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from .components import LinearActivation, Activation, Normalization, DropoutNd
hyena-dna-main
src/models/nn/__init__.py
""" Utility wrappers around modules to let them handle Args and extra arguments """ import inspect from functools import wraps import torch from torch import nn def wrap_kwargs(f): """ Given a callable f that can consume some named arguments, wrap it with a kwargs that passes back any unused args EXA...
hyena-dna-main
src/models/nn/utils.py
""" Defines flexible gating mechanisms based on ideas from LSSL paper and UR-LSTM paper https://arxiv.org/abs/1910.09890 """ import torch import torch.nn as nn class Gate(nn.Module): """ Implements gating mechanisms. TODO update this with more detailed description with reference to LSSL paper when it's on arxiv ...
hyena-dna-main
src/models/nn/gate.py
"""Implementations of several types of Discrete Sin/Cosine Transforms with various reductions to FFT. Currently not used by S4 """ import torch import torch.nn as nn import numpy as np import scipy.fft from einops import rearrange, repeat class DCT(nn.Module): """ Reductions adapted from https://dsp.stackexchang...
hyena-dna-main
src/models/nn/dxt.py
""" Utility nn components, in particular handling activations, initializations, and normalization layers """ from functools import partial import math from typing import ForwardRef import torch import torch.nn as nn import torch.nn.functional as F from einops import rearrange from opt_einsum import contract def stoc...
hyena-dna-main
src/models/nn/components.py
# Copyright (c) 2023, Tri Dao, Dan Fu. # Simplified, mostly standalone version of LongConvLM for synthetics. import math from functools import partial from collections import namedtuple import torch import torch.nn as nn import torch.nn.functional as F from torchvision.ops import StochasticDepth from einops import ...
hyena-dna-main
src/models/sequence/simple_lm.py
""" Implementation of FFN block in the style of Transformers """ from functools import partial from torch import nn from src.models.sequence.base import SequenceModule from src.models.nn import LinearActivation, DropoutNd class FF(SequenceModule): def __init__(self, d_input, expand=2, d_output=None, transposed=Fa...
hyena-dna-main
src/models/sequence/ff.py
'''PyTorch version of the block FFT convolution as described in the H3 paper.''' import torch from einops import rearrange import math from torch import nn from src.models.nn import Activation from src.utils.train import OptimModule def ref_dft_matrix(N, H=1): """Compute the DFT matrix of size N x N. Thi...
hyena-dna-main
src/models/sequence/block_fft.py
from .base import SequenceModule, TransposedModule from .model import SequenceModel from .ff import FF
hyena-dna-main
src/models/sequence/__init__.py
from functools import partial import torch import torch.nn as nn from flash_attn.utils.generation import GenerationMixin from flash_attn.utils.distributed import sync_shared_params try: from flash_attn.ops.fused_dense import ColumnParallelLinear except ImportError: ColumnParallelLinear = None # grab all func...
hyena-dna-main
src/models/sequence/dna_embedding.py
import torch import torch.nn as nn import torch.nn.functional as F from einops import rearrange import opt_einsum as oe optimized = True if optimized: contract = oe.contract else: contract = torch.einsum from src.models.nn import LinearActivation, Activation, DropoutNd from src.models.sequence.block_fft impo...
hyena-dna-main
src/models/sequence/long_conv.py
import copy import math import re from functools import partial from collections import namedtuple, OrderedDict from collections.abc import Sequence import torch import torch.nn as nn import torch.nn.functional as F from torch.utils.checkpoint import checkpoint from transformers.models.gpt2.configuration_gpt2 import...
hyena-dna-main
src/models/sequence/long_conv_lm.py
""" Isotropic deep sequence model backbone, in the style of ResNets / Transformers. The SequenceModel class implements a generic (batch, length, d_input) -> (batch, length, d_output) transformation """ from functools import partial import torch import torch.nn as nn from einops import rearrange from src.utils.confi...
hyena-dna-main
src/models/sequence/model.py
import torch import torch.nn as nn import torch.nn.functional as F from einops import repeat from src.utils.train import OptimModule class LongConvKernel(OptimModule): def __init__( self, H, L, channels=1, learning_rate=None, lam=0.1, causal=True, ...
hyena-dna-main
src/models/sequence/long_conv_kernel.py
import math import sys from re import U import torch import torch.nn as nn import torch.nn.functional as F from functools import partial from einops import rearrange, repeat try: from src.ops.fftconv import fftconv_ref, fftconv_func, fftconv_heads_ref except ImportError: fftconv_func = None try: from f...
hyena-dna-main
src/models/sequence/hyena.py
""" Implements a full residual block around a black box layer Configurable options include: normalization position: prenorm or postnorm normalization type: batchnorm, layernorm etc. subsampling/pooling residual options: feedforward, residual, affine scalars, depth-dependent scaling, etc. """ from torch import nn fro...
hyena-dna-main
src/models/sequence/block.py
"""Implements downsampling and upsampling on sequences.""" import torch from torch import nn import torch.nn.functional as F from einops import rearrange, repeat, reduce from src.models.sequence import SequenceModule from src.models.nn import LinearActivation """ Simple pooling functions that just downsample or repe...
hyena-dna-main
src/models/sequence/pool.py
from torch import nn import functools class SequenceModule(nn.Module): """Abstract sequence model class. All models must adhere to this interface A SequenceModule is generally a model that transforms an input of shape (n_batch, l_sequence, d_model) to (n_batch, l_sequence, d_output) REQUIRED methods ...
hyena-dna-main
src/models/sequence/base.py
""" Wrapper around nn.MultiheadAttention to adhere to SequenceModule interface. """ import torch import torch.nn.functional as F from torch import nn import hydra from src.models.sequence.base import SequenceModule, TransposedModule import src.models.nn.utils as U from einops import rearrange @TransposedModule class ...
hyena-dna-main
src/models/sequence/mha.py
import math import torch import torch.nn.functional as F from einops import rearrange from fftconv import fftconv_fwd, fftconv_bwd @torch.jit.script def _mul_sum(y, q): return (y * q).sum(dim=1) # reference convolution with residual connection def fftconv_ref(u, k, D, dropout_mask, gelu=True, k_rev=None): ...
hyena-dna-main
src/ops/fftconv.py
"""pykeops implementations of the Vandermonde matrix multiplication kernel used in the S4D kernel.""" import math import torch from einops import rearrange, repeat from opt_einsum import contract import os try: import pykeops from pykeops.torch import LazyTensor, Genred except: pass try: from cauchy...
hyena-dna-main
src/ops/vandermonde.py
""" Old utilities for parallel scan implementation of Linear RNNs. """ # TODO this file could use much cleanup import torch import torch.nn as nn import torch.nn.functional as F import numpy as np import math from src.models.functional.toeplitz import triangular_toeplitz_multiply, triangular_toeplitz_multiply_padded ...
hyena-dna-main
src/ops/unroll.py
""" Compute a Krylov function efficiently. (S4 renames the Krylov function to a "state space kernel") A : (N, N) b : (N,) c : (N,) Return: [c^T A^i b for i in [L]] """ import torch import torch.nn.functional as F from einops import rearrange, repeat from src.ops.toeplitz import causal_convolution def krylov_sequent...
hyena-dna-main
src/ops/krylov.py
""" Utilities for computing convolutions. There are 3 equivalent views: 1. causal convolution 2. multiplication of (lower) triangular Toeplitz matrices 3. polynomial multiplication (mod x^N) """ import torch import torch.nn as nn import torch.nn.functional as F def construct_toeplitz(v, f=0.0): """E...
hyena-dna-main
src/ops/toeplitz.py
#!/usr/bin/env python3 # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 sys from setuptools import Extension, find_packages, setup if sys.version_inf...
flash_metaseq-main
setup.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Utils for gpu_tests. """ import os import unittest def is_this_circleci(): """ Return if we are currently ...
flash_metaseq-main
gpu_tests/utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import copy import logging import unittest import torch from omegaconf import OmegaConf from metaseq.optim.fp16_optim...
flash_metaseq-main
gpu_tests/test_fp16_optimizer.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch import torch.nn as nn from torch.utils.checkpoint import checkpoint from metaseq.modules...
flash_metaseq-main
gpu_tests/test_activation_checkpointing.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 logging import unittest import torch from omegaconf import OmegaConf from metaseq.optim.adam im...
flash_metaseq-main
tests/test_polynomial_lr.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import collections import unittest import numpy as np from metaseq.data import ListDataset, ResamplingDataset class...
flash_metaseq-main
tests/test_resampling_dataset.py
flash_metaseq-main
tests/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import json import os import random import string import tempfile import unittest import torch from tests.utils impor...
flash_metaseq-main
tests/test_streaming_language_modeling_task.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 os import random from typing import Optional import numpy as np import torch import torch.nn.fu...
flash_metaseq-main
tests/utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 logging import unittest import torch from omegaconf import OmegaConf from metaseq.optim.adam i...
flash_metaseq-main
tests/test_memory_efficient_fp16.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 tempfile import unittest import torch import tests.utils as test_utils from metaseq import sea...
flash_metaseq-main
tests/test_sequence_generator.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 unittest try: import boto3 from metaseq.s3_utils import S3PathHandler except ImportError: ...
flash_metaseq-main
tests/test_s3_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from metaseq.data import MonolingualDataset from metaseq.tasks.language_modeling import ...
flash_metaseq-main
tests/test_lm_context_window.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 shutil import sys import tempfile import unittest from typing import Optional from unittest.mock impor...
flash_metaseq-main
tests/test_file_io.py
#!/usr/bin/env python3 # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 tempfile import unittest import torch from metaseq.data.dictionary impo...
flash_metaseq-main
tests/test_export.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import functools import sys import unittest import torch from metaseq.distributed import utils as dist_utils from .ut...
flash_metaseq-main
tests/distributed/test_utils.py
flash_metaseq-main
tests/distributed/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import functools import tempfile import torch def spawn_and_init(fn, world_size, args=None): if args is None: ...
flash_metaseq-main
tests/distributed/utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import io import os import string import tempfile import unittest import torch from metaseq import tokenizer from meta...
flash_metaseq-main
cpu_tests/test_dictionary.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from metaseq import utils class TestUtils(unittest.TestCase): def test_make_positio...
flash_metaseq-main
cpu_tests/test_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import uuid from metaseq import metrics class TestMetrics(unittest.TestCase): def test_nesting(s...
flash_metaseq-main
cpu_tests/test_metrics.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 unittest import tests.utils as test_utils import torch from metaseq.sequence_scorer import Sequ...
flash_metaseq-main
cpu_tests/test_sequence_scorer.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from metaseq.modules.multihead_attention import MultiheadAttention class TestMultiheadA...
flash_metaseq-main
cpu_tests/test_multihead_attention.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import numpy as np from metaseq.data.data_utils_fast import batch_by_size_fn from metaseq.data.data_ut...
flash_metaseq-main
cpu_tests/test_data_utils.py
flash_metaseq-main
cpu_tests/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import numpy as np import torch from metaseq.data import StreamingTokenBlockDataset class TensorLis...
flash_metaseq-main
cpu_tests/test_streaming_token_block_dataset.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from metaseq.data import PartitionedStreamingDataset class TensorListIterableDataset(t...
flash_metaseq-main
cpu_tests/test_partitioned_streaming_dataset.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import tests.utils as test_utils import torch from metaseq.data import TokenBlockDataset class TestT...
flash_metaseq-main
cpu_tests/test_token_block_dataset.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 shutil import tempfile import unittest from typing import Optional class TestFileChunker(unittest.Te...
flash_metaseq-main
cpu_tests/test_file_chunker_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from metaseq.data import StreamingShuffleDataset class TensorListDataset(torch.utils.d...
flash_metaseq-main
cpu_tests/test_streaming_shuffle_dataset.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from metaseq.data import iterators class TensorListIterableDataset(torch.utils.data.It...
flash_metaseq-main
cpu_tests/test_streaming_iterators.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import json import os import random import string import tempfile import unittest from unittest.mock import MagicMock ...
flash_metaseq-main
cpu_tests/test_jsonl_dataset.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest import torch from torch import nn from metaseq.distributed import ModuleProxyWrapper from tests.dist...
flash_metaseq-main
cpu_tests/distributed/test_module_proxy_wrapper.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 signal import time import unittest import torch from torch import nn from metaseq.distributed i...
flash_metaseq-main
cpu_tests/distributed/test_distributed_timeout_wrapper.py
flash_metaseq-main
cpu_tests/distributed/__init__.py
#!/usr/bin/env python3 -u # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Host the demo. Launch with `python -m metaseq_cli.interactive_hosted` to run locally. Se...
flash_metaseq-main
metaseq_cli/interactive_hosted.py
flash_metaseq-main
metaseq_cli/__init__.py
#!/usr/bin/env python3 -u # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 sys from argparse import Namespace from itertools import chai...
flash_metaseq-main
metaseq_cli/validate.py
#!/usr/bin/env python3 -u # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Train a new model on one or across multiple GPUs. """ import argparse import functools im...
flash_metaseq-main
metaseq_cli/train.py
#!/usr/bin/env python3 -u # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Host the demo. Launch with `python -m metaseq_cli.interactive_hosted` to run locally. Se...
flash_metaseq-main
metaseq_cli/interactive_cli.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 typing import Callable, List, Optional import torch from metaseq import utils from metaseq.datac...
flash_metaseq-main
metaseq/options.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 N...
flash_metaseq-main
metaseq/nan_detector.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 hydra.core.config_store import ConfigStore from omegaconf...
flash_metaseq-main
metaseq/registry.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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: ...
flash_metaseq-main
metaseq/file_chunker_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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: v...
flash_metaseq-main
metaseq/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 math from typing import Dict, List, Optional import torch import torch.nn as nn from torch impor...
flash_metaseq-main
metaseq/sequence_generator.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 = multip...
flash_metaseq-main
metaseq/pdb.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import datetime as dt import io import logging import os import shutil import types from functools import partial from ...
flash_metaseq-main
metaseq/s3_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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)...
flash_metaseq-main
metaseq/tokenizer.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 ast import copy import logging import os import time from argparse import Namespace from typing ...
flash_metaseq-main
metaseq/hub_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 metaseq import utils class SequenceScorer(object): """Scores the target for a give...
flash_metaseq-main
metaseq/sequence_scorer.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 from typing_extensions import Protocol class ...
flash_metaseq-main
metaseq/incremental_decoding_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 importlib import logging import os import random import sys import warnings from typ...
flash_metaseq-main
metaseq/utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 functools import logging import os import re import traceback from glob import glo...
flash_metaseq-main
metaseq/checkpoint_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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...
flash_metaseq-main
metaseq/file_utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from typing import Optional import torch import torch.nn as nn from torch import Tensor class Search(nn.Module): ...
flash_metaseq-main
metaseq/search.py
#!/usr/bin/env python3 # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import json import logging import os import shutil from typing import List, Optional import to...
flash_metaseq-main
metaseq/file_io.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 re import sys import time from i...
flash_metaseq-main
metaseq/trainer.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 numpy as np import torch fr...
flash_metaseq-main
metaseq/benchmark/dummy_lm.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from . import dummy_lm # noqa
flash_metaseq-main
metaseq/benchmark/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from dataclasses import dataclass from enum import Enum @dataclass class Size: n_layers: int emb_size: int ...
flash_metaseq-main
metaseq/launcher/opt_job_constants.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import datetime import fnmatch import hashlib import itertools import os import random import shlex import shutil impor...
flash_metaseq-main
metaseq/launcher/slurm.py
flash_metaseq-main
metaseq/launcher/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 datetime import os import subprocess from typing import Optional, List, Callable, MutableMapping...
flash_metaseq-main
metaseq/launcher/sweep.py
#!/usr/bin/env python3 -u # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ This sweep script takes some additional optional arguments. See add_extra_options_func fo...
flash_metaseq-main
metaseq/launcher/opt_baselines.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Streaming Language Modeling task that loads corpora in src-tgt format and performs on-the-fly tokenization. """ imp...
flash_metaseq-main
metaseq/tasks/streaming_finetune_language_modeling.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 from dataclasses import dataclass, field from typing import Optional, List import numpy as np...
flash_metaseq-main
metaseq/tasks/language_modeling_inference_for_models_trained_with_streaming.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 from dataclasses import dataclass, field from typing import Optional import numpy as np impor...
flash_metaseq-main
metaseq/tasks/language_modeling.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 warnings from argparse import Namespace from typing import Any, Callable, Dict, List import torc...
flash_metaseq-main
metaseq/tasks/base_task.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Streaming Language Modeling task that loads corpora in plaintext and performs on-the-fly tokenization. """ import l...
flash_metaseq-main
metaseq/tasks/streaming_language_modeling.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 argparse import importlib import os from metaseq.dataclass import MetaseqDataclass from m...
flash_metaseq-main
metaseq/tasks/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # 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 signal import threading from torch import nn logger = logging.getLogger(__name__) c...
flash_metaseq-main
metaseq/distributed/distributed_timeout_wrapper.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import contextlib import logging import os from typing import Optional import torch from metaseq.dataclass.configs im...
flash_metaseq-main
metaseq/distributed/fully_sharded_data_parallel.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from .distributed_timeout_wrapper import DistributedTimeoutWrapper from .fully_sharded_data_parallel import ( fsdp_...
flash_metaseq-main
metaseq/distributed/__init__.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import io import logging import os import pickle import random import signal import socket import struct import subproc...
flash_metaseq-main
metaseq/distributed/utils.py
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import gc import logging import os import re import time from collections import defaultdict, OrderedDict from glob imp...
flash_metaseq-main
metaseq/distributed/stitch_fsdp_ckpt.py