# def switch_to_fairseq_indexing():
# def switch_to_t2t_indexing():
# def log_sum_tropical_semiring(vals):
# def log_sum_log_semiring(vals):
# def oov_to_unk(seq, vocab_size, unk_idx=None):
# def argmax_n(arr, n):
# def argmax(arr):
# def common_viewkeys(obj):
# def common_iterable(obj):
# def common_get(obj, key, default):
# def common_contains(obj, key):
# def w2f(fstweight):
# def load_fst(path):
# def get_path(tmpl, sub = 1):
# def split_comma(s, func=None):
#     def notify(self, message, message_type = MESSAGE_TYPE_DEFAULT):
#     def __init__(self):
#     def add_observer(self, observer):
#     def notify_observers(self, message, message_type = MESSAGE_TYPE_DEFAULT):
# class Observer(object):
# class Observable(object):
# 
# Path: cam/sgnmt/io.py
# def encode(src_sentence):
# def decode(trg_sentence):
# def initialize(args):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def __init__(self, codes_path, separator='@@', remove_eow=False):
#     def process_line(self, line):
#     def segment(self, sentence):
#     def segment_tokens(self, tokens):
#     def get_pairs(self, word):
#     def encode(self, orig):
#     def __init__(self, codes_path, separator='', remove_eow=False):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def decode(self, trg_sentence):
# def load_src_wmap(path):
# def load_trg_wmap(path):
# class Encoder(object):
# class Decoder(object):
# class IDEncoder(Encoder):
# class IDDecoder(Decoder):
# class WordEncoder(Encoder):
# class WordDecoder(Decoder):
# class CharEncoder(Encoder):
# class CharDecoder(Decoder):
# class BPE(object):
# class BPEEncoder(Encoder):
# class BPEDecoder(Decoder):
# class BPEAtAtDecoder(Decoder):


from abc import abstractmethod
from cam.sgnmt import utils
from cam.sgnmt import io
from collections import defaultdict
import os
import errno
import logging
import numpy as np
import codecs
    import pywrapfst as fst
        import openfst_python as fst
    def __init__(self, path, predictor_names):
        """Creates a Moses n-best list output handler.
        
        Args:
            path (string):  Path to the n-best file to write
            predictor_names: Names of the predictors whose scores
                             should be included in the score breakdown
                             in the n-best list
        """
        super(NBestOutputHandler, self).__init__()
        self.path = path
        self.predictor_names = []
        name_count = {}
        for name in predictor_names:
            if not name in name_count:
                name_count[name] = 1
                final_name = name
            else:
                name_count[name] += 1
                final_name = "%s%d" % (name, name_count[name])
            self.predictor_names.append(final_name.replace("_", "0"))
        
    def write_hypos(self, all_hypos, sen_indices):
        """Writes the hypotheses in ``all_hypos`` to ``path`` """
        with codecs.open(self.path, "w", encoding='utf-8') as f:
            n_predictors = len(self.predictor_names)
            for idx, hypos in zip(sen_indices, all_hypos):
                for hypo in hypos:
                    f.write("%d ||| %s ||| %s ||| %f" %
                            (idx,

# Path: cam/sgnmt/utils.py
# GO_ID = 1
# EOS_ID = 2
# UNK_ID = 0
# NOTAPPLICABLE_ID = 3
# NEG_INF = float("-inf")
# INF = float("inf")
# EPS_P = 0.00001
#     GO_ID = 0
#     EOS_ID = 2
#     UNK_ID = 3
#     GO_ID = 2 # Usually not used
#     EOS_ID = 1
#     UNK_ID = 3 # Don't rely on this: UNK not standardized in T2T
# TMP_FILENAME = '/tmp/sgnmt.%s.fst' % os.getpid()
# MESSAGE_TYPE_DEFAULT = 1
# MESSAGE_TYPE_POSTERIOR = 2
# MESSAGE_TYPE_FULL_HYPO = 3
# def switch_to_fairseq_indexing():
# def switch_to_t2t_indexing():
# def log_sum_tropical_semiring(vals):
# def log_sum_log_semiring(vals):
# def oov_to_unk(seq, vocab_size, unk_idx=None):
# def argmax_n(arr, n):
# def argmax(arr):
# def common_viewkeys(obj):
# def common_iterable(obj):
# def common_get(obj, key, default):
# def common_contains(obj, key):
# def w2f(fstweight):
# def load_fst(path):
# def get_path(tmpl, sub = 1):
# def split_comma(s, func=None):
#     def notify(self, message, message_type = MESSAGE_TYPE_DEFAULT):
#     def __init__(self):
#     def add_observer(self, observer):
#     def notify_observers(self, message, message_type = MESSAGE_TYPE_DEFAULT):
# class Observer(object):
# class Observable(object):
# 
# Path: cam/sgnmt/io.py
# def encode(src_sentence):
# def decode(trg_sentence):
# def initialize(args):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def __init__(self, codes_path, separator='@@', remove_eow=False):
#     def process_line(self, line):
#     def segment(self, sentence):
#     def segment_tokens(self, tokens):
#     def get_pairs(self, word):
#     def encode(self, orig):
#     def __init__(self, codes_path, separator='', remove_eow=False):
#     def encode(self, src_sentence):
#     def decode(self, trg_sentence):
#     def decode(self, trg_sentence):
# def load_src_wmap(path):
# def load_trg_wmap(path):
# class Encoder(object):
# class Decoder(object):
# class IDEncoder(Encoder):
# class IDDecoder(Decoder):
# class WordEncoder(Encoder):
# class WordDecoder(Decoder):
# class CharEncoder(Encoder):
# class CharDecoder(Decoder):
# class BPE(object):
# class BPEEncoder(Encoder):
# class BPEDecoder(Decoder):
# class BPEAtAtDecoder(Decoder):


# Path: cam/sgnmt/output.py
from abc import abstractmethod
from cam.sgnmt import utils
from cam.sgnmt import io
from collections import defaultdict
import os
import errno
import logging
import numpy as np
import codecs
    import pywrapfst as fst
        import openfst_python as fst

    def __init__(self, path, predictor_names):
        """Creates a Moses n-best list output handler.
        
        Args:
            path (string):  Path to the n-best file to write
            predictor_names: Names of the predictors whose scores
                             should be included in the score breakdown
                             in the n-best list
        """
        super(NBestOutputHandler, self).__init__()
        self.path = path
        self.predictor_names = []
        name_count = {}
        for name in predictor_names:
            if not name in name_count:
                name_count[name] = 1
                final_name = name
            else:
                name_count[name] += 1
                final_name = "%s%d" % (name, name_count[name])
            self.predictor_names.append(final_name.replace("_", "0"))
        
    def write_hypos(self, all_hypos, sen_indices):
        """Writes the hypotheses in ``all_hypos`` to ``path`` """
        with codecs.open(self.path, "w", encoding='utf-8') as f:
            n_predictors = len(self.predictor_names)
            for idx, hypos in zip(sen_indices, all_hypos):
                for hypo in hypos:
                    f.write("%d ||| %s ||| %s ||| %f" %
                            (idx,

                             io.decode(hypo.trgt_sentence),