id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
38,193 | import collections
import math
import paddle
import paddle.distributed.auto_parallel as auto
import paddle.incubate as incubate
import paddle.nn as nn
import paddle.nn.functional as F
import paddle.tensor as tensor
from paddle.common_ops_import import convert_dtype
from paddle.base import layers
from paddle.nn.layer.tr... | null |
38,194 | import argparse
import multiprocessing
import os
import time
import warnings
from multiprocessing import Process
def read_command(shell_cmd_list_filename):
shell_cmd_list = []
with open(shell_cmd_list_filename, "r") as f:
for cmd in f:
cmd = cmd.strip()
shell_cmd_list.append(cmd... | null |
38,195 | import argparse
import multiprocessing
import os
import time
import warnings
from multiprocessing import Process
def process_fn(cmd_list):
for cmd in cmd_list:
try:
ret = os.system(cmd)
if ret != 0:
raise Exception(f"execute command: {cmd} failed.")
except Exc... | null |
38,196 | import paddle
from ppfleetx.utils.log import logger
import paddle
paddle.framework.io.EagerParamBase.to = to
logger = Logger()
def version_check():
version = paddle.version.full_version
logger.info("run with paddle {}, commit id {}".format(paddle.__version__, paddle.__git_commit__[:8]))
if version != "... | null |
38,197 | import os
import paddle
from .log import logger
def _prune_input_spec(input_spec, program, targets):
# try to prune static program to figure out pruned input spec
# so we perform following operations in static mode
device = paddle.get_device()
paddle.enable_static()
paddle.set_device(device)
pru... | null |
38,198 | from collections import OrderedDict
import numpy as np
import paddle
from paddle.distributed.fleet.meta_parallel.sharding.group_sharded_storage import (
GradStorage,
ParamStorage,
)
from paddle.distributed.fleet.meta_parallel.sharding.group_sharded_utils import Type
from paddle.framework import core
def obtain_... | null |
38,199 | from collections import OrderedDict
import numpy as np
import paddle
from paddle.distributed.fleet.meta_parallel.sharding.group_sharded_storage import (
GradStorage,
ParamStorage,
)
from paddle.distributed.fleet.meta_parallel.sharding.group_sharded_utils import Type
from paddle.framework import core
import pad... | null |
38,200 | import csv
import os
import tarfile
import zipfile
from typing import Callable, Iterable
from ppfleetx.distributed.apis import env
def unzip(zip_path, mode="r", out_dir=None, delete=False):
with zipfile.ZipFile(zip_path, mode) as zip_ref:
zip_ref.extractall(out_dir)
if delete:
os.remove(zip_pa... | null |
38,201 | import csv
import os
import tarfile
import zipfile
from typing import Callable, Iterable
from ppfleetx.distributed.apis import env
def untar(tar_path, mode="r:gz", out_dir=None, delete=False):
try:
with tarfile.open(tar_path, "r:gz") as f:
f.extractall(out_dir)
finally:
if delete:
... | null |
38,202 | import csv
import os
import tarfile
import zipfile
from typing import Callable, Iterable
from ppfleetx.distributed.apis import env
def parse_csv(
path, skip_lines=0, delimiter=" ", quotechar="|", quoting=csv.QUOTE_NONE, map_funcs=None, filter_funcs=None
):
with open(path, newline="") as csvfile:
data ... | null |
38,203 | import argparse
import codecs
import copy
import os
import sys
import paddle
import paddle.distributed as dist
import yaml
from paddle.base.reader import use_pinned_memory
from . import check
from .log import advertise, logger
def process_dist_config(configs):
"""
process distributed strategy for hybrid paralle... | Read config from file |
38,204 | import argparse
import codecs
import copy
import os
import sys
import paddle
import paddle.distributed as dist
import yaml
from paddle.base.reader import use_pinned_memory
from . import check
from .log import advertise, logger
def parse_args():
parser = argparse.ArgumentParser("train script")
parser.add_argume... | null |
38,205 | import os
import shutil
import time
import paddle
import requests
from ppfleetx.utils.log import logger
from tqdm import tqdm
def is_url(path):
"""
Whether path is URL.
Args:
path (string): URL string or not.
"""
return path.startswith("http://") or path.startswith("https://")
def _map_path(... | null |
38,206 | import paddle
import paddleslim
def get_pruned_params(model):
params = []
for sublayer in model.sublayers():
for param in sublayer.parameters(include_sublayers=False):
if (
isinstance(sublayer, paddle.nn.layer.common.Linear)
or isinstance(sublayer, paddle.dist... | null |
38,207 | import paddle
import paddleslim
def quant_model(model, configs):
quanter = paddleslim.dygraph.quant.QAT(configs)
return quanter.quantize(model), quanter | null |
38,208 | import contextlib
import datetime
import functools
import logging
import threading
import time
import colorlog
logger = Logger()
from .device import synchronize
def synchronize():
def get_timestamp():
if synchronize():
return time.time()
else:
logger.warning("Device synchronizing failed, which... | null |
38,209 | import contextlib
import datetime
import functools
import logging
import threading
import time
import colorlog
from .device import synchronize
def convert_timestamp_to_data(timeStamp):
return str(datetime.timedelta(seconds=int(timeStamp))) | null |
38,210 | import argparse
import os
import sys
import paddle
import paddle.distributed as dist
import paddle.distributed.auto_parallel as auto
from .config import (
AttrDict,
check_config,
create_attr_dict,
override_config,
parse_config,
print_config,
)
from .log import logger
def process_dist_configs(con... | Read config from file for auto parallel |
38,211 | import argparse
import os
import sys
import paddle
import paddle.distributed as dist
import paddle.distributed.auto_parallel as auto
from .config import (
AttrDict,
check_config,
create_attr_dict,
override_config,
parse_config,
print_config,
)
from .log import logger
def parse_args():
parse... | null |
38,212 | from __future__ import absolute_import, division, print_function
import os
import sys
import paddle
import paddle.distributed as dist
from ppfleetx.core import EagerEngine
from ppfleetx.data import build_dataloader
from ppfleetx.distributed.apis import env
from ppfleetx.models import build_module
from ppfleetx.ops.fuse... | null |
38,213 | import argparse
import os
import random
import time
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import paddle
from paddle.io import DataLoader
from paddlenlp.data import Pad, Tuple
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import (
BertForSequenceClassifi... | null |
38,214 | import argparse
import os
import random
import time
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import paddle
from paddle.io import DataLoader
from paddlenlp.data import Pad, Tuple
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import (
BertForSequenceClassifi... | null |
38,215 | import argparse
import os
import random
import time
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import paddle
from paddle.io import DataLoader
from paddlenlp.data import Pad, Tuple
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import (
BertForSequenceClassifi... | print arguments |
38,216 | import argparse
import logging
import math
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from pad... | null |
38,217 | import argparse
import logging
import math
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from pad... | null |
38,218 | import argparse
import logging
import math
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from pad... | print arguments |
38,219 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddleslim.nas.ofa import OFA, DistillConfig, RunConfig, utils
from paddleslim.nas.ofa.... | null |
38,220 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddleslim.nas.ofa import OFA, DistillConfig, RunConfig, utils
from paddleslim.nas.ofa.... | null |
38,221 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddleslim.nas.ofa import OFA, DistillConfig, RunConfig, utils
from paddleslim.nas.ofa.... | null |
38,222 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddleslim.nas.ofa import OFA, DistillConfig, RunConfig, utils
from paddleslim.nas.ofa.... | null |
38,223 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddleslim.nas.ofa import OFA, DistillConfig, RunConfig, utils
from paddleslim.nas.ofa.... | null |
38,224 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddleslim.nas.ofa import OFA, DistillConfig, RunConfig, utils
from paddleslim.nas.ofa.... | print arguments |
38,225 | import argparse
import json
import math
import os
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import (
BertForSequenceClassification,
BertModel,
BertTokenizer,
)
def bert_forward(
self, input_ids, tok... | null |
38,226 | import argparse
import json
import math
import os
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import (
BertForSequenceClassification,
BertModel,
BertTokenizer,
)
MODEL_CLASSES = {
"bert": (BertForSeque... | null |
38,227 | import argparse
import json
import math
import os
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import (
BertForSequenceClassification,
BertModel,
BertTokenizer,
)
MODEL_CLASSES = {
"bert": (BertForSeque... | null |
38,228 | import argparse
import json
import math
import os
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import (
BertForSequenceClassification,
BertModel,
BertTokenizer,
)
The provided code snippet includes necessa... | print arguments |
38,229 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
fro... | null |
38,230 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
fro... | null |
38,231 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
fro... | null |
38,232 | import argparse
import math
import os
import random
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddle.metric import Accuracy
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
fro... | print arguments |
38,233 | import argparse
import json
import math
import os
import sys
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import PPMiniLMModel
from data import METRIC_CLASSES, MODEL_CLASSES
def ppminilm_forward(self, input_ids, token... | null |
38,234 | import argparse
import json
import math
import os
import sys
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import PPMiniLMModel
from data import METRIC_CLASSES, MODEL_CLASSES
MODEL_CLASSES = {
"ppminilm": (PPMiniLM... | null |
38,235 | import argparse
import json
import math
import os
import sys
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import PPMiniLMModel
from data import METRIC_CLASSES, MODEL_CLASSES
MODEL_CLASSES = {
"ppminilm": (PPMiniLM... | null |
38,236 | import argparse
import json
import math
import os
import sys
import paddle
from paddleslim.nas.ofa import OFA, utils
from paddleslim.nas.ofa.convert_super import Convert, supernet
from paddlenlp.transformers import PPMiniLMModel
from data import METRIC_CLASSES, MODEL_CLASSES
The provided code snippet includes necessar... | print arguments |
38,237 | import argparse
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddleslim.nas.ofa import OFA, DistillConfig, utils
from paddleslim.nas.ofa.convert_supe... | null |
38,238 | import argparse
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddleslim.nas.ofa import OFA, DistillConfig, utils
from paddleslim.nas.ofa.convert_supe... | null |
38,239 | import argparse
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddleslim.nas.ofa import OFA, DistillConfig, utils
from paddleslim.nas.ofa.convert_supe... | null |
38,240 | import argparse
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from paddle.io import DataLoader
from paddleslim.nas.ofa import OFA, DistillConfig, utils
from paddleslim.nas.ofa.convert_supe... | print arguments |
38,241 | import argparse
import sys
import time
from functools import partial
import paddle
from paddle import inference
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer.argparser import strtobool
from data import METRIC_CLASSES, MODEL_CLASSES, convert_example
def ... | null |
38,242 | import argparse
import sys
import time
from functools import partial
import paddle
from paddle import inference
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer.argparser import strtobool
from data import METRIC_CLASSES, MODEL_CLASSES, convert_example
def ... | null |
38,243 | import argparse
import os
import sys
import paddle
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import PPMiniLMForSequenceClassification
from data import METRIC_CLASSES
def strtobool(v):
if isinstance(v, bool):
return v
if v.lower() in ("yes", "true", "t", "y", "1"):
... | null |
38,244 | import argparse
import os
import sys
import paddle
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import PPMiniLMForSequenceClassification
from data import METRIC_CLASSES
def do_export(args):
save_path = os.path.join(os.path.dirname(args.model_path), "inference")
model = PPMiniLM... | null |
38,245 | import argparse
import os
import sys
import paddle
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import PPMiniLMForSequenceClassification
from data import METRIC_CLASSES
The provided code snippet includes necessary dependencies for implementing the `print_arguments` function. Write a Py... | print arguments |
38,246 | import argparse
import logging
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer... | null |
38,247 | import argparse
import logging
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer... | null |
38,248 | import argparse
import logging
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer... | null |
38,249 | import argparse
import logging
import math
import os
import random
import sys
import time
from functools import partial
import numpy as np
import paddle
import paddle.nn as nn
from paddle.io import DataLoader
from paddlenlp.data import Pad, Stack, Tuple
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer... | print arguments |
38,250 | import argparse
import os
import random
import time
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import paddle
from paddle.io import DataLoader
from paddlenlp.data import Pad, Tuple
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import (
LinearDecayWithWarmup,
... | null |
38,251 | import argparse
import os
import random
import time
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import paddle
from paddle.io import DataLoader
from paddlenlp.data import Pad, Tuple
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import (
LinearDecayWithWarmup,
... | null |
38,252 | import argparse
import os
import random
import time
from concurrent.futures import ThreadPoolExecutor
import numpy as np
import paddle
from paddle.io import DataLoader
from paddlenlp.data import Pad, Tuple
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import (
LinearDecayWithWarmup,
... | print arguments |
38,253 | import argparse
import os
import sys
from functools import partial
import paddle
import paddleslim
from paddlenlp.data import Pad
from paddlenlp.datasets import load_dataset
from paddlenlp.trainer.argparser import strtobool
from paddlenlp.transformers import PPMiniLMTokenizer
from data import convert_example
def conve... | null |
38,254 | import os
import argparse
from paddlenlp.utils.env import MODEL_HOME
MODEL_HOME = _get_sub_home("models")
def parse_args():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--task_name", type=str, default="sst-2", help="Task name.")
parser.add_argument(
"--optimizer", t... | null |
38,255 | import os
import time
import paddle
import paddle.nn as nn
from args import parse_args
from data import create_distill_loader
from paddle.metric import Accuracy
from small import BiLSTM
from paddlenlp.metrics import AccuracyAndF1
from paddlenlp.transformers import BertForSequenceClassification
METRIC_CLASSES = {"sst-2"... | null |
38,256 | import os
import time
import paddle
import paddle.nn as nn
import paddle.nn.initializer as I
from args import parse_args
from data import create_data_loader_for_small_model, create_pair_loader_for_small_model
from paddle.metric import Accuracy
from paddlenlp.embeddings import TokenEmbedding
from paddlenlp.metrics impor... | null |
38,257 | import argparse
import os
import os.path as osp
from functools import partial
import data
import paddle
import paddle.nn as nn
import paddlenlp
from paddlenlp.data import Pad, Stack, Tuple, Vocab
from paddlenlp.datasets import load_dataset
from paddlenlp.embeddings import TokenEmbedding
from paddlenlp.utils.downloader ... | Creats dataloader. Args: dataset(obj:`paddle.io.Dataset`): Dataset instance. mode(obj:`str`, optional, defaults to obj:`train`): If mode is 'train', it will shuffle the dataset randomly. batch_size(obj:`int`, optional, defaults to 1): The sample number of a mini-batch. pad_token_id(obj:`int`, optional, defaults to 0): ... |
38,258 | import jieba
import numpy as np
from paddlenlp.data import JiebaTokenizer
tokenizer = jieba
def set_tokenizer(vocab):
global tokenizer
if vocab is not None:
tokenizer = JiebaTokenizer(vocab=vocab) | null |
38,259 | import jieba
import numpy as np
from paddlenlp.data import JiebaTokenizer
The provided code snippet includes necessary dependencies for implementing the `load_vocab` function. Write a Python function `def load_vocab(vocab_file)` to solve the following problem:
Loads a vocabulary file into a dictionary.
Here is the fu... | Loads a vocabulary file into a dictionary. |
38,260 | import jieba
import numpy as np
from paddlenlp.data import JiebaTokenizer
tokenizer = jieba
The provided code snippet includes necessary dependencies for implementing the `convert_example` function. Write a Python function `def convert_example(example, vocab, unk_token_id=1, is_test=False)` to solve the following prob... | Builds model inputs from a sequence for sequence classification tasks. It use `jieba.cut` to tokenize text. Args: example(obj:`list[str]`): List of input data, containing text and label if it have label. vocab(obj:`dict`): The vocabulary. unk_token_id(obj:`int`, defaults to 1): The unknown token id. is_test(obj:`False`... |
38,261 | import jieba
import numpy as np
from paddlenlp.data import JiebaTokenizer
The provided code snippet includes necessary dependencies for implementing the `pad_texts_to_max_seq_len` function. Write a Python function `def pad_texts_to_max_seq_len(texts, max_seq_len, pad_token_id=0)` to solve the following problem:
Padded... | Padded the texts to the max sequence length if the length of text is lower than it. Unless it truncates the text. Args: texts(obj:`list`): Texts which contains a sequence of word ids. max_seq_len(obj:`int`): Max sequence length. pad_token_id(obj:`int`, optional, defaults to 0) : The pad token index. |
38,262 | import jieba
import numpy as np
from paddlenlp.data import JiebaTokenizer
tokenizer = jieba
def convert_tokens_to_ids(tokens, vocab):
"""Converts a token id (or a sequence of id) in a token string
(or a sequence of tokens), using the vocabulary.
"""
ids = []
unk_id = vocab.get("[UNK]", None)
for... | It process the prediction data as the format used as training. Args: data (obj:`List[str]`): The prediction data whose each element is a tokenized text. Returns: examples (obj:`List(Example)`): The processed data whose each element is a Example (numedtuple) object. A Example object contains `text`(word_ids) and `seq_le... |
38,263 | import paddle
import paddle.nn as nn
from args import parse_args
from data import create_train_loader
from seq2seq_attn import CrossEntropyCriterion, Seq2SeqAttnModel
from paddlenlp.metrics import Perplexity
def create_train_loader(args):
batch_size = args.batch_size
max_len = args.max_len
train_ds, dev_d... | null |
38,264 | import argparse
def parse_args():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--learning_rate", type=float, default=0.001, help="learning rate for optimizer")
parser.add_argument("--num_layers", type=int, default=1, help="layers number of encoder and decoder")
parser.a... | null |
38,265 | import io
import numpy as np
import paddle
from args import parse_args
from data import create_infer_loader
from seq2seq_attn import Seq2SeqAttnInferModel
from paddlenlp.data import Vocab
from paddlenlp.metrics import BLEU
def post_process_seq(seq, bos_idx, eos_idx, output_bos=False, output_eos=False):
def create_infe... | null |
38,266 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def get_preprocessing_parser():
parser = argparse.ArgumentParser()
parser.add_argument("-s", "--src_lang", default=None, type=str, help="S... | null |
38,267 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def _dev_path(lang, dev_pref):
return "{}{}".format(dev_pref, ("." + lang) if lang else "") | null |
38,268 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def _test_path(lang, test_pref):
return "{}{}".format(test_pref, ("." + lang) if lang else "") | null |
38,269 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def _dest_path(prefix, lang, dest_dir):
return os.path.join(dest_dir, _file_name(prefix, lang))
def _dict_path(lang, dest_dir):
return _des... | null |
38,270 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def _build_dictionary(filenames, args, src=False, trg=False):
assert src ^ trg, "src and trg cannot be both True or both False. "
if not i... | null |
38,271 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def _make_dataset(vocab, input_prefix, output_prefix, lang, args):
def _make_all(lang, vocab, args):
if args.train_pref:
_make_dataset(... | null |
38,272 | import argparse
import os
import shutil
from itertools import zip_longest
from pprint import pprint
from paddlenlp.data import Vocab
from paddlenlp.utils.log import logger
def _train_path(lang, train_pref):
return "{}{}".format(train_pref, ("." + lang) if lang else "")
def _align_files(args, src_vocab, trg_vocab):... | null |
38,273 | import argparse
import inspect
import os
import time
from pprint import pprint
import numpy as np
import paddle
import paddle.distributed as dist
import reader
import yaml
from easydict import EasyDict as AttrDict
from tls.record import AverageStatistical
from tls.to_static import apply_to_static
from paddlenlp.transfo... | null |
38,274 | import argparse
import inspect
import os
import time
from pprint import pprint
import numpy as np
import paddle
import paddle.distributed as dist
import reader
import yaml
from easydict import EasyDict as AttrDict
from tls.record import AverageStatistical
from tls.to_static import apply_to_static
from paddlenlp.transfo... | null |
38,275 | import argparse
from pprint import pprint
import numpy as np
import yaml
from easydict import EasyDict as AttrDict
from transformer_reader import TransformerReader
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--config", default="../configs/transformer.big.yaml", type=str, ... | null |
38,276 | import argparse
from pprint import pprint
import numpy as np
import yaml
from easydict import EasyDict as AttrDict
from transformer_reader import TransformerReader
The provided code snippet includes necessary dependencies for implementing the `post_process_seq` function. Write a Python function `def post_process_seq(s... | Post-process the decoded sequence. |
38,277 | import argparse
from pprint import pprint
import numpy as np
import yaml
from easydict import EasyDict as AttrDict
from transformer_reader import TransformerReader
class TransformerService(WebService):
def init_client(self, args):
self.args = args
self.transformer_reader = TransformerReader(args=arg... | null |
38,278 | import sys
import yaml
def parse_benchmark(filein, fileout):
with open(filein, "r") as fin:
res = yaml.load(fin)
del_list = []
for key in res["DAG"].keys():
if "call" in key:
del_list.append(key)
for key in del_list:
del res["DAG"][key]
wi... | null |
38,279 | import argparse
import json
from pprint import pprint
import requests
import yaml
from easydict import EasyDict as AttrDict
from paddle_serving_client.utils import MultiThreadRunner
from paddlenlp.datasets import load_dataset
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--... | null |
38,280 | import argparse
import json
from pprint import pprint
import requests
import yaml
from easydict import EasyDict as AttrDict
from paddle_serving_client.utils import MultiThreadRunner
from paddlenlp.datasets import load_dataset
def do_client(idx, args):
def multithread_http(args):
multi_thread_runner = MultiThreadRu... | null |
38,281 | import argparse
import paddle
import paddle_serving_client.io as serving_io
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--model_dir", type=str, required=True, help="input inference model dir")
return parser.parse_args() | null |
38,282 | import argparse
import paddle
import paddle_serving_client.io as serving_io
def do_export(model_dir):
feed_names, fetch_names = serving_io.inference_model_to_serving(
dirname=model_dir,
serving_server="transformer_server",
serving_client="transformer_client",
model_filename="transfo... | null |
38,283 | import argparse
import os
import sys
from pprint import pprint
import paddle
import yaml
from easydict import EasyDict as AttrDict
from paddle import inference
from paddlenlp.utils.log import logger
import reader
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--batch_size", type=int,... | null |
38,284 | import argparse
import os
import sys
from pprint import pprint
import paddle
import yaml
from easydict import EasyDict as AttrDict
from paddle import inference
from paddlenlp.utils.log import logger
import reader
The provided code snippet includes necessary dependencies for implementing the `post_process_seq` function... | Post-process the decoded sequence. |
38,285 | import argparse
import os
import sys
from pprint import pprint
import paddle
import yaml
from easydict import EasyDict as AttrDict
from paddle import inference
from paddlenlp.utils.log import logger
import reader
class Predictor(object):
def __init__(self, predictor, input_handles, output_handles, autolog=None):
... | null |
38,286 | import argparse
import os
from pprint import pprint
import paddle
import reader
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.transformers import InferTransformerModel, position_encoding_init
from paddlenlp.utils.log import logger
def parse_args():
parser = argparse.ArgumentParser()
pars... | null |
38,287 | import argparse
import os
from pprint import pprint
import paddle
import reader
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.transformers import InferTransformerModel, position_encoding_init
from paddlenlp.utils.log import logger
logger = Logger()
def do_export(args):
# Adapt vocabulary si... | null |
38,288 | import argparse
import os
from pprint import pprint
import paddle
import reader
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.ops import TransformerGenerator
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--config", default="./configs/transformer.big.y... | null |
38,289 | import argparse
import os
from pprint import pprint
import paddle
import reader
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.ops import TransformerGenerator
def post_process_seq(seq, bos_idx, eos_idx, output_bos=False, output_eos=False):
"""
Post-process the decoded sequence.
"""
... | null |
38,290 | import argparse
import os
import sys
from pprint import pprint
import paddle
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.ops import FasterTransformer
from paddlenlp.utils.log import logger
import reader
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"... | null |
38,291 | import argparse
import os
import sys
from pprint import pprint
import paddle
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.ops import FasterTransformer
from paddlenlp.utils.log import logger
import reader
logger = Logger()
def do_predict(args):
place = "gpu"
place = paddle.set_device(pl... | null |
38,292 | import argparse
import os
import sys
from pprint import pprint
import numpy as np
import paddle
import yaml
from easydict import EasyDict as AttrDict
from paddlenlp.ops import FasterTransformer
from paddlenlp.utils.log import logger
import reader
def parse_args():
parser = argparse.ArgumentParser()
parser.add_... | null |
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