repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/sync_batchnorm/batchnorm.py | sync_batchnorm/batchnorm.py | # -*- coding: utf-8 -*-
# File : batchnorm.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
import collections
import torch
import torc... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/TFHub/converter.py | TFHub/converter.py | """Utilities for converting TFHub BigGAN generator weights to PyTorch.
Recommended usage:
To convert all BigGAN variants and generate test samples, use:
```bash
CUDA_VISIBLE_DEVICES=0 python converter.py --generate_samples
```
See `parse_args` for additional options.
"""
import argparse
import os
import sys
impor... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/TFHub/biggan_v1.py | TFHub/biggan_v1.py | # BigGAN V1:
# This is now deprecated code used for porting the TFHub modules to pytorch,
# included here for reference only.
import numpy as np
import torch
from scipy.stats import truncnorm
from torch import nn
from torch.nn import Parameter
from torch.nn import functional as F
def l2normalize(v, eps=1e-4):
retur... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/setup.py | setup.py | from setuptools import setup
requirements = ["scikit-allel", "pandas", "numpy", "multiprocess", "scipy", "numcodecs", "typing-extensions"]
setup(
name="pixy",
version="2.0.0.beta14",
packages=["pixy"],
entry_points={"console_scripts": ["pixy=pixy.__main__:main"]},
url="https://github.com/ksamuk/pi... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/enums.py | pixy/enums.py | from enum import Enum
from enum import unique
@unique
class PixyStat(Enum):
"""
The genetic variance statistics that `pixy` can calculate.
Attributes:
PI: a measure of genetic diversity _within_ populations
DXY: a measure of genetic diversity _between_ populations
FST: the "fixati... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/models.py | pixy/models.py | from dataclasses import dataclass
from dataclasses import fields
from typing import Literal
from typing import Union
from typing_extensions import TypeAlias
from pixy.args_validation import PixyStat
NA: TypeAlias = Literal["NA"]
@dataclass(frozen=True)
class PixyTempResult:
"""
Stores temporary `pixy` resu... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/core.py | pixy/core.py | import argparse
import logging
import os
import shutil
import subprocess
import uuid
from pathlib import Path
from typing import Dict
from typing import List
from typing import Literal
from typing import Optional
from typing import Set
from typing import Tuple
from typing import Union
import allel
import multiprocess ... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | true |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/__main__.py | pixy/__main__.py | #!/usr/bin/env python
# coding: utf-8
import argparse
import logging
import os
import re
import subprocess
import sys
import time
from multiprocessing.context import BaseContext
from multiprocessing.managers import SyncManager
from multiprocessing.pool import ApplyResult
from typing import List
from typing import Optio... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | true |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/args_validation.py | pixy/args_validation.py | import argparse
import gzip
import logging
import os
import shutil
import subprocess
import uuid
from dataclasses import dataclass
from functools import cached_property
from pathlib import Path
from typing import List
from typing import Tuple
from typing import Union
import allel
import multiprocess as mp
import numpy... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/calc.py | pixy/calc.py | from collections import Counter
from typing import Any
from typing import Counter as CounterType
from typing import List
from typing import Tuple
from typing import Union
import allel
import numpy as np
from allel import AlleleCountsArray
from allel import GenotypeArray
from numpy.typing import NDArray
from scipy impo... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/__init__.py | pixy/__init__.py | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false | |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/stats/summary.py | pixy/stats/summary.py | """Compute summary statistics."""
import argparse
from itertools import combinations
from typing import Dict
from typing import List
from typing import Tuple
from typing import Union
from typing import cast
import numpy as np
from allel import AlleleCountsArray
from allel import GenotypeArray
from allel import Genoty... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/pixy/stats/__init__.py | pixy/stats/__init__.py | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false | |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/tests/test_calc.py | tests/test_calc.py | import allel
import numpy as np
import pytest
from allel import AlleleCountsArray
from allel import GenotypeArray
from allel import hudson_fst
from allel import mean_pairwise_difference
from allel import mean_pairwise_difference_between
from allel import watterson_theta
from allel import weir_cockerham_fst
from pixy.c... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | true |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/tests/conftest.py | tests/conftest.py | import sys
from pathlib import Path
from typing import List
from typing import Optional
from unittest.mock import patch
import pandas as pd
import pytest
from pixy.__main__ import main
################################################################################
# Fixtures for testing input + output locations
###... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/tests/__init__.py | tests/__init__.py | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false | |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/tests/stats/test_models.py | tests/stats/test_models.py | from typing import Union
import pytest
from pixy.args_validation import PixyStat
from pixy.models import NA
from pixy.models import PixyTempResult
@pytest.mark.parametrize(
"pixy_stat, pop1, pop2, chr, pos_1, pos_2, calculated_stat, shared, diffs, comps, missing,"
"expected_str",
[
(
... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/tests/main/test_main.py | tests/main/test_main.py | import logging
import os
import shutil
from pathlib import Path
from typing import List
from typing import Optional
from unittest.mock import patch
import pytest
from tests.conftest import assert_files_are_consistent
from tests.conftest import run_pixy_helper
#########################################################... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/tests/args_validation/test_args_validation.py | tests/args_validation/test_args_validation.py | import argparse
from pathlib import Path
import pytest
from pixy.args_validation import PixyArgs
from pixy.args_validation import check_and_validate_args
@pytest.mark.parametrize("bypass_variant_check", [True, False])
def test_check_and_validate_args(
ag1000_vcf_path: Path,
ag1000_pop_path: Path,
bypass... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
ksamuk/pixy | https://github.com/ksamuk/pixy/blob/7ceab4530d2bfbaea6e7fab4fb782e64b2d83156/docs/conf.py | docs/conf.py | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... | python | MIT | 7ceab4530d2bfbaea6e7fab4fb782e64b2d83156 | 2026-01-05T07:08:43.851194Z | false |
AIAnytime/Document-Buddy-App | https://github.com/AIAnytime/Document-Buddy-App/blob/c34bd80fb7f83ab3b28365ffe320a750f19caa96/vectors.py | vectors.py | import os
from langchain_community.document_loaders import UnstructuredPDFLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import Qdrant
import streamlit as st
class EmbeddingsManager:
d... | python | MIT | c34bd80fb7f83ab3b28365ffe320a750f19caa96 | 2026-01-05T07:08:49.962939Z | false |
AIAnytime/Document-Buddy-App | https://github.com/AIAnytime/Document-Buddy-App/blob/c34bd80fb7f83ab3b28365ffe320a750f19caa96/chatbot.py | chatbot.py | # chatbot.py
import os
from langchain_community.embeddings import HuggingFaceBgeEmbeddings
from langchain_community.vectorstores import Qdrant
from langchain_ollama import ChatOllama
from qdrant_client import QdrantClient
from langchain import PromptTemplate
from langchain.chains import RetrievalQA
import streamlit as... | python | MIT | c34bd80fb7f83ab3b28365ffe320a750f19caa96 | 2026-01-05T07:08:49.962939Z | false |
AIAnytime/Document-Buddy-App | https://github.com/AIAnytime/Document-Buddy-App/blob/c34bd80fb7f83ab3b28365ffe320a750f19caa96/new.py | new.py | # app.py
import streamlit as st
from streamlit import session_state
import time
import base64
import os
from vectors import EmbeddingsManager # Import the EmbeddingsManager class
from chatbot import ChatbotManager # Import the ChatbotManager class
# Function to display the PDF of a given file
def displayPDF(file... | python | MIT | c34bd80fb7f83ab3b28365ffe320a750f19caa96 | 2026-01-05T07:08:49.962939Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/export_onnx.py | model_convert/export_onnx.py | # Copyright (c) 2021 Binbin Zhang(binbzha@qq.com)
# Copyright (c) 2024 Yang Chen (cyang8050@163.com)
#
# 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/LIC... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/subsampling.py | model_convert/model/subsampling.py | # Copyright (c) 2021 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/mdtc.py | model_convert/model/mdtc.py | #!/usr/bin/env python3
# Copyright (c) 2021 Jingyong Hou (houjingyong@gmail.com)
#
# 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 re... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/tcn.py | model_convert/model/tcn.py | #!/usr/bin/env python3
# Copyright (c) 2021 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/kws_model.py | model_convert/model/kws_model.py | # Copyright (c) 2021 Binbin Zhang
# 2023 Jing Du
#
# 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 applic... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/cmvn.py | model_convert/model/cmvn.py | #!/usr/bin/env python3
# Copyright (c) 2020 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/loss.py | model_convert/model/loss.py | # Copyright (c) 2021 Binbin Zhang
# 2023 Jing Du
#
# 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 applic... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/classifier.py | model_convert/model/classifier.py | # Copyright (c) 2021 Jingyong Hou
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/model/fsmn.py | model_convert/model/fsmn.py | '''
FSMN implementation.
Copyright: 2022-03-09 yueyue.nyy
2023 Jing Du
'''
from typing import Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def toKaldiMatrix(np_mat):
np.set_printoptions(threshold=np.inf, linewidth=np.nan)
out_str = str(np_mat)... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/utils/file_utils.py | model_convert/utils/file_utils.py | # Copyright (c) 2021 Mobvoi Inc. (authors: Binbin Zhang)
#
# 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 l... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/utils/train_utils.py | model_convert/utils/train_utils.py | #!/usr/bin/env python3
# Copyright (c) 2021 Jingyong Hou (houjingyong@gmail.com)
#
# 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 re... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/utils/executor.py | model_convert/utils/executor.py | # Copyright (c) 2021 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/utils/checkpoint.py | model_convert/utils/checkpoint.py | # Copyright (c) 2021 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/utils/mask.py | model_convert/utils/mask.py | # Copyright (c) 2021 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
chenyangMl/keyword-spot | https://github.com/chenyangMl/keyword-spot/blob/269d3853ea4d84dfba391a2aec2bf51e0e396d0a/model_convert/utils/cmvn.py | model_convert/utils/cmvn.py | #!/usr/bin/env python3
# Copyright (c) 2020 Binbin Zhang
#
# 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... | python | MIT | 269d3853ea4d84dfba391a2aec2bf51e0e396d0a | 2026-01-05T07:08:50.083450Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/setup.py | model/parler-tts/setup.py | # Copyright 2024 The HuggingFace Team. 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 applicabl... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/gradio_demo/app.py | model/parler-tts/helpers/gradio_demo/app.py | import gradio as gr
import torch
from transformers import AutoFeatureExtractor, AutoTokenizer, set_seed
from parler_tts import ParlerTTSForConditionalGeneration
device = "cuda:0" if torch.cuda.is_available() else "cpu"
repo_id = "parler-tts/parler_tts_mini_v0.1"
model = ParlerTTSForConditionalGeneration.from_pretr... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/model_init_scripts/init_large_model.py | model/parler-tts/helpers/model_init_scripts/init_large_model.py | from parler_tts import ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration, ParlerTTSDecoderConfig
from transformers import AutoConfig
import os
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("save_directory", type=str, help="Directory where to save the m... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/model_init_scripts/init_dummy_model.py | model/parler-tts/helpers/model_init_scripts/init_dummy_model.py | import argparse
import os
from transformers import AutoConfig
from parler_tts import ParlerTTSDecoderConfig, ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("save_directory", type=str, help="Directory where to save the... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/model_init_scripts/init_dummy_model_with_encodec.py | model/parler-tts/helpers/model_init_scripts/init_dummy_model_with_encodec.py | import argparse
import os
from transformers import AutoConfig
from parler_tts import ParlerTTSDecoderConfig, ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("save_directory", type=str, help="Directory where to save the... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/model_init_scripts/init_model_600M.py | model/parler-tts/helpers/model_init_scripts/init_model_600M.py | import argparse
import os
from transformers import AutoConfig
from parler_tts import ParlerTTSDecoderConfig, ParlerTTSForCausalLM, ParlerTTSForConditionalGeneration
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("save_directory", type=str, help="Directory where to save the... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/push_to_hub_scripts/push_trained_parler_tts_to_hub.py | model/parler-tts/helpers/push_to_hub_scripts/push_trained_parler_tts_to_hub.py | from transformers import AutoFeatureExtractor, AutoTokenizer
from parler_tts import ParlerTTSForConditionalGeneration
path = "TODO"
repo_id = "parler_tts_600M"
AutoFeatureExtractor.from_pretrained("ylacombe/dac_44khZ_8kbps").push_to_hub(repo_id)
AutoTokenizer.from_pretrained("google/t5-v1_1-base").push_to_hub(repo... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/helpers/push_to_hub_scripts/push_dac_to_hub.py | model/parler-tts/helpers/push_to_hub_scripts/push_dac_to_hub.py | import dac
from transformers import AutoConfig, AutoModel, EncodecFeatureExtractor
from parler_tts import DACConfig, DACModel
from transformers import AutoConfig, AutoModel
from transformers import EncodecFeatureExtractor
from importlib.metadata import version
from packaging.version import Version
if Version(version... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/configuration_parler_tts.py | model/parler-tts/parler_tts/configuration_parler_tts.py | # coding=utf-8
# Copyright 2024 and The HuggingFace Inc. team. 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
#
# Unle... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/logits_processors.py | model/parler-tts/parler_tts/logits_processors.py | from transformers import LogitsProcessor, LogitsProcessorList
from transformers.pytorch_utils import isin_mps_friendly
import math
import torch
class ParlerTTSLogitsProcessor(LogitsProcessor):
r"""This processor ensures that the delayed pattern mask constraints are respected.
<Tip warning={true}>
This lo... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/__init__.py | model/parler-tts/parler_tts/__init__.py | __version__ = "0.2.2"
from transformers import AutoConfig, AutoModel
from .configuration_parler_tts import ParlerTTSConfig, ParlerTTSDecoderConfig
from .dac_wrapper import DACConfig, DACModel
from .modeling_parler_tts import (
ParlerTTSForCausalLM,
ParlerTTSForConditionalGeneration,
apply_delay_pattern_m... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/modeling_parler_tts.py | model/parler-tts/parler_tts/modeling_parler_tts.py | # coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. 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 r... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | true |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/streamer.py | model/parler-tts/parler_tts/streamer.py |
from .modeling_parler_tts import ParlerTTSForConditionalGeneration
from transformers.generation.streamers import BaseStreamer
from typing import Optional
import torch
import numpy as np
import math
from queue import Queue
class ParlerTTSStreamer(BaseStreamer):
def __init__(
self,
model: ParlerTTS... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/dac_wrapper/configuration_dac.py | model/parler-tts/parler_tts/dac_wrapper/configuration_dac.py |
from transformers import PretrainedConfig
from importlib.metadata import version
from packaging.version import Version
class DACConfig(PretrainedConfig):
model_type = "dac" if Version(version("transformers"))<= Version("4.44.2dev") else "dac_on_the_hub"
def __init__(
self,
num_codebooks: int... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/dac_wrapper/modeling_dac.py | model/parler-tts/parler_tts/dac_wrapper/modeling_dac.py | import torch
from dac.model import DAC
from torch import nn
from transformers import PreTrainedModel
from transformers.models.encodec.modeling_encodec import EncodecDecoderOutput, EncodecEncoderOutput
from .configuration_dac import DACConfig
# model doesn't support batching yet
class DACModel(PreTrainedModel):
... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/parler_tts/dac_wrapper/__init__.py | model/parler-tts/parler_tts/dac_wrapper/__init__.py | from .configuration_dac import DACConfig
from .modeling_dac import DACModel
| python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/training/eval.py | model/parler-tts/training/eval.py | import torch
from torchaudio.pipelines import SQUIM_OBJECTIVE
import torchaudio
import evaluate
from transformers import (
AutoModel,
AutoProcessor,
pipeline,
WhisperForConditionalGeneration,
WhisperTokenizer,
WhisperTokenizerFast,
)
from accelerate.utils.memory import release_memory
import nump... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/training/arguments.py | model/parler-tts/training/arguments.py | from dataclasses import dataclass, field
from typing import Optional, List
from transformers import Seq2SeqTrainingArguments
@dataclass
class ModelArguments:
"""
Arguments pertaining to which model/config/tokenizer we are going to fine-tune from.
"""
model_name_or_path: str = field(
metadata... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/training/utils.py | model/parler-tts/training/utils.py | import os
import re
import shutil
from dataclasses import field
from pathlib import Path
from typing import Dict, List
import torch
from datasets import concatenate_datasets, load_from_disk
from wandb import Audio
from datasets import load_from_disk, concatenate_datasets
def list_field(default=None, metadata=None):
... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/training/run_parler_tts_training.py | model/parler-tts/training/run_parler_tts_training.py | #!/usr/bin/env python
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. 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/LI... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | true |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/training/__init__.py | model/parler-tts/training/__init__.py | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false | |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/parler-tts/training/data.py | model/parler-tts/training/data.py | import logging
from dataclasses import dataclass
from typing import Dict, List, Optional, Set, Union
import datasets
import numpy as np
import torch
from accelerate import Accelerator
from datasets import Dataset, IterableDataset, concatenate_datasets, interleave_datasets, load_dataset
from tqdm import tqdm
from trans... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/inference/run_inference.py | model/inference/run_inference.py | import argparse
import torch
from parler_tts import ParlerTTSForConditionalGeneration
from transformers import AutoTokenizer, pipeline, WhisperForConditionalGeneration, WhisperTokenizer, WhisperTokenizerFast
import soundfile as sf
import evaluate
def wer(asr_pipeline, prompt, audio, sampling_rate):
"""
Calcula... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/model/inference/run_inference_gradio_app.py | model/inference/run_inference_gradio_app.py | import gradio as gr
import torch
from parler_tts import ParlerTTSForConditionalGeneration
from transformers import AutoTokenizer, pipeline, WhisperForConditionalGeneration, WhisperTokenizer, WhisperTokenizerFast
import numpy as np
import evaluate
# Example prompts from the paper (only style and text)
EXAMPLES = [
... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/dataset/audio_preprocessing/apply_expresso_vad.py | dataset/audio_preprocessing/apply_expresso_vad.py | import argparse
from pathlib import Path
import pydub
import sys
def load_vad_segments(vad_file):
"""Load VAD segments from file into a nested dictionary."""
vad_segments = {} # {filename: {channel: [(start, end)]}}
with open(vad_file, 'r') as f:
for line in f:
line = line.strip()... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/dataset/audio_preprocessing/add_real_audio_paths.py | dataset/audio_preprocessing/add_real_audio_paths.py | import argparse
from pathlib import Path
from datasets import load_dataset
def add_audio_paths(example, source_to_root, validate_exists=False):
"""Adds real audio path to a single example."""
source = example["source"]
if source not in source_to_root:
raise ValueError(f"Unknown source dataset: {sou... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
ajd12342/paraspeechcaps | https://github.com/ajd12342/paraspeechcaps/blob/9a5e98892fbae54fcc6b56dc3bb755af5ca47601/dataset/audio_preprocessing/apply_voicefixer.py | dataset/audio_preprocessing/apply_voicefixer.py | import voicefixer
from pathlib import Path
import sys
from pydub import AudioSegment, effects
import argparse
def apply_voicefixer(model, input_audio_path, output_audio_path):
"""Apply voicefixer to a single audio file and normalize the output."""
if output_audio_path.exists():
return
model.re... | python | MIT | 9a5e98892fbae54fcc6b56dc3bb755af5ca47601 | 2026-01-05T07:08:54.013665Z | false |
DadaNanjesha/AI-Text-Humanizer-App | https://github.com/DadaNanjesha/AI-Text-Humanizer-App/blob/eeea9f13805d21a91071beae0f1403fcfe9165b1/main.py | main.py | import streamlit as st
from transformer.app import AcademicTextHumanizer, NLP_GLOBAL, download_nltk_resources
from nltk.tokenize import word_tokenize
import difflib
def main():
"""
The `main` function sets up a Streamlit page for transforming user-provided text into a more formal
academic style by expand... | python | MIT | eeea9f13805d21a91071beae0f1403fcfe9165b1 | 2026-01-05T07:08:59.727233Z | false |
DadaNanjesha/AI-Text-Humanizer-App | https://github.com/DadaNanjesha/AI-Text-Humanizer-App/blob/eeea9f13805d21a91071beae0f1403fcfe9165b1/transformer/__init__.py | transformer/__init__.py | python | MIT | eeea9f13805d21a91071beae0f1403fcfe9165b1 | 2026-01-05T07:08:59.727233Z | false | |
DadaNanjesha/AI-Text-Humanizer-App | https://github.com/DadaNanjesha/AI-Text-Humanizer-App/blob/eeea9f13805d21a91071beae0f1403fcfe9165b1/transformer/app.py | transformer/app.py | import ssl
import random
import warnings
import nltk
import spacy
from nltk.tokenize import word_tokenize
from nltk.corpus import wordnet
from sentence_transformers import SentenceTransformer, util
warnings.filterwarnings("ignore", category=FutureWarning)
NLP_GLOBAL = spacy.load("en_core_web_sm")
def download_nltk_... | python | MIT | eeea9f13805d21a91071beae0f1403fcfe9165b1 | 2026-01-05T07:08:59.727233Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/batch_normalization/__init__.py | batch_normalization/__init__.py | """Example of batch normalization tackling a difficult optimization.
Running with --no-batch-normalize, we see that the algorithm makes very
very slow progress in the same amount of time.
"""
import argparse
from theano import tensor
from blocks.algorithms import Adam, GradientDescent
from blocks.bricks import MLP, B... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/sqrt/__main__.py | sqrt/__main__.py | """Super-basic example, mainly for testing purposes.
This script trains a tiny network to compute square roots.
"""
import argparse
import logging
from sqrt import main
if __name__ == "__main__":
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s: %(name)s: %(levelname)s: %(message)s"... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/sqrt/__init__.py | sqrt/__init__.py | import numpy
import theano
from theano import tensor
from blocks.algorithms import GradientDescent, Scale
from blocks.bricks import MLP, Tanh, Identity
from blocks.bricks.cost import SquaredError
from blocks.graph import ComputationGraph
from blocks.initialization import IsotropicGaussian, Constant
from blocks.model ... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/stream.py | machine_translation/stream.py | import numpy
from fuel.datasets import TextFile
from fuel.schemes import ConstantScheme
from fuel.streams import DataStream
from fuel.transformers import (
Merge, Batch, Filter, Padding, SortMapping, Unpack, Mapping)
from six.moves import cPickle
def _ensure_special_tokens(vocab, bos_idx=0, eos_idx=0, unk_idx=1... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/sampling.py | machine_translation/sampling.py | from __future__ import print_function
import logging
import numpy
import operator
import os
import re
import signal
import time
from blocks.extensions import SimpleExtension
from blocks.search import BeamSearch
from subprocess import Popen, PIPE
logger = logging.getLogger(__name__)
class SamplingBase(object):
... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/model.py | machine_translation/model.py |
from theano import tensor
from toolz import merge
from blocks.bricks import (Tanh, Maxout, Linear, FeedforwardSequence,
Bias, Initializable, MLP)
from blocks.bricks.attention import SequenceContentAttention
from blocks.bricks.base import application
from blocks.bricks.lookup import LookupTa... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/__main__.py | machine_translation/__main__.py | """Encoder-Decoder with search for machine translation.
In this demo, encoder-decoder architecture with attention mechanism is used for
machine translation. The attention mechanism is implemented according to
[BCB]_. The training data used is WMT15 Czech to English corpus, which you have
to download, preprocess and pu... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/checkpoint.py | machine_translation/checkpoint.py |
import logging
import numpy
import os
import time
from contextlib import closing
from six.moves import cPickle
from blocks.extensions.saveload import SAVED_TO, LOADED_FROM
from blocks.extensions import TrainingExtension, SimpleExtension
from blocks.serialization import secure_dump, load, BRICK_DELIMITER
from blocks.... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/configurations.py | machine_translation/configurations.py | def get_config_cs2en():
config = {}
# Model related -----------------------------------------------------------
# Sequences longer than this will be discarded
config['seq_len'] = 50
# Number of hidden units in encoder/decoder GRU
config['enc_nhids'] = 1000
config['dec_nhids'] = 1000
... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/__init__.py | machine_translation/__init__.py | import logging
from collections import Counter
from theano import tensor
from toolz import merge
from blocks.algorithms import (GradientDescent, StepClipping, AdaDelta,
CompositeRule)
from blocks.extensions import FinishAfter, Printing
from blocks.extensions.monitoring import TrainingDa... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/machine_translation/prepare_data.py | machine_translation/prepare_data.py | #!/usr/bin/python
import argparse
import logging
import os
import subprocess
import tarfile
import urllib2
import uuid
from picklable_itertools.extras import equizip
TRAIN_DATA_URL = 'http://www.statmt.org/wmt15/training-parallel-nc-v10.tgz'
VALID_DATA_URL = 'http://www.statmt.org/wmt15/dev-v2.tgz'
PREPROCESS_URL = ... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_markov_chain.py | tests/test_markov_chain.py | import tempfile
from markov_chain import main
def test_markov_chain():
with tempfile.NamedTemporaryFile() as f:
main("train", f.name, None, 10)
| python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_parity_problem.py | tests/test_parity_problem.py | from parity_problem import main
def test_parity_problem():
main_loop = main(20, 1, 10, 10, 1)
assert main_loop.log.status['epochs_done'] == 1
assert main_loop.log.status['iterations_done'] == 10
| python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_mnist.py | tests/test_mnist.py | import tempfile
from blocks.serialization import load
from mnist import main
def test_mnist():
with tempfile.NamedTemporaryFile() as f:
main(f.name, 1)
with open(f.name, "rb") as source:
main_loop = load(source)
main_loop.find_extension("FinishAfter").set_conditions(
... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_batch_normalization.py | tests/test_batch_normalization.py | from batch_normalization import main
def test_batch_normalization_example():
bn_main_loop = main(num_epochs=2)
assert bn_main_loop.log.current_row['test_misclass'] < 0.62
assert bn_main_loop.log.current_row['train_misclass'] < 0.6
nbn_main_loop = main(num_epochs=2, batch_normalized=False)
assert n... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_sqrt.py | tests/test_sqrt.py | import tempfile
from blocks.extensions.saveload import SAVED_TO
from sqrt import main
def test_sqrt():
save_path = tempfile.mktemp()
main_loop = main(save_path, 7)
assert main_loop.log[7][SAVED_TO][0] == save_path
| python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_mnist_lenet.py | tests/test_mnist_lenet.py | import tempfile
from blocks.serialization import load
from mnist_lenet import main
def test_mnist_lenet():
with tempfile.NamedTemporaryFile() as f:
main(f.name, 1, num_batches=3)
with open(f.name, "rb") as source:
main_loop = load(source)
main_loop.find_extension("FinishAfter").se... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/__init__.py | tests/__init__.py | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false | |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_reverse_words.py | tests/test_reverse_words.py | from __future__ import print_function
import tempfile
import sys
from six.moves import StringIO
from blocks.config import config
from reverse_words import main
def test_reverse_words():
old_limit = config.recursion_limit
config.recursion_limit = 100000
with tempfile.NamedTemporaryFile() as f_save,\
... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/tests/test_machine_translation.py | tests/test_machine_translation.py | import numpy
import tempfile
import theano
from blocks.initialization import IsotropicGaussian, Orthogonal, Constant
from blocks.model import Model
from machine_translation.model import BidirectionalEncoder, Decoder
from machine_translation.stream import get_tr_stream, get_dev_stream
from numpy.testing import assert... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/markov_chain/dataset.py | markov_chain/dataset.py | """Defines the dataset for a Markov chain.
Has to be in a separate module from the main script in order to be
unpicklable by a third party.
"""
import numpy
import copy
from fuel.datasets import Dataset
class MarkovChainDataset(Dataset):
"""Training data generator."""
num_states = 3
trans_prob = numpy.... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/markov_chain/__main__.py | markov_chain/__main__.py | import argparse
import logging
from . import main
if __name__ == "__main__":
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s: %(name)s: %(levelname)s: %(message)s")
parser = argparse.ArgumentParser(
"Case study of generating a Markov chain with RNN.",
formatter_cla... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/markov_chain/__init__.py | markov_chain/__init__.py | #!/usr/bin/env python
"""Learn a Markov chain with an RNN and sample from it."""
from __future__ import print_function
import logging
import pprint
import sys
from six.moves import cPickle
import numpy
import theano
from theano import tensor
from blocks.bricks import Tanh
from blocks.bricks.recurrent import GatedRec... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/parity_problem/__main__.py | parity_problem/__main__.py | """This example shows how to train a simple RNN for the sequence classification
task: given a sequence of 0s and 1s, determine whether number of 1s in it
is odd or even
"""
import argparse
import logging
from parity_problem import main
if __name__ == "__main__":
logging.basicConfig(
level=logging.INFO,
... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/parity_problem/__init__.py | parity_problem/__init__.py | from __future__ import print_function
import random
import numpy as np
import theano
import theano.tensor as T
from fuel.streams import DataStream
from fuel.datasets import IterableDataset
from blocks.bricks import Linear, Logistic
from blocks.bricks.recurrent import LSTM
from blocks.bricks.cost import BinaryCrossEn... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/reverse_words/__main__.py | reverse_words/__main__.py | #!/usr/bin/env python
"""Learn to reverse the letters in each word in text
In this demo, a recurrent network equipped with an attention mechanism
learns to reverse each word (on a character-by-character basis) in
its input text. The default training data is the Google Billion Word corpus,
which you should download a... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/reverse_words/__init__.py | reverse_words/__init__.py | from __future__ import print_function
import logging
import pprint
import math
import numpy
import traceback
import operator
import theano
from six.moves import input
from picklable_itertools.extras import equizip
from theano import tensor
from blocks.bricks import Tanh, Initializable
from blocks.bricks.base import a... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/mnist_lenet/__init__.py | mnist_lenet/__init__.py | """Convolutional network example.
Run the training for 50 epochs with
```
python __init__.py --num-epochs 50
```
It is going to reach around 0.8% error rate on the test set.
"""
import logging
import numpy
from argparse import ArgumentParser
from theano import tensor
from blocks.algorithms import GradientDescent, S... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
mila-iqia/blocks-examples | https://github.com/mila-iqia/blocks-examples/blob/7d30adff73140b6a873047b062077b4c12bd9099/mnist/__init__.py | mnist/__init__.py | #!/usr/bin/env python
import logging
from argparse import ArgumentParser
from theano import tensor
from blocks.algorithms import GradientDescent, Scale
from blocks.bricks import MLP, Tanh, Softmax
from blocks.bricks.cost import CategoricalCrossEntropy, MisclassificationRate
from blocks.initialization import Isotropi... | python | MIT | 7d30adff73140b6a873047b062077b4c12bd9099 | 2026-01-05T07:09:00.712415Z | false |
vintasoftware/django-zombodb | https://github.com/vintasoftware/django-zombodb/blob/2391f27709819bd135e3d0dd571ef42e6996a201/test_manage.py | test_manage.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
import os
import sys
if __name__ == "__main__":
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "tests.settings")
from django.core.management import execute_from_command_line
execute_from_command_line(... | python | MIT | 2391f27709819bd135e3d0dd571ef42e6996a201 | 2026-01-05T07:09:01.604399Z | false |
vintasoftware/django-zombodb | https://github.com/vintasoftware/django-zombodb/blob/2391f27709819bd135e3d0dd571ef42e6996a201/setup.py | setup.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import re
import sys
try:
from setuptools import setup
except ImportError:
from distutils.core import setup
def get_version(*file_paths):
"""Retrieves the version from django_zombodb/__init__.py"""
filename = os.path.join(os.path.dirname(__file... | python | MIT | 2391f27709819bd135e3d0dd571ef42e6996a201 | 2026-01-05T07:09:01.604399Z | false |
vintasoftware/django-zombodb | https://github.com/vintasoftware/django-zombodb/blob/2391f27709819bd135e3d0dd571ef42e6996a201/runtests.py | runtests.py | #!/usr/bin/env python
# -*- coding: utf-8
from __future__ import absolute_import, unicode_literals
import os
import sys
from django.core.management import execute_from_command_line
def runtests():
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "tests.settings")
argv = sys.argv[:1] + ['test'] + sys.argv[1:]... | python | MIT | 2391f27709819bd135e3d0dd571ef42e6996a201 | 2026-01-05T07:09:01.604399Z | false |
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