python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
|---|---|---|
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
from io import open
from setuptools import find_packages, setup
setup(
name="torchscale",
version="0.1.1",
author="TorchScale Team",
author_email="Shuming.Ma@microsoft.com",
description="Transformers at any ... | KosmosX-API-main | kosmosX/torchscale/setup.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/torchscale/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch
import torch.nn as nn
def fixed_pos_embedding(x):
seq_len, dim = x.shape
inv_freq = 1.0 / (10000 ** (torch.arange(0, dim) / dim))
sinusoid_inp = (
torch.einsum("i , j -> i j", torch.arange(0, se... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/sope_relative_position.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import copy
import torch
import torch.nn as nn
def MultiwayWrapper(args, module, dim=0):
if args.multiway:
return MultiwayNetwork(module, dim=dim)
return module
def set_split_position(position):
def apply... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/multiway_network.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import math
import torch
import torch.nn.functional as F
from apex.normalization import FusedLayerNorm as LayerNorm
from torch import nn
from .multiway_network import MultiwayWrapper
from xformers.ops import memory_efficient_at... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/multihead_attention.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import math
import torch
import torch.nn as nn
class RelativePositionBias(nn.Module):
def __init__(
self, bidirectional=True, num_buckets=32, max_distance=128, n_heads=12
):
super().__init__()
s... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/relative_position_bias.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch
import torch.nn as nn
import torch.nn.functional as F
class VisionLanguageEmbedding(nn.Module):
def __init__(self, text_embed, vision_embed):
super().__init__()
self.text_embed = text_embed
... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/embedding.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch.nn as nn
from timm.models.layers import drop_path
class DropPath(nn.Module):
"""Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks)."""
def __init__(self, drop_prob=Non... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/droppath.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/torchscale/component/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch
import torch.nn as nn
import torch.nn.functional as F
from apex.normalization import FusedLayerNorm as LayerNorm
class set_torch_seed(object):
def __init__(self, seed):
assert isinstance(seed, int)
... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/feedforward_network.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/torchscale/component/xmoe/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
# NOTE: This is a mirror of th... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/xmoe/moe_layer.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
# Implementation of Top2Gating... | KosmosX-API-main | kosmosX/torchscale/torchscale/component/xmoe/routing.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import math
import numpy as np
import torch
import torch.nn as nn
from apex.normalization import FusedLayerNorm as LayerNorm
from fairscale.nn import checkpoint_wrapper, wrap
from torchscale.architecture.utils import init_bert_... | KosmosX-API-main | kosmosX/torchscale/torchscale/architecture/decoder.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
class EncoderConfig(object):
def __init__(self, **kwargs):
self.encoder_embed_dim = kwargs.pop("encoder_embed_dim", 768)
self.encoder_attention_heads = kwargs.pop("encoder_attention_heads", 12)
self.e... | KosmosX-API-main | kosmosX/torchscale/torchscale/architecture/config.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch.nn as nn
from torchscale.architecture.decoder import Decoder
from torchscale.architecture.encoder import Encoder
class EncoderDecoder(nn.Module):
def __init__(
self,
args,
encoder_embed... | KosmosX-API-main | kosmosX/torchscale/torchscale/architecture/encoder_decoder.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/torchscale/architecture/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import math
import numpy as np
import torch
import torch.nn as nn
from apex.normalization import FusedLayerNorm as LayerNorm
from fairscale.nn import checkpoint_wrapper, wrap
from torchscale.architecture.utils import init_bert_... | KosmosX-API-main | kosmosX/torchscale/torchscale/architecture/encoder.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch.nn as nn
from torchscale.component.multihead_attention import MultiheadAttention
from torchscale.component.multiway_network import MultiwayNetwork
def init_bert_params(module):
def normal_(data):
data.... | KosmosX-API-main | kosmosX/torchscale/torchscale/architecture/utils.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch
import torch.nn as nn
from torchscale.architecture.encoder import Encoder
from torchscale.component.embedding import (
PositionalEmbedding,
TextEmbedding,
VisionEmbedding,
)
from torchscale.component.mul... | KosmosX-API-main | kosmosX/torchscale/torchscale/model/BEiT3.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/torchscale/model/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/examples/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# flake8: noqa
import models
import tasks
from fairseq_cli.generate import cli_main
if __name__ == "__main__":
cli_main()
| KosmosX-API-main | kosmosX/torchscale/examples/fairseq/generate.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/examples/fairseq/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# flake8: noqa
import models
import tasks
from fairseq_cli.interactive import cli_main
if __name__ == "__main__":
cli_main()
| KosmosX-API-main | kosmosX/torchscale/examples/fairseq/interactive.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# flake8: noqa
import models
import tasks
from fairseq_cli.train import cli_main
if __name__ == "__main__":
cli_main()
| KosmosX-API-main | kosmosX/torchscale/examples/fairseq/train.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import json
import logging
import os
from argparse import Namespace
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of t... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/pretraining.py |
import os
import json
from argparse import Namespace
import torch
from fairseq import utils
from fairseq.data import Dictionary
from fairseq.tasks import register_task
from fairseq.tasks.language_modeling import LanguageModelingTask, LanguageModelingConfig
from fairseq.data.encoders.gpt2_bpe import GPT2BPE
from datacl... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/gpt_base.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import argparse
import importlib
import os
# register dataclass
TASK_DATACLASS_REGISTRY = {}
TASK_REGISTRY = {}
TASK_CLASS_NAMES = set()
# automatically import any Python files in the tasks/ directory
tasks_dir = os.path.dirnam... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/__init__.py |
import os
import json
from argparse import Namespace
import torch
from fairseq import utils
from fairseq.data import Dictionary
from fairseq.tasks import register_task
from fairseq.tasks.language_modeling import LanguageModelingTask
from fairseq.data.encoders.gpt2_bpe import GPT2BPE
from dataclasses import dataclass, ... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/vl_gpt_base.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import torch
from infinibatch.iterators import CheckpointableIterator
from . import utils
from .utils import ConcatIterator
class BaseBatchGen(CheckpointableIterator):
"""
This is a base class for batch generators that... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/basic_loader.py |
import sys,os
sys.path.append(os.getcwd())
from typing import NamedTuple
import os
import argparse
import json
import sentencepiece as spm
# from fairseq.data.dictionary import Dictionary
# from laion_loader import LaionLoader
def image_code_to_token(code):
return "<image{}>".format(code)
def to_word(item, dict... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/laion_loader_test.py |
import sys,os
sys.path.append(os.getcwd())
from typing import NamedTuple
import os
import argparse
import json
import sentencepiece as spm
from fairseq.data.dictionary import Dictionary
from wild_loader import WildLoader
def image_code_to_token(code):
return "<image{}>".format(code)
def to_word(item, diction... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/wild_loader_test_2.py |
IMAGE_KEY="Images"
TEXT_KEY="Extracted"
import os, json, random, re
max_image_num = 5
tokens_per_sample = 2048
from spacy.lang.en import English
import sentencepiece as spm
nlp_sentencizer = English()
nlp_sentencizer.add_pipe("sentencizer")
spm_tokenizer = spm.SentencePieceProcessor(model_file=r"C:\Users\shaohanh\D... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/wild_loader_test.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/__init__.py |
import json
import os
import random
import re
from infinibatch import iterators
from tasks.data.lm_loader import LMLoader
from tasks.data.utils import NativeCheckpointableIterator, WeightIterator, BOI_SYMBOL, EOI_SYMBOL, image_code_to_token
from fairseq.data.encoders.gpt2_bpe import GPT2BPE
from spacy.lang.en import E... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/wild_loader.py |
import os
import numpy as np
import json
from infinibatch import iterators
from .basic_loader import BaseBatchGen
from .utils import EOL_SYMBOL
from .utils import safe_getattr
class LMLoader(BaseBatchGen):
def __init__(
self,
args,
dataset,
dictionary,
... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/lm_loader.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import collections
from random import Random
from typing import Dict, Iterable, Optional
import numpy as np
from infinibatch import iterators
EOL_SYMBOL = "</line>"
BOI_SYMBOL = "<image>"
EOI_SYMBOL = "</image>"
def apply_to... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/utils.py |
import json
import os
import random
from infinibatch import iterators
from tasks.data.lm_loader import LMLoader
from tasks.data.utils import NativeCheckpointableIterator, WeightIterator, BOI_SYMBOL, EOI_SYMBOL, image_code_to_token
from fairseq.data.encoders.gpt2_bpe import GPT2BPE
class LaionLoader(LMLoader):
de... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/laion_loader.py |
import json
import os
from infinibatch import iterators
from .lm_loader import LMLoader
from .utils import NativeCheckpointableIterator, WeightIterator, EOL_SYMBOL
from fairseq.data.encoders.gpt2_bpe import GPT2BPE
class SpmLmLoader(LMLoader):
def _tokenize(self):
multilingual_iters = []
weights ... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/spm_lm_loader.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import copy
import itertools
import os
import numpy as np
from infinibatch import iterators
from .basic_loader import BaseBatchGen
from .utils import NativeCheckpointableIterator, WeightIterator
class MLMLoader(BaseBatchGen):... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/tasks/data/mlm_loader.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import math
import warnings
import torch
import torch.distributed as dist
from fairseq.utils import multi_tensor_l2norm_available, multi_tensor_total_norm
@torch.no_grad()
def clip_grad_norm_(
params, max_norm, moe_expert_... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/utils/sparse_clip.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
| KosmosX-API-main | kosmosX/torchscale/examples/fairseq/utils/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from dataclasses import dataclass, f... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/models/language_modeling.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import argparse
import importlib
import os
MODEL_REGISTRY = {}
MODEL_DATACLASS_REGISTRY = {}
ARCH_MODEL_REGISTRY = {}
ARCH_MODEL_NAME_REGISTRY = {}
ARCH_MODEL_INV_REGISTRY = {}
ARCH_CONFIG_REGISTRY = {}
# automatically import a... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/models/__init__.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from typing import Dict, List, Optio... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/models/machine_translation.py |
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
import logging
from dataclasses import dataclass, field
from typing import Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from apex.normalization import FusedLayerNorm as LayerNorm
from fairseq impor... | KosmosX-API-main | kosmosX/torchscale/examples/fairseq/models/bert.py |
KosmosX-API-main | kosmosX/unilm/__init__.py | |
import logging
import os
from dataclasses import dataclass, field
import numpy as np
import torch
from fairseq import utils
from fairseq.data import (
FairseqDataset,
AppendTokenDataset,
Dictionary,
IdDataset,
NestedDictionaryDataset,
NumelDataset,
PadDataset,
StripTokenDataset,
T... | KosmosX-API-main | kosmosX/unilm/tasks/generation_obj.py |
import os
from fairseq.tasks import import_tasks
tasks_dir = os.path.dirname(__file__)
import_tasks(tasks_dir, "unilm.tasks")
| KosmosX-API-main | kosmosX/unilm/tasks/__init__.py |
from dataclasses import dataclass, field
import logging
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import checkpoint_utils
from fairseq import utils
from fairseq.utils import safe_getattr
from fairseq.models import (
BaseFairseqModel,
register_model,
register... | KosmosX-API-main | kosmosX/unilm/models/unigpt.py |
import os
from fairseq.models import import_models
models_dir = os.path.dirname(__file__)
import_models(models_dir, "unilm.models") | KosmosX-API-main | kosmosX/unilm/models/__init__.py |
import torch
import torch.nn as nn
from fairseq.modules import MultiheadAttention
from fairseq import utils
def build_connector(args, input_dim, output_dim):
if isinstance(args, str):
connector_name = args
else:
connector_name = args.text_connector if hasattr(args, "text_connector") else args... | KosmosX-API-main | kosmosX/unilm/models/connector.py |
from dataclasses import dataclass, field
from typing import Optional
from torch import Tensor
import torch
from fairseq import distributed_utils
from fairseq.utils import safe_getattr
from fairseq.models import (
register_model,
register_model_architecture,
)
from fairseq.models.transformer_lm import (
Transf... | KosmosX-API-main | kosmosX/unilm/models/gpt.py |
KosmosX-API-main | kosmosX/unilm/models/vl/__init__.py | |
# TODO load openai model | KosmosX-API-main | kosmosX/unilm/models/vl/openai.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Dict, List, Optional
import sys
import torch
import torch.nn as nn
from fairseq import search
from fairseq.mod... | KosmosX-API-main | kosmosX/unilm/models/vl/vlm_generator.py |
import logging
import os
import torch
from copy import deepcopy
from typing import Callable
from torch import nn
from torch.nn import functional as F
from open_clip.model import CLIPVisionCfg, QuickGELU, TimmModel, ModifiedResNet, to_2tuple, LayerNorm, Transformer
from open_clip.factory import _MODEL_CONFIGS, list_mod... | KosmosX-API-main | kosmosX/unilm/models/vl/clip.py |
KosmosX-API-main | kosmosX/unilm/data/__init__.py | |
import numpy as np
from random import Random
from typing import Dict, Iterable, Optional
import collections
from infinibatch import iterators
EOD_SYMBOL = "</doc>"
BOI_SYMBOL = "<image>"
EOI_SYMBOL = "</image>"
EOC_SYMBOL = "</chunk>"
EOL_SYMBOL = "</line>"
GRD_SYMBOL="<grounding>"
BOP_SYMBOL="<phrase>"
EOP_SYMBOL="<... | KosmosX-API-main | kosmosX/unilm/data/utils.py |
from dataclasses import dataclass, field
import math
from omegaconf import II
import torch.nn.functional as F
from fairseq import metrics, utils
from fairseq.criterions import FairseqCriterion, register_criterion
from fairseq.dataclass import FairseqDataclass
LOSS_NAMES = ["gpt", "image_wild", "image_laion"]
@datacl... | KosmosX-API-main | kosmosX/unilm/criterions/unigpt.py |
import importlib
import os
# automatically import any Python files in the criterions/ directory
for file in sorted(os.listdir(os.path.dirname(__file__))):
if file.endswith(".py") and not file.startswith("_"):
file_name = file[: file.find(".py")]
importlib.import_module("unilm.criterions." + file_na... | KosmosX-API-main | kosmosX/unilm/criterions/__init__.py |
from setuptools import setup, find_packages
import site
site.ENABLE_USER_SITE = True
setup(
name='infinibatch',
version='0.1.0',
url='https://github.com/microsoft/infinibatch',
author='Frank Seide',
author_email='fseide@microsoft.com',
description='Infinibatch is a library of checkpointable ite... | KosmosX-API-main | kosmosX/infinibatch/setup.py |
import copy
import itertools
import multiprocessing
from random import Random
import unittest
import torch
from infinibatch.iterators import *
if __name__ == "__main__":
unittest.main()
class TestBase(unittest.TestCase):
def setUp(self):
self.lengths = [1, 2, 3, 42, 57]
self.world_sizes = [... | KosmosX-API-main | kosmosX/infinibatch/test/test_iterators.py |
import gzip
import itertools
from random import Random
import os
import shutil
import tempfile
from typing import Iterator
import unittest
import gc
from infinibatch.datasets import chunked_dataset_iterator
class TestBase(unittest.TestCase):
def setUp(self):
self.test_data = [
["item number o... | KosmosX-API-main | kosmosX/infinibatch/test/test_datasets.py |
"""
This file causes the doctests to be included as part of unit tests.
To make sure the doctests of a specific module are included,
please replicate the `addTests` call for the iterators module below.
"""
import doctest
import infinibatch.iterators
def load_tests(loader, tests, ignore):
tests.addTests(doctest.D... | KosmosX-API-main | kosmosX/infinibatch/test/test_doctests.py |
from .iterators import create_source_iterator, CheckpointableIterator, SelectManyIterator, PrefetchIterator, BufferedShuffleIterator, BlockwiseShuffleIterator, MapIterator
from typing import List, Iterator, Callable, Any, Optional
"""
This module contains common datasets, which are implemented as convenience functions... | KosmosX-API-main | kosmosX/infinibatch/infinibatch/datasets.py |
"""
Infinibatch is a library of checkpointable iterators for randomized data loading of massive data sets in deep neural network training.
## Features
* support for corpora much larger than fit into RAM
* hierarchical block+sentence-level randomization over the whole corpus, different randomization in each epoch... | KosmosX-API-main | kosmosX/infinibatch/infinibatch/__init__.py |
"""
## Overview
This part of the documentation covers the __advanced usage__ of Infinibatch by assembling __custom data loading pipelines__.
Before you continue, please go through the tutorial on the top-level of the documentation of the `infinibatch` module.
Two of the main features of Infinibatch are __lazy evaluat... | KosmosX-API-main | kosmosX/infinibatch/infinibatch/iterators.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import subprocess
import sys
from setuptools import Extension, find_packages, setup
if sys.version_info < (... | KosmosX-API-main | kosmosX/fairseq/setup.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Legacy entry point. Use fairseq_cli/train.py or fairseq-train instead.
"""
from fairseq_cli.train import cli_mai... | KosmosX-API-main | kosmosX/fairseq/train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""isort:skip_file"""
import functools
import importlib
dependencies = [
"dataclasses",
"hydra",
"numpy",
"omegaconf",
"... | KosmosX-API-main | kosmosX/fairseq/hubconf.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
from pathlib import Path
from typing import Callable, List, Optional, Union
import torch
from fairseq import utils
from fairs... | KosmosX-API-main | kosmosX/fairseq/fairseq/options.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import namedtuple
import numpy as np
import torch
from fairseq import utils
DecoderOut = namedtuple(
"IterativeRefinem... | KosmosX-API-main | kosmosX/fairseq/fairseq/iterative_refinement_generator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import torch
logger = logging.getLogger(__name__)
class NanDetector:
"""
Detects the first NaN or Inf in forward a... | KosmosX-API-main | kosmosX/fairseq/fairseq/nan_detector.py |
# Originally from Microsoft Corporation.
# Licensed under the MIT License.
""" Wrapper for ngram_repeat_block cuda extension """
import math
import warnings
from typing import Dict, List
import torch
from torch import nn
try:
from fairseq import ngram_repeat_block_cuda
EXTENSION_BUILT = True
except ImportEr... | KosmosX-API-main | kosmosX/fairseq/fairseq/ngram_repeat_block.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from argparse import Namespace
from typing import Union
from fairseq.dataclass import FairseqDataclass
from fairseq.dataclass.utils import me... | KosmosX-API-main | kosmosX/fairseq/fairseq/registry.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import numpy as np
from fairseq.data.audio.speech_to_text_dataset import S2TDataConfig
class SpeechGenerator(object):
def ... | KosmosX-API-main | kosmosX/fairseq/fairseq/speech_generator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import typing as tp
def _safe_readline(fd) -> str:
pos = fd.tell()
while True:
try:
return fd.readline... | KosmosX-API-main | kosmosX/fairseq/fairseq/file_chunker_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""isort:skip_file"""
import os
import sys
try:
from .version import __version__ # noqa
except ImportError:
version_txt = os.path.jo... | KosmosX-API-main | kosmosX/fairseq/fairseq/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import Dict, List, Optional
import sys
import torch
import torch.nn as nn
from fairseq import search, utils
from fair... | KosmosX-API-main | kosmosX/fairseq/fairseq/sequence_generator.py |
"""
DeepSpeed trainer
"""
import os
import sys
import torch
import time
import logging
import deepspeed
import json
from typing import Any, Dict, List
from itertools import chain
from argparse import Namespace
import torch.distributed as dist
from fairseq import optim, utils
from fairseq.distributed import utils as ... | KosmosX-API-main | kosmosX/fairseq/fairseq/ds_trainer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import multiprocessing
import os
import pdb
import sys
__all__ = ["set_trace"]
_stdin = [None]
_stdin_lock = multiprocessing.Lock()
try:
... | KosmosX-API-main | kosmosX/fairseq/fairseq/pdb.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import re
SPACE_NORMALIZER = re.compile(r"\s+")
def tokenize_line(line):
line = SPACE_NORMALIZER.sub(" ", line)
line = line.strip(... | KosmosX-API-main | kosmosX/fairseq/fairseq/tokenizer.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import copy
import logging
import os
from typing import Any, Dict, Iterator, List
import torch
from... | KosmosX-API-main | kosmosX/fairseq/fairseq/hub_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
import torch
from fairseq import utils
class SequenceScorer(object):
"""Scores the target for a given source sentence."""
... | KosmosX-API-main | kosmosX/fairseq/fairseq/sequence_scorer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import uuid
from typing import Dict, Optional
from torch import Tensor
class FairseqIncrementalState(object):
def __init__(self, *args,... | KosmosX-API-main | kosmosX/fairseq/fairseq/incremental_decoding_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import contextlib
import copy
import importlib
import logging
import os
import sys
import warnings
from itertools import accum... | KosmosX-API-main | kosmosX/fairseq/fairseq/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import ast
import collections
import contextlib
import logging
import numpy as np
import os
import re
import time
import traceback
from collec... | KosmosX-API-main | kosmosX/fairseq/fairseq/checkpoint_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from fairseq.modules.quantization import pq, quantization_options, scalar
from omegaconf import DictConfig
logger = logging.... | KosmosX-API-main | kosmosX/fairseq/fairseq/quantization_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Utilities for working with the local dataset cache.
This file is adapted from `AllenNLP <https://github.com/allenai/allennlp>`_.
and `hugg... | KosmosX-API-main | kosmosX/fairseq/fairseq/file_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from typing import List, Optional
import torch
import torch.nn as nn
from fairseq.token_generation_constraints import (
Const... | KosmosX-API-main | kosmosX/fairseq/fairseq/search.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import shutil
from typing import List, Optional
logger = logging.getLogger(__file__)
try:... | KosmosX-API-main | kosmosX/fairseq/fairseq/file_io.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Train a network across multiple GPUs.
"""
import contextlib
import logging
import os
import sys
import time
from argparse import Namespac... | KosmosX-API-main | kosmosX/fairseq/fairseq/trainer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import typing as tp
from abc import ABC, abstractmethod
from collections import Counter
from dataclasses import datac... | KosmosX-API-main | kosmosX/fairseq/fairseq/binarizer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""Implements tracking of constraints for a beam item.
A list of constraints is given as a list of one or more token
sequences, each of lengt... | KosmosX-API-main | kosmosX/fairseq/fairseq/token_generation_constraints.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from dataclasses import dataclass, field
from typing import Optional
import torch
from omegaconf import II
from .dummy_datase... | KosmosX-API-main | kosmosX/fairseq/fairseq/benchmark/dummy_masked_lm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from dataclasses import dataclass, field
from typing import Optional
import torch
from .dummy_dataset import DummyDataset
from... | KosmosX-API-main | kosmosX/fairseq/fairseq/benchmark/dummy_lm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import numpy as np
import torch
from fairseq.data import Dictionary, FairseqDataset
from fairseq.tasks import LegacyFairseqTa... | KosmosX-API-main | kosmosX/fairseq/fairseq/benchmark/dummy_mt.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# import models/tasks to register them
from . import dummy_dataset, dummy_lm, dummy_masked_lm, dummy_model, dummy_mt # noqa
| KosmosX-API-main | kosmosX/fairseq/fairseq/benchmark/__init__.py |
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