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triton
triton-main/python/triton/compiler/compiler.py
from __future__ import annotations import functools import hashlib import json import os import re import subprocess import tempfile from collections import namedtuple from pathlib import Path from typing import Any, Tuple from .._C.libtriton.triton import (add_external_libs, compile_ptx_to_cubin, ...
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triton
triton-main/python/triton/compiler/code_generator.py
import ast import inspect import re import sys import warnings from typing import Any, Callable, Dict, Optional, Tuple, Type, Union from .. import language from .._C.libtriton.triton import ir from ..language import constexpr, tensor # ideally we wouldn't need any runtime component from ..runtime import JITFunction fr...
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triton
triton-main/python/triton/compiler/__init__.py
from .compiler import CompiledKernel, compile, instance_descriptor from .errors import CompilationError __all__ = ["compile", "instance_descriptor", "CompiledKernel", "CompilationError"]
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triton
triton-main/python/triton/language/semantic.py
from __future__ import annotations # remove after python 3.11 import warnings from functools import wraps from typing import List, Optional, Sequence, Tuple, TypeVar from .._C.libtriton.triton import ir from . import core as tl T = TypeVar('T') # Create custom exception that prints message "hello" class Incompat...
65,322
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triton
triton-main/python/triton/language/core.py
from __future__ import annotations from contextlib import contextmanager from enum import Enum from functools import wraps from typing import Callable, List, Sequence, TypeVar from .._C.libtriton.triton import ir from ..runtime.jit import jit from . import math, semantic T = TypeVar('T') TRITON_MAX_TENSOR_NUMEL = 1...
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triton
triton-main/python/triton/language/math.py
import functools import os from . import core @functools.lru_cache() def libdevice_path(): import torch third_party_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "third_party") if torch.version.hip is None: default = os.path.join(third_party_dir, "cuda", "lib", "libdevice.1...
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triton
triton-main/python/triton/language/standard.py
from __future__ import annotations from ..runtime.jit import jit from . import core # ----------------------- # Standard library # ----------------------- @jit def cdiv(x, div): """ Computes the ceiling division of :code:`x` by :code:`div` :param x: the input number :type input: Block :param di...
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triton
triton-main/python/triton/language/random.py
from ..runtime.jit import jit from . import core as tl PHILOX_KEY_A: tl.constexpr = 0x9E3779B9 PHILOX_KEY_B: tl.constexpr = 0xBB67AE85 PHILOX_ROUND_A: tl.constexpr = 0xD2511F53 PHILOX_ROUND_B: tl.constexpr = 0xCD9E8D57 N_ROUNDS_DEFAULT = 10 # Default number of rounds for philox # ------------------- # randint # ----...
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triton
triton-main/python/triton/language/__init__.py
"""isort:skip_file""" # Import order is significant here. from . import math from . import extra from .standard import ( cdiv, sigmoid, softmax, ravel, swizzle2d, zeros, zeros_like, ) from .core import ( TRITON_MAX_TENSOR_NUMEL, abs, advance, arange, argmin, argmax, ...
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triton
triton-main/python/triton/language/extra/cuda.py
import os from .. import core __path__ = os.path.dirname(os.path.abspath(__file__)) @core.extern def globaltimer(_builder=None): return core.extern_elementwise("cuda", os.path.join(__path__, "cuda.bc"), [], {tuple(): ("globaltimer", core.dtype("int64")), ...
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triton
triton-main/python/triton/language/extra/__init__.py
from . import cuda __all__ = ['cuda']
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triton
triton-main/python/triton/ops/flash_attention.py
""" Fused Attention =============== This is a Triton implementation of the Flash Attention algorithm (see: Dao et al., https://arxiv.org/pdf/2205.14135v2.pdf; Rabe and Staats https://arxiv.org/pdf/2112.05682v2.pdf) Sequence Parallel implementation inspired by HazyResearch (see https://github.com/HazyResearch/flash-att...
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triton
triton-main/python/triton/ops/cross_entropy.py
import torch from .. import heuristics, jit from .. import language as tl from .. import next_power_of_2 def num_warps(N): if N < 2048: return 4 elif N < 8192: return 8 return 16 @heuristics({'num_warps': lambda nargs: num_warps(nargs['N'])}) @heuristics({'BLOCK': lambda nargs: next_pow...
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triton
triton-main/python/triton/ops/matmul.py
import torch from .. import Config, autotune, cdiv, heuristics, jit from .. import language as tl from .matmul_perf_model import early_config_prune, estimate_matmul_time _ordered_datatypes = [torch.float16, torch.bfloat16, torch.float32] def get_higher_dtype(a, b): if a is b: return a assert a in _...
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triton
triton-main/python/triton/ops/__init__.py
# from .conv import _conv, conv from . import blocksparse from .cross_entropy import _cross_entropy, cross_entropy from .flash_attention import attention from .matmul import _matmul, matmul __all__ = [ "blocksparse", "_cross_entropy", "cross_entropy", "_matmul", "matmul", "attention", ]
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triton
triton-main/python/triton/ops/matmul_perf_model.py
import heapq import torch from .. import cdiv from .._C.libtriton.triton import runtime from ..runtime import driver from ..testing import get_dram_gbps, get_max_simd_tflops, get_max_tensorcore_tflops def get_tensorcore_tflops(backend, device, num_ctas, num_warps, dtype): ''' return compute throughput in TOPS '...
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triton
triton-main/python/triton/ops/blocksparse/softmax.py
import torch from ... import jit from ... import language as tl from ... import next_power_of_2 def num_warps(n): if n <= 128: return 1 if n <= 256: return 2 if n <= 512: return 4 if n <= 4096: return 8 return 16 @jit def _blocksparse_softmax_fwd( Out, A, str...
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triton
triton-main/python/triton/ops/blocksparse/matmul.py
import torch from ... import cdiv, heuristics, jit from ... import language as tl # ******************************************************** # -------------------------------------------------------- # Sparse = Dense x Dense (SDD) # This operation uses super-blocking to make sure that # it's done efficiently when sma...
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triton
triton-main/python/triton/ops/blocksparse/__init__.py
from .matmul import matmul from .softmax import softmax __all__ = [ "matmul", "softmax", ]
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triton
triton-main/test/lit.cfg.py
# -*- Python -*- import os import platform import re import subprocess import tempfile import lit.formats import lit.util from lit.llvm import llvm_config from lit.llvm.subst import FindTool, ToolSubst # Configuration file for the 'lit' test runner # name: The name of this test suite config.name = 'TRITON' config....
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triton
triton-main/docs/conf.py
# -*- coding: utf-8 -*- # # Triton documentation build configuration file, created by # sphinx-quickstart on Mon Feb 10 01:19:09 2020. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # Al...
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G-PATE
G-PATE-master/main.py
import os import scipy.misc import numpy as np from model import DCGAN from utils import pp, visualize, to_json, show_all_variables, mkdir import tensorflow as tf import argparse from gen_data import batch2str import sys import pickle # os.environ["CUDA_VISIBLE_DEVICES"] = "1" flags = tf.app.flags flags.DEFINE_inte...
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G-PATE
G-PATE-master/pate_core.py
# core method from 'Scalable Private Learning with PATE' # Copyright 2017 The 'Scalable Private Learning with PATE' Authors All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the Licens...
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G-PATE
G-PATE-master/download.py
""" Modification of https://github.com/stanfordnlp/treelstm/blob/master/scripts/download.py Downloads the following: - Celeb-A dataset - LSUN dataset - MNIST dataset """ from __future__ import print_function import os import sys import gzip import json import shutil import zipfile import argparse import requests impo...
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G-PATE
G-PATE-master/rdp_utils.py
import numpy as np import math import sys from sklearn.preprocessing import normalize from pate_core import * from numpy import linalg as LA EPS = sys.float_info.epsilon # Algorithm 1 in 'Scalable Private Learning with PATE' def gnmax_thresh_aggregator(counts, thresh_cnt, sigma_thresh, sigma, orders): log_pr_an...
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G-PATE
G-PATE-master/dp_pca.py
# Copyright 2016 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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G-PATE
G-PATE-master/utils.py
""" Some codes from https://github.com/Newmu/dcgan_code """ from __future__ import division import math import json import random import pprint import scipy.misc import numpy as np from time import gmtime, strftime from six.moves import xrange import os import tensorflow as tf import tensorflow.contrib.slim as slim p...
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G-PATE
G-PATE-master/model.py
from __future__ import division import os import time import math from glob import glob import tensorflow as tf import numpy as np from six.moves import xrange import json import sys from keras.datasets import cifar10 from ops import * from utils import * from rdp_utils import * from pate_core import * import pickle fr...
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G-PATE
G-PATE-master/gen_data.py
import numpy as np import argparse x = [2, 2, 5, 8, 8, 9, 10, 11, 11, 12, 15, 28, 32, 42, 46, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101] y = [[-1, 2], [-1, 2], [-1, 5], [-1, 8], [-1, 8], [-1, 9], [-1, 10], [-1, 11], [-1, 11], [-1, 12], [-1, 15], [-1, 28], [-1, 32], [-1, 42], [-1, 46], [14515...
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G-PATE
G-PATE-master/ops.py
import math import numpy as np import tensorflow as tf from tensorflow.python.framework import ops from utils import * try: image_summary = tf.image_summary scalar_summary = tf.scalar_summary histogram_summary = tf.histogram_summary merge_summary = tf.merge_summary SummaryWriter = tf.train.SummaryWriter e...
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G-PATE
G-PATE-master/dp_utils.py
# Copyright 2016 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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G-PATE
G-PATE-master/input.py
# Copyright 2016 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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G-PATE
G-PATE-master/evaluation/train-classifier-celebA.py
#!/usr/bin/env python # coding: utf-8 import numpy as np import argparse import joblib import tensorflow as tf config = tf.ConfigProto() config.gpu_options.allow_growth = True # config.gpu_options.per_process_gpu_memory_fraction = 0.3 tf.keras.backend.set_session(tf.Session(config=config)); def load_celeb(): ...
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G-PATE
G-PATE-master/evaluation/train-classifier-fmnist.py
#!/usr/bin/env python # coding: utf-8 import numpy as np import argparse import tensorflow as tf config = tf.ConfigProto() config.gpu_options.allow_growth = True # config.gpu_options.per_process_gpu_memory_fraction = 0.3 tf.keras.backend.set_session(tf.Session(config=config)); def pipeline(): parser = argpars...
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G-PATE
G-PATE-master/evaluation/train-classifier-mnist.py
#!/usr/bin/env python # coding: utf-8 import numpy as np import argparse import tensorflow as tf config = tf.ConfigProto() config.gpu_options.allow_growth = True # config.gpu_options.per_process_gpu_memory_fraction = 0.3 tf.keras.backend.set_session(tf.Session(config=config)); def pipeline(): parser = argpa...
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G-PATE
G-PATE-master/evaluation/train-classifier-hair.py
#!/usr/bin/env python # coding: utf-8 # In[13]: import numpy as np import argparse import joblib import tensorflow as tf config = tf.ConfigProto() config.gpu_options.allow_growth = True # config.gpu_options.per_process_gpu_memory_fraction = 0.3 tf.keras.backend.set_session(tf.Session(config=config)); def load_cel...
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G-PATE
G-PATE-master/evaluation/train-classifier-small-celebA.py
#!/usr/bin/env python # coding: utf-8 import numpy as np import argparse parser = argparse.ArgumentParser(description='Train classifier and evaluate their accuracy') parser.add_argument('--data', type=str, help='datafile name') args = parser.parse_args() import joblib data = joblib.load(args.data) print(args.data) ...
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kraken
kraken-main/setup.py
#!/usr/bin/env python from setuptools import setup setup( include_package_data=True, setup_requires=['pbr'], pbr=True, )
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kraken
kraken-main/kraken/rpred.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/linegen.py
# # Copyright 2014 Google Inc. All rights reserved. # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # ...
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kraken
kraken-main/kraken/align.py
# # Copyright 2021 Teklia # Copyright 2021 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applica...
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kraken
kraken-main/kraken/blla.py
# # Copyright 2019 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/pageseg.py
# # Copyright 2015 Benjamin Kiessling # 2014 Thomas M. Breuel # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by a...
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kraken
kraken-main/kraken/kraken.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/transcribe.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/__init__.py
""" entry point for kraken functionality """
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kraken
kraken-main/kraken/binarization.py
# # Copyright 2015 Benjamin Kiessling # 2014 Thomas M. Breuel # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by a...
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kraken
kraken-main/kraken/repo.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/serialization.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/pretrain.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/linegen.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/dataset.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/segmentation.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/util.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/__init__.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/transcription.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/ketos/repo.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
4,240
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kraken
kraken-main/kraken/ketos/recognition.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/contrib/heatmap_overlay.py
#! /usr/bin/env python """ Produces semi-transparent neural segmenter output overlays """ import click @click.command() @click.option('-i', '--model', default=None, show_default=True, type=click.Path(exists=True), help='Baseline detection model to use.') @click.argument('files', nargs=-1) def cli(model,...
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kraken
kraken-main/kraken/contrib/recognition_boxes.py
#!/usr/bin/env python """ Draws transparent character bounding boxes over images giving a legacy segmenter model. """ import os import sys from PIL import Image, ImageDraw from kraken.pageseg import segment from kraken.binarization import nlbin from kraken.rpred import rpred from itertools import cycle from kraken.l...
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kraken
kraken-main/kraken/contrib/print_word_spreader.py
#!/usr/bin/env python #2020, Bruce Robertson #Master file at https://github.com/brobertson/Lace2-tools/blob/master/normalize_hocr.py import html, os, sys, argparse from statistics import mean from lxml import etree from PIL import Image #a custom exception to indicate when a page or other element doesn't #have a bound...
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kraken
kraken-main/kraken/contrib/repolygonize.py
#!/usr/bin/env python """ Reads in a bunch of ALTO documents and repolygonizes the lines contained with the kraken polygonizer. """ import click @click.command() @click.option('-f', '--format-type', type=click.Choice(['alto', 'page']), default='alto', help='Sets the input document format. In ALTO and Pa...
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kraken
kraken-main/kraken/contrib/segmentation_overlay.py
#!/usr/bin/env python """ Draws a transparent overlay of baseline segmenter output over a list of image files. """ import re import os import click import unicodedata from itertools import cycle from collections import defaultdict cmap = cycle([(230, 25, 75, 127), (60, 180, 75, 127)]) bmap = (0, 130, 20...
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kraken
kraken-main/kraken/contrib/generate_scripts.py
#!/usr/bin/env python3 """ Script fetching the latest unicode Scripts.txt and dumping it as json. """ from urllib import request import json import regex uri = 'http://www.unicode.org/Public/UNIDATA/Scripts.txt' re = regex.compile(r'^(?P<start>[0-9A-F]{4,6})(..(?P<end>[0-9A-F]{4,6}))?\s+; (?P<name>[A-Za-z]+)') with ...
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kraken
kraken-main/kraken/contrib/forced_alignment_overlay.py
#!/usr/bin/env python """ Draws a transparent overlay of the forced alignment output over the input image. """ import re import os import click import unicodedata from lxml import etree from itertools import cycle from unicodedata import normalize cmap = cycle([(230, 25, 75, 127), (60, 180, 75, 127), ...
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kraken
kraken-main/kraken/contrib/set_seg_options.py
#!/usr/bin/env python """ A script setting the metadata of segmentation models. """ import click import shutil @click.command() @click.option('-b', '--bounding-region', multiple=True, help='Sets region identifiers which bound line bounding polygons') @click.option('--topline/--baseline', default=False, help='Sets mod...
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kraken
kraken-main/kraken/contrib/extract_lines.py
#! /usr/bin/env python import click @click.command() @click.option('-f', '--format-type', type=click.Choice(['xml', 'alto', 'page', 'binary']), default='xml', help='Sets the input document format. In ALTO and PageXML mode all ' 'data is extracted from xml files containing both baselines, ...
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kraken
kraken-main/kraken/contrib/baselineset_overlay.py
#! /usr/bin/env python """ Produces semi-transparent neural segmenter output overlays """ import click @click.command() @click.argument('files', nargs=-1) def cli(files): import torch from PIL import Image from os.path import splitext import torchvision.transforms as tf from kraken.lib import dat...
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kraken-main/kraken/contrib/hyperparameters/tune_pretraining.py
#!/usr/bin/env python """ A script for a grid search over pretraining hyperparameters. """ import click from functools import partial from ray import tune from ray.tune.integration.pytorch_lightning import TuneReportCallback from kraken.lib.default_specs import RECOGNITION_PRETRAIN_HYPER_PARAMS, RECOGNITION_SPEC fro...
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kraken
kraken-main/kraken/contrib/hyperparameters/tune_training.py
#!/usr/bin/env python """ A script for a grid search over pretraining hyperparameters. """ import sys from functools import partial from ray import tune from ray.tune.integration.pytorch_lightning import TuneReportCallback from kraken.lib.default_spec import RECOGNITION_PRETRAIN_HYPER_PARAMS, RECOGNITION_SPEC from k...
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kraken-main/kraken/lib/lstm.py
# flake8: noqa from typing import Dict from scipy.special import expit initial_range = 0.1 class Codec(object): """Translate between integer codes and characters.""" def init(self, charset): charset = sorted(list(set(charset))) self.code2char = {} # type: Dict[int, str] self.char2cod...
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kraken
kraken-main/kraken/lib/exceptions.py
""" kraken.lib.exceptions ~~~~~~~~~~~~~~~~~~~~~ All custom exceptions raised by kraken's modules and packages. Packages should always define their exceptions here. """ class KrakenCodecException(Exception): def __init__(self, message=None): Exception.__init__(self, message) class KrakenStopTrainingExc...
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kraken-main/kraken/lib/xml.py
# # Copyright 2019 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/codec.py
# # Copyright 2017 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/lib/progress.py
# Copyright Benjamin Kiessling # Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required b...
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kraken-main/kraken/lib/ctc_decoder.py
# # Copyright 2017 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/lib/vgsl.py
""" VGSL plumbing """ import re import json import torch import logging import warnings from torch import nn from os import PathLike from typing import Sequence, List, Tuple, Union, Optional, Iterable, Callable, Dict, Any from kraken.lib import layers from kraken.lib.codec import PytorchCodec from kraken.lib.exceptio...
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kraken
kraken-main/kraken/lib/morph.py
""" Various add-ons to the SciPy morphology package """ import numpy as np from scipy.ndimage import label as _label from scipy.ndimage import distance_transform_edt from scipy.ndimage import find_objects as _find_objects from scipy.ndimage import filters def label(image: np.ndarray, **kw) -> np.ndarray: """ ...
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kraken
kraken-main/kraken/lib/lineest.py
import warnings from PIL import Image import numpy as np from kraken.lib.util import pil2array, array2pil from scipy.ndimage import affine_transform, gaussian_filter, uniform_filter __all__ = ['CenterNormalizer', 'dewarp'] def scale_to_h(img, target_height, order=1, dtype=np.dtype('f'), cval=0): h, w = img.shap...
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kraken-main/kraken/lib/segmentation.py
# # Copyright 2019 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/log.py
# # Copyright 2018 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/arrow_dataset.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/kraken/lib/default_specs.py
# # Copyright 2020 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/layers.py
""" Layers for VGSL models """ import torch import numpy as np from typing import List, Tuple, Optional, Iterable from torch.nn import Module, Sequential from torch.nn import functional as F from torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence from coremltools.proto import NeuralNetwork_pb2 # all ...
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kraken
kraken-main/kraken/lib/util.py
""" Ocropus's magic PIL-numpy array conversion routines. They express slightly different behavior from PIL.Image.toarray(). """ import torch import unicodedata import numpy as np from PIL import Image from typing import Union __all__ = ['pil2array', 'array2pil', 'is_bitonal', 'make_printable', 'get_im_str'] def pi...
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kraken-main/kraken/lib/models.py
""" kraken.lib.models ~~~~~~~~~~~~~~~~~ Wrapper around TorchVGSLModel including a variety of forward pass helpers for sequence classification. """ from os import PathLike from os.path import expandvars, expanduser, abspath import torch import numpy as np import kraken.lib.lineest import kraken.lib.ctc_decoder from t...
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kraken-main/kraken/lib/functional_im_transforms.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/__init__.py
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kraken-main/kraken/lib/train.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/sl.py
import numpy as np def dim0(s): """Dimension of the slice list for dimension 0.""" return s[0].stop-s[0].start def dim1(s): """Dimension of the slice list for dimension 1.""" return s[1].stop-s[1].start def area(a): """Return the area of the slice list (ignores anything past a[:2].""" retu...
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kraken-main/kraken/lib/dataset/utils.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/dataset/segmentation.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/dataset/__init__.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/dataset/recognition.py
# # Copyright 2015 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/pretrain/model.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken-main/kraken/lib/pretrain/layers.py
""" Layers for VGSL models """ import torch from typing import Tuple, Optional from torch.nn import Module, Embedding, Linear from kraken.lib.vgsl import VGSLBlock from kraken.lib.pretrain.util import compute_mask_indices, sample_negatives # all tensors are ordered NCHW, the "feature" dimension is C, so the output o...
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kraken
kraken-main/kraken/lib/pretrain/util.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 typing import Sequence, Union, Tuple import torch import random import numpy as np def positive_integers_with_sum(n, total): ls = ...
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kraken
kraken-main/kraken/lib/pretrain/__init__.py
# # Copyright 2022 Benjamin Kiessling # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
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kraken
kraken-main/tests/test_layers.py
# -*- coding: utf-8 -*- import unittest import torch from kraken.lib import layers class TestLayers(unittest.TestCase): """ Testing custom layer implementations. """ def setUp(self): torch.set_grad_enabled(False) def test_maxpool(self): """ Test maximum pooling layer. ...
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kraken
kraken-main/tests/test_transcribe.py
# -*- coding: utf-8 -*- import os import json import unittest from PIL import Image from io import BytesIO from lxml import etree from pathlib import Path from kraken.transcribe import TranscriptionInterface thisfile = Path(__file__).resolve().parent resources = thisfile / 'resources' class TestTranscriptionInterfa...
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