repo_id stringlengths 6 101 | file_path stringlengths 2 269 | content stringlengths 367 5.14M | size int64 367 5.14M | filename stringlengths 1 248 | ext stringlengths 0 87 | lang stringclasses 88
values | program_lang stringclasses 232
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values | quality_signal stringlengths 2 1.9k | effective stringclasses 2
values | hit_map stringlengths 2 1.4k |
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1y33/100Days | day05/vectorSumTricks.cu | #include <iostream>
#include <cuda_runtime.h>
#include <chrono>
__global__ void sumKernel(
const float *vector_pointer,
float *output,
const int size)
{
extern __shared__ float sharedData[]; // shared memory for partial sums
int ti = threadIdx.x; // thread index in ... | 3,880 | vectorSumTricks | cu | en | cuda | code | {"qsc_code_num_words": 437, "qsc_code_num_chars": 3880.0, "qsc_code_mean_word_length": 5.44393593, "qsc_code_frac_words_unique": 0.32723112, "qsc_code_frac_chars_top_2grams": 0.01765448, "qsc_code_frac_chars_top_3grams": 0.02185792, "qsc_code_frac_chars_top_4grams": 0.03867171, "qsc_code_frac_chars_dupe_5grams": 0.0651... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day63/lstm.py | import torch
import triton
import triton.language as tl
@triton.jit
def lstm_kernel(
input_ptr, h_prev_ptr, c_prev_ptr,
weights_ptr, biases_ptr,
h_new_ptr, c_new_ptr,
N, D: tl.constexpr, H: tl.constexpr, K,
stride_input_n, stride_input_d,
stride_h_prev_n, stride_h_prev_h,
stride_c_prev_n, s... | 6,290 | lstm | py | en | python | code | {"qsc_code_num_words": 1085, "qsc_code_num_chars": 6290.0, "qsc_code_mean_word_length": 3.46728111, "qsc_code_frac_words_unique": 0.13364055, "qsc_code_frac_chars_top_2grams": 0.02923977, "qsc_code_frac_chars_top_3grams": 0.03349282, "qsc_code_frac_chars_top_4grams": 0.03402446, "qsc_code_frac_chars_dupe_5grams": 0.390... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day11/test.py | import torch
from torch.utils.cpp_extension import load
def speed_test():
size = [1, 1000000] # Batch size 1, dimension 1M
A_large = torch.rand(size=size, device='cuda', dtype=torch.float32)
num_runs = 100 # Number of iterations for timing
def time_function(func, *args,**kwargs):
torch.... | 3,306 | test | py | en | python | code | {"qsc_code_num_words": 480, "qsc_code_num_chars": 3306.0, "qsc_code_mean_word_length": 4.52708333, "qsc_code_frac_words_unique": 0.19166667, "qsc_code_frac_chars_top_2grams": 0.02485044, "qsc_code_frac_chars_top_3grams": 0.05890474, "qsc_code_frac_chars_top_4grams": 0.0478601, "qsc_code_frac_chars_dupe_5grams": 0.31477... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day11/binding.cpp | #include <torch/extension.h>
#include "ATen/ATen.h"
void CudaLeakyReLU(float *A,float*B,float slope ,int N);
torch::Tensor LeakyReLU(torch::Tensor A, float slope){
torch::Tensor B = torch::empty_like(A);
int N = A.numel();
CudaLeakyReLU(A.data_ptr<float>(),B.data_ptr<float>(),slope,N);
return B;
}
vo... | 1,690 | binding | cpp | en | cpp | code | {"qsc_code_num_words": 252, "qsc_code_num_chars": 1690.0, "qsc_code_mean_word_length": 4.28968254, "qsc_code_frac_words_unique": 0.17460317, "qsc_code_frac_chars_top_2grams": 0.16281221, "qsc_code_frac_chars_top_3grams": 0.12210916, "qsc_code_frac_chars_top_4grams": 0.05550416, "qsc_code_frac_chars_dupe_5grams": 0.3237... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/layui/layui.min.js | /** layui-v2.7.5 MIT License By https://www.layui.com */
!function(win){var doc=win.document,config={modules:{},status:{},timeout:10,event:{}},Layui=function(){this.v="2.7.5"},GLOBAL=win.LAYUI_GLOBAL||{},getPath=function(){var jsPath=doc.currentScript?doc.currentScript.src:function(){var js=doc.scripts,last=js.length-1... | 12,192 | layui.min | js | en | javascript | code | {"qsc_code_num_words": 1765, "qsc_code_num_chars": 12192.0, "qsc_code_mean_word_length": 5.02322946, "qsc_code_frac_words_unique": 0.16147309, "qsc_code_frac_chars_top_2grams": 0.04737198, "qsc_code_frac_chars_top_3grams": 0.01488834, "qsc_code_frac_chars_top_4grams": 0.01624182, "qsc_code_frac_chars_dupe_5grams": 0.12... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1x-technologies/1xgpt | train.py | import argparse
import contextlib
import logging
import math
import os
import time
import matplotlib
import mup
import numpy as np
import torch
import torchvision.transforms.functional as transforms_f
from accelerate import Accelerator
from accelerate.logging import get_logger
from accelerate.utils import set_seed
fro... | 31,552 | train | py | en | python | code | {"qsc_code_num_words": 3745, "qsc_code_num_chars": 31552.0, "qsc_code_mean_word_length": 5.04753004, "qsc_code_frac_words_unique": 0.17730307, "qsc_code_frac_chars_top_2grams": 0.01618791, "qsc_code_frac_chars_top_3grams": 0.03057716, "qsc_code_frac_chars_top_4grams": 0.01840978, "qsc_code_frac_chars_dupe_5grams": 0.28... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/АнализОпроса/Templates/МакетОтветы/Ext/Template.xml | <?xml version="1.0" encoding="UTF-8"?>
<document xmlns="http://v8.1c.ru/8.2/data/spreadsheet" xmlns:style="http://v8.1c.ru/8.1/data/ui/style" xmlns:v8="http://v8.1c.ru/8.1/data/core" xmlns:v8ui="http://v8.1c.ru/8.1/data/ui" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instanc... | 14,586 | Template | xml | en | xml | data | {"qsc_code_num_words": 1757, "qsc_code_num_chars": 14586.0, "qsc_code_mean_word_length": 5.03642573, "qsc_code_frac_words_unique": 0.12293682, "qsc_code_frac_chars_top_2grams": 0.01536897, "qsc_code_frac_chars_top_3grams": 0.00847553, "qsc_code_frac_chars_top_4grams": 0.06237993, "qsc_code_frac_chars_dupe_5grams": 0.76... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/jsonview/jquery.jsonview.js | (function(jQuery) {
var $, Collapser, JSONFormatter, JSONView;
JSONFormatter = (function() {
function JSONFormatter(options) {
if (options == null) {
options = {};
}
this.options = options;
}
JSONFormatter.prototype.htmlEncode = function(html) {
if (html !== null) {
... | 8,036 | jquery.jsonview | js | en | javascript | code | {"qsc_code_num_words": 719, "qsc_code_num_chars": 8036.0, "qsc_code_mean_word_length": 6.05841446, "qsc_code_frac_words_unique": 0.18358832, "qsc_code_frac_chars_top_2grams": 0.02984389, "qsc_code_frac_chars_top_3grams": 0.00918274, "qsc_code_frac_chars_top_4grams": 0.01285583, "qsc_code_frac_chars_dupe_5grams": 0.2536... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1x-technologies/1xgpt | data.py | import json
import math
import os
import random
from pathlib import Path
import numpy as np
import torch
from einops import rearrange
from torch.utils.data import Dataset as TorchDataset
from genie.factorization_utils import factorize_token_ids, unfactorize_token_ids
from genie.config import GenieConfig
from genie.st... | 7,767 | data | py | en | python | code | {"qsc_code_num_words": 1038, "qsc_code_num_chars": 7767.0, "qsc_code_mean_word_length": 4.45375723, "qsc_code_frac_words_unique": 0.27649326, "qsc_code_frac_chars_top_2grams": 0.02725503, "qsc_code_frac_chars_top_3grams": 0.02768765, "qsc_code_frac_chars_top_4grams": 0.02336145, "qsc_code_frac_chars_dupe_5grams": 0.160... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/jsonview/jquery.jsonview.css | @charset "UTF-8";
.jsonview {
font-family: monospace;
font-size: 1.1em;
white-space: pre-wrap; }
.jsonview .prop {
font-weight: bold; }
.jsonview .null {
color: red; }
.jsonview .bool {
color: blue; }
.jsonview .num {
color: blue; }
.jsonview .string {
color: green;
white-space: ... | 1,159 | jquery.jsonview | css | en | css | data | {"qsc_code_num_words": 130, "qsc_code_num_chars": 1159.0, "qsc_code_mean_word_length": 5.39230769, "qsc_code_frac_words_unique": 0.52307692, "qsc_code_frac_chars_top_2grams": 0.05563481, "qsc_code_frac_chars_top_3grams": 0.07703281, "qsc_code_frac_chars_top_4grams": 0.04850214, "qsc_code_frac_chars_dupe_5grams": 0.0713... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1x-technologies/1xgpt | visualize.py | #!/usr/bin/env python3
"""
Script to decode tokenized video into images/video.
Example usage: See https://github.com/1x-technologies/1xgpt?tab=readme-ov-file#1x-genie-baseline
"""
import argparse
import math
import os
from PIL import Image, ImageDraw
import numpy as np
import torch
import torch.distributed.optim
imp... | 7,458 | visualize | py | en | python | code | {"qsc_code_num_words": 975, "qsc_code_num_chars": 7458.0, "qsc_code_mean_word_length": 4.68615385, "qsc_code_frac_words_unique": 0.31076923, "qsc_code_frac_chars_top_2grams": 0.01969796, "qsc_code_frac_chars_top_3grams": 0.02757715, "qsc_code_frac_chars_top_4grams": 0.02516962, "qsc_code_frac_chars_dupe_5grams": 0.0914... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/АнализОпроса/Forms/ФормаОтчета/Ext/Form.xml | <?xml version="1.0" encoding="UTF-8"?>
<Form xmlns="http://v8.1c.ru/8.3/xcf/logform" xmlns:app="http://v8.1c.ru/8.2/managed-application/core" xmlns:cfg="http://v8.1c.ru/8.1/data/enterprise/current-config" xmlns:dcscor="http://v8.1c.ru/8.1/data-composition-system/core" xmlns:dcssch="http://v8.1c.ru/8.1/data-composition... | 7,503 | Form | xml | ru | xml | data | {"qsc_code_num_words": 819, "qsc_code_num_chars": 7503.0, "qsc_code_mean_word_length": 6.2026862, "qsc_code_frac_words_unique": 0.24542125, "qsc_code_frac_chars_top_2grams": 0.02362205, "qsc_code_frac_chars_top_3grams": 0.02519685, "qsc_code_frac_chars_top_4grams": 0.03149606, "qsc_code_frac_chars_dupe_5grams": 0.32952... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1xinghuan/usdNodeGraph | lib/python/usdNodeGraph/ui/graph/view.py | # -*- coding: utf-8 -*-
import os
import re
import json
import time
from pxr import Usd, Sdf, Ar
from usdNodeGraph.module.sqt import *
from usdNodeGraph.utils.const import VIEWPORT_FULL_UPDATE
from usdNodeGraph.core.node import (
Node, TransformNode, AttributeSetNode, MetadataNode,
RelationshipSetNode, Materia... | 48,807 | view | py | en | python | code | {"qsc_code_num_words": 4641, "qsc_code_num_chars": 48807.0, "qsc_code_mean_word_length": 6.31975867, "qsc_code_frac_words_unique": 0.1512605, "qsc_code_frac_chars_top_2grams": 0.00797818, "qsc_code_frac_chars_top_3grams": 0.00398909, "qsc_code_frac_chars_top_4grams": 0.00797818, "qsc_code_frac_chars_dupe_5grams": 0.209... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1xinghuan/usdNodeGraph | lib/python/usdNodeGraph/ui/parameter/register.py | from usdNodeGraph.core.parameter.basic import Parameter
from .param_widget import *
Parameter.registerParameter(StringParameter)
Parameter.registerParameter(ChooseParameter)
Parameter.registerParameter(TokenParameter)
Parameter.registerParameter(FilePathParameter)
Parameter.registerParameter(AssetParameter)
Parameter... | 4,568 | register | py | mr | python | code | {"qsc_code_num_words": 284, "qsc_code_num_chars": 4568.0, "qsc_code_mean_word_length": 14.40140845, "qsc_code_frac_words_unique": 0.38732394, "qsc_code_frac_chars_top_2grams": 0.37506112, "qsc_code_frac_chars_top_3grams": 0.01809291, "qsc_code_frac_chars_top_4grams": 0.0, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_co... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 1, "qsc_code_frac_chars_top_2grams": 1, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1xinghuan/usdNodeGraph | lib/python/usdNodeGraph/ui/other/timeSlider.py | from usdNodeGraph.module.sqt import *
from usdNodeGraph.core.state.core import GraphState
class LineEdit(QtWidgets.QLineEdit):
def __init__(self, text=""):
super(LineEdit, self).__init__()
self.setFixedHeight(30)
self.setText(text)
self.setAlignment(QtCore.Qt.AlignHCenter)
class... | 5,076 | timeSlider | py | en | python | code | {"qsc_code_num_words": 507, "qsc_code_num_chars": 5076.0, "qsc_code_mean_word_length": 6.29585799, "qsc_code_frac_words_unique": 0.26627219, "qsc_code_frac_chars_top_2grams": 0.03947368, "qsc_code_frac_chars_top_3grams": 0.0297619, "qsc_code_frac_chars_top_4grams": 0.02756892, "qsc_code_frac_chars_dupe_5grams": 0.07581... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/ПросроченныеЗадачи/Ext/ObjectModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 1,338 | ObjectModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 101, "qsc_code_num_chars": 1338.0, "qsc_code_mean_word_length": 9.18811881, "qsc_code_frac_words_unique": 0.75247525, "qsc_code_frac_chars_top_2grams": 0.00646552, "qsc_code_frac_chars_top_3grams": 0.00862069, "qsc_code_frac_chars_top_4grams": 0.08189655, "qsc_code_frac_chars_dupe_5grams": 0.0926... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1yefuwang1/vectorlite | README.md | 
# Overview
Vectorlite is a [Runtime-loadable extension](https://www.sqlite.org/loadext.html) for SQLite that enables fast vector search based on [hnswlib](https://github.com/nmslib/hnswlib) and works ... | 35,822 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.00189827, "qsc_doc_frac_words_redpajama_stop": 0.16224299, "qsc_doc_num_sentences": 666.0, "qsc_doc_num_words": 6378, "qsc_doc_num_chars": 35822.0, "qsc_doc_num_lines": 493.0, "qsc_doc_mean_word_length": 3.87096268, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_w... | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/js/jquery.tmpl.js | /*!
* jQuery Templates Plugin 1.0.0pre
* http://github.com/jquery/jquery-tmpl
* Requires jQuery 1.4.2
*
* Copyright 2011, Software Freedom Conservancy, Inc.
* Dual licensed under the MIT or GPL Version 2 licenses.
* http://jquery.org/license
*/
(function( factory ) {
if (typeof define === 'function' && define.... | 19,323 | jquery.tmpl | js | en | javascript | code | {"qsc_code_num_words": 2291, "qsc_code_num_chars": 19323.0, "qsc_code_mean_word_length": 5.25054561, "qsc_code_frac_words_unique": 0.20253165, "qsc_code_frac_chars_top_2grams": 0.01695902, "qsc_code_frac_chars_top_3grams": 0.00498795, "qsc_code_frac_chars_top_4grams": 0.00581927, "qsc_code_frac_chars_dupe_5grams": 0.03... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1xinghuan/usdNodeGraph | lib/python/usdNodeGraph/ui/graph/nodeItem/nodeItem.py | # -*- coding: utf-8 -*-
import traceback
from usdNodeGraph.module.sqt import *
from usdNodeGraph.ui.graph.other.port import InputPort, OutputPort
from usdNodeGraph.ui.graph.other.pipe import Pipe, ConnectionPipe
from ..const import *
from usdNodeGraph.utils.log import get_logger
import re
from usdNodeGraph.core.node i... | 18,545 | nodeItem | py | en | python | code | {"qsc_code_num_words": 1903, "qsc_code_num_chars": 18545.0, "qsc_code_mean_word_length": 5.84130321, "qsc_code_frac_words_unique": 0.17708881, "qsc_code_frac_chars_top_2grams": 0.01133501, "qsc_code_frac_chars_top_3grams": 0.00971573, "qsc_code_frac_chars_top_4grams": 0.01169485, "qsc_code_frac_chars_dupe_5grams": 0.19... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1yefuwang1/vectorlite | setup.py | from distutils.command.build_ext import build_ext
from distutils.command.install_lib import install_lib
from wheel.bdist_wheel import bdist_wheel
import platform
import os
import shutil
from pathlib import Path
from setuptools import Extension, setup
# import cmake
import subprocess
# import ninja
VERSION = '0.2.0'... | 3,634 | setup | py | en | python | code | {"qsc_code_num_words": 444, "qsc_code_num_chars": 3634.0, "qsc_code_mean_word_length": 5.32657658, "qsc_code_frac_words_unique": 0.31981982, "qsc_code_frac_chars_top_2grams": 0.02536998, "qsc_code_frac_chars_top_3grams": 0.02536998, "qsc_code_frac_chars_top_4grams": 0.02029598, "qsc_code_frac_chars_dupe_5grams": 0.1116... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/css/animate.min.css | @charset "UTF-8";/*!
Animate.css - http://daneden.me/animate
Licensed under the MIT license
Copyright (c) 2013 Daniel Eden
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, inc... | 47,161 | animate.min | css | en | css | data | {"qsc_code_num_words": 6251, "qsc_code_num_chars": 47161.0, "qsc_code_mean_word_length": 6.0806271, "qsc_code_frac_words_unique": 0.04175332, "qsc_code_frac_chars_top_2grams": 0.1495659, "qsc_code_frac_chars_top_3grams": 0.05724809, "qsc_code_frac_chars_top_4grams": 0.04235727, "qsc_code_frac_chars_dupe_5grams": 0.8486... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 1, "qsc_code... |
1c-syntax/ssl_3_1 | src/cf/Reports/УчастникиГруппПользователей/Ext/ManagerModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 2,530 | ManagerModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 191, "qsc_code_num_chars": 2530.0, "qsc_code_mean_word_length": 9.91099476, "qsc_code_frac_words_unique": 0.58115183, "qsc_code_frac_chars_top_2grams": 0.00316957, "qsc_code_frac_chars_top_3grams": 0.03328051, "qsc_code_frac_chars_top_4grams": 0.0306392, "qsc_code_frac_chars_dupe_5grams": 0.13629... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/УчастникиГруппПользователей/Templates/Макет.xml | <?xml version="1.0" encoding="UTF-8"?>
<MetaDataObject xmlns="http://v8.1c.ru/8.3/MDClasses" xmlns:app="http://v8.1c.ru/8.2/managed-application/core" xmlns:cfg="http://v8.1c.ru/8.1/data/enterprise/current-config" xmlns:cmi="http://v8.1c.ru/8.2/managed-application/cmi" xmlns:ent="http://v8.1c.ru/8.1/data/enterprise" xm... | 1,235 | Макет | xml | ru | xml | data | {"qsc_code_num_words": 223, "qsc_code_num_chars": 1235.0, "qsc_code_mean_word_length": 3.83408072, "qsc_code_frac_words_unique": 0.32735426, "qsc_code_frac_chars_top_2grams": 0.10526316, "qsc_code_frac_chars_top_3grams": 0.14035088, "qsc_code_frac_chars_top_4grams": 0.1754386, "qsc_code_frac_chars_dupe_5grams": 0.42923... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 1, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1c-syntax/ssl_3_1 | src/cf/Reports/УчастникиГруппПользователей/Templates/Макет/Ext/Template.xml | <?xml version="1.0" encoding="UTF-8"?>
<DataCompositionSchema xmlns="http://v8.1c.ru/8.1/data-composition-system/schema" xmlns:dcscom="http://v8.1c.ru/8.1/data-composition-system/common" xmlns:dcscor="http://v8.1c.ru/8.1/data-composition-system/core" xmlns:dcsset="http://v8.1c.ru/8.1/data-composition-system/settings" ... | 14,981 | Template | xml | ru | xml | data | {"qsc_code_num_words": 1553, "qsc_code_num_chars": 14981.0, "qsc_code_mean_word_length": 7.01545396, "qsc_code_frac_words_unique": 0.14681262, "qsc_code_frac_chars_top_2grams": 0.0372648, "qsc_code_frac_chars_top_3grams": 0.02863699, "qsc_code_frac_chars_top_4grams": 0.03588802, "qsc_code_frac_chars_dupe_5grams": 0.713... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/css/bootstrap.min.css | /*!
* Bootstrap v3.3.7 (http://getbootstrap.com)
* Copyright 2011-2016 Twitter, Inc.
* Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
*//*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */html{font-family:sans-serif;-webkit-text-size-adjust:100%;-ms-text-size-adju... | 121,155 | bootstrap.min | css | en | css | data | {"qsc_code_num_words": 19787, "qsc_code_num_chars": 121155.0, "qsc_code_mean_word_length": 4.81300854, "qsc_code_frac_words_unique": 0.05589528, "qsc_code_frac_chars_top_2grams": 0.03631018, "qsc_code_frac_chars_top_3grams": 0.01870111, "qsc_code_frac_chars_top_4grams": 0.00492466, "qsc_code_frac_chars_dupe_5grams": 0.... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1c-syntax/ssl_3_1 | src/cf/Reports/СостояниеУчетнойЗаписиDSS/Ext/ObjectModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 5,197 | ObjectModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 356, "qsc_code_num_chars": 5197.0, "qsc_code_mean_word_length": 11.35674157, "qsc_code_frac_words_unique": 0.53089888, "qsc_code_frac_chars_top_2grams": 0.01607717, "qsc_code_frac_chars_top_3grams": 0.00197873, "qsc_code_frac_chars_top_4grams": 0.0138511, "qsc_code_frac_chars_dupe_5grams": 0.0197... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/СостояниеУчетнойЗаписиDSS/Ext/ManagerModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 15,711 | ManagerModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 1142, "qsc_code_num_chars": 15711.0, "qsc_code_mean_word_length": 10.94658494, "qsc_code_frac_words_unique": 0.26269702, "qsc_code_frac_chars_top_2grams": 0.01535877, "qsc_code_frac_chars_top_3grams": 0.04031677, "qsc_code_frac_chars_top_4grams": 0.04895608, "qsc_code_frac_chars_dupe_5grams": 0.2... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/blockUI/jquery.blockUI.js | /*!
* jQuery blockUI plugin
* Version 2.70.0-2014.11.23
* Requires jQuery v1.7 or later
*
* Examples at: http://malsup.com/jquery/block/
* Copyright (c) 2007-2013 M. Alsup
* Dual licensed under the MIT and GPL licenses:
* http://www.opensource.org/licenses/mit-license.php
* http://www.gnu.org/licenses/gpl.htm... | 20,014 | jquery.blockUI | js | en | javascript | code | {"qsc_code_num_words": 2557, "qsc_code_num_chars": 20014.0, "qsc_code_mean_word_length": 4.87446226, "qsc_code_frac_words_unique": 0.22565506, "qsc_code_frac_chars_top_2grams": 0.0105905, "qsc_code_frac_chars_top_3grams": 0.01251605, "qsc_code_frac_chars_top_4grams": 0.00673941, "qsc_code_frac_chars_dupe_5grams": 0.155... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day58/layer_norm.cpp | #include <hip/hip_runtime.h>
__global__ void layer_norm_kernel(
float* output,
const float* input,
const float* gamma,
const float* beta,
int batch_size,
int hidden_size,
float epsilon)
{
extern __shared__ float shared[];
int batch_idx = blockIdx.x;
int tid = threadIdx.x;
i... | 2,163 | layer_norm | cpp | en | cpp | code | {"qsc_code_num_words": 282, "qsc_code_num_chars": 2163.0, "qsc_code_mean_word_length": 4.25886525, "qsc_code_frac_words_unique": 0.20921986, "qsc_code_frac_chars_top_2grams": 0.09991674, "qsc_code_frac_chars_top_3grams": 0.06411324, "qsc_code_frac_chars_top_4grams": 0.05995004, "qsc_code_frac_chars_dupe_5grams": 0.4412... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1x-technologies/1xgpt | magvit2/modules/losses/vqperceptual.py | """
Modified Open-MAGVIT2 code to use VQConfig.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from magvit2.config import VQConfig
from magvit2.modules.losses.lpips import LPIPS
from magvit2.modules.discriminator.model import NLayerDiscriminator, weights_init
class DummyLoss(nn.Module):
... | 12,805 | vqperceptual | py | en | python | code | {"qsc_code_num_words": 1520, "qsc_code_num_chars": 12805.0, "qsc_code_mean_word_length": 4.79144737, "qsc_code_frac_words_unique": 0.12828947, "qsc_code_frac_chars_top_2grams": 0.05492242, "qsc_code_frac_chars_top_3grams": 0.045311, "qsc_code_frac_chars_top_4grams": 0.02471509, "qsc_code_frac_chars_dupe_5grams": 0.4701... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day10/FlashAttention.cu | #include <cuda_runtime.h>
#include <iostream>
// #include "ATen/ATen.h"
// #include <torch/types.h>
template <typename T>
__global__ void flashKernel(const T *Q,
const T *K,
const T *V,
T *O,
T *m,
... | 10,398 | FlashAttention | cu | en | cuda | code | {"qsc_code_num_words": 1175, "qsc_code_num_chars": 10398.0, "qsc_code_mean_word_length": 4.00595745, "qsc_code_frac_words_unique": 0.14723404, "qsc_code_frac_chars_top_2grams": 0.06755895, "qsc_code_frac_chars_top_3grams": 0.05374973, "qsc_code_frac_chars_top_4grams": 0.06798385, "qsc_code_frac_chars_dupe_5grams": 0.48... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day84/kernel.py | import triton
import triton.language as tl
import torch
@triton.jit
def fp8_gemm_kernel(
a_ptr, b_ptr, c_ptr,
M, N, K,
stride_am, stride_ak,
stride_bk, stride_bn,
stride_cm, stride_cn,
scale_a, scale_b, scale_c,
BLOCK_M: tl.constexpr, BLOCK_N: tl.constexpr, BLOCK_K: tl.constexpr
):
pid_... | 2,549 | kernel | py | en | python | code | {"qsc_code_num_words": 422, "qsc_code_num_chars": 2549.0, "qsc_code_mean_word_length": 3.14454976, "qsc_code_frac_words_unique": 0.20616114, "qsc_code_frac_chars_top_2grams": 0.03617182, "qsc_code_frac_chars_top_3grams": 0.05275057, "qsc_code_frac_chars_top_4grams": 0.03617182, "qsc_code_frac_chars_dupe_5grams": 0.1311... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day30/kernelHisto.cu | #include <cuda_runtime.h>
#include <stdio.h>
#define BLOCK_SIZE 16 // 16x16 thread block
#define HIST_SIZE 256 // Grayscale histogram bins
__global__ void histogram_equalization(unsigned char *d_img, unsigned char *d_out, int width, int height) {
__shared__ unsigned int hist_shared[HIST_SIZE]; // Shared memory... | 1,797 | kernelHisto | cu | en | cuda | code | {"qsc_code_num_words": 235, "qsc_code_num_chars": 1797.0, "qsc_code_mean_word_length": 4.2212766, "qsc_code_frac_words_unique": 0.28510638, "qsc_code_frac_chars_top_2grams": 0.06451613, "qsc_code_frac_chars_top_3grams": 0.02116935, "qsc_code_frac_chars_top_4grams": 0.02419355, "qsc_code_frac_chars_dupe_5grams": 0.16129... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day46/flash_attention.py | import torch
import triton
import triton.language as tl
@triton.jit
def _attn_fwd_inner(
O_block,
l_i,
m_i,
Q_block,
K_block_ptr,
V_block_ptr,
block_index_q,
softmax_scale,
BLOCK_SIZE_Q: tl.constexpr,
BLOCK_SIZE_KV: tl.constexpr,
STAGE: tl.constexpr,
offs_q: tl.constex... | 24,586 | flash_attention | py | en | python | code | {"qsc_code_num_words": 3847, "qsc_code_num_chars": 24586.0, "qsc_code_mean_word_length": 3.58929036, "qsc_code_frac_words_unique": 0.09747855, "qsc_code_frac_chars_top_2grams": 0.03041715, "qsc_code_frac_chars_top_3grams": 0.0202781, "qsc_code_frac_chars_top_4grams": 0.02216107, "qsc_code_frac_chars_dupe_5grams": 0.568... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1x-technologies/1xgpt | magvit2/modules/diffusionmodules/improved_model.py | import torch
import torch.nn as nn
from magvit2.config import VQConfig
def swish(x):
# swish
return x*torch.sigmoid(x)
class ResBlock(nn.Module):
def __init__(self,
in_filters,
out_filters,
use_conv_shortcut = False
) -> None:
... | 7,725 | improved_model | py | en | python | code | {"qsc_code_num_words": 1069, "qsc_code_num_chars": 7725.0, "qsc_code_mean_word_length": 3.8484565, "qsc_code_frac_words_unique": 0.14312442, "qsc_code_frac_chars_top_2grams": 0.03232863, "qsc_code_frac_chars_top_3grams": 0.04666991, "qsc_code_frac_chars_top_4grams": 0.03889159, "qsc_code_frac_chars_dupe_5grams": 0.4854... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/ДлительностьОтложенногоОбновления/Ext/ObjectModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 16,693 | ObjectModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 1181, "qsc_code_num_chars": 16693.0, "qsc_code_mean_word_length": 11.21083827, "qsc_code_frac_words_unique": 0.26756986, "qsc_code_frac_chars_top_2grams": 0.00883686, "qsc_code_frac_chars_top_3grams": 0.01450151, "qsc_code_frac_chars_top_4grams": 0.00845921, "qsc_code_frac_chars_dupe_5grams": 0.1... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | core_compact.cu | #include "core.h"
#include <algorithm>
#include <assert.h>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define G 1024
#define WL 512
#define B 256
#define W 32
#define H 16
__forceinline__ __device__ static float logaddexpf(float a, float b) {
float co... | 15,512 | core_compact | cu | en | cuda | code | {"qsc_code_num_words": 2068, "qsc_code_num_chars": 15512.0, "qsc_code_mean_word_length": 3.59719536, "qsc_code_frac_words_unique": 0.094294, "qsc_code_frac_chars_top_2grams": 0.15230542, "qsc_code_frac_chars_top_3grams": 0.06022315, "qsc_code_frac_chars_top_4grams": 0.01693776, "qsc_code_frac_chars_dupe_5grams": 0.6625... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | core.cu | #include "core.h"
#include <stdio.h>
#include <assert.h>
#include <algorithm>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define W 32
#define G 1024
#define B 256
__forceinline__ __device__ static int idx2(int n, int u, int U1) {
return n * U1 + u;
}
... | 11,104 | core | cu | en | cuda | code | {"qsc_code_num_words": 1704, "qsc_code_num_chars": 11104.0, "qsc_code_mean_word_length": 3.26115023, "qsc_code_frac_words_unique": 0.09037559, "qsc_code_frac_chars_top_2grams": 0.02303401, "qsc_code_frac_chars_top_3grams": 0.01133705, "qsc_code_frac_chars_top_4grams": 0.01583588, "qsc_code_frac_chars_dupe_5grams": 0.74... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/ИзменениеУчастниковГруппПользователей/Ext/ManagerModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 3,920 | ManagerModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 288, "qsc_code_num_chars": 3920.0, "qsc_code_mean_word_length": 10.63194444, "qsc_code_frac_words_unique": 0.43402778, "qsc_code_frac_chars_top_2grams": 0.01175702, "qsc_code_frac_chars_top_3grams": 0.03527106, "qsc_code_frac_chars_top_4grams": 0.03135206, "qsc_code_frac_chars_dupe_5grams": 0.382... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/bootstrap-select/bootstrap-select.css | /*!
* Bootstrap-select v1.13.18 (https://developer.snapappointments.com/bootstrap-select)
*
* Copyright 2012-2020 SnapAppointments, LLC
* Licensed under MIT (https://github.com/snapappointments/bootstrap-select/blob/master/LICENSE)
*/
@-webkit-keyframes bs-notify-fadeOut {
0% {
opacity: 0.9;
}
100% {
... | 12,885 | bootstrap-select | css | en | css | data | {"qsc_code_num_words": 1670, "qsc_code_num_chars": 12885.0, "qsc_code_mean_word_length": 5.46467066, "qsc_code_frac_words_unique": 0.13113772, "qsc_code_frac_chars_top_2grams": 0.19395135, "qsc_code_frac_chars_top_3grams": 0.13609467, "qsc_code_frac_chars_top_4grams": 0.12710936, "qsc_code_frac_chars_dupe_5grams": 0.60... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1ytic/pytorch-edit-distance | torch_edit_distance/test.py | import torch
import unittest
from numpy.testing import assert_array_almost_equal
from torch_edit_distance_cuda import *
class EditDistanceTest(unittest.TestCase):
blank = torch.tensor([0], dtype=torch.int).cuda()
separator = torch.tensor([1], dtype=torch.int).cuda()
def test_repetitions(self):
... | 2,985 | test | py | en | python | code | {"qsc_code_num_words": 503, "qsc_code_num_chars": 2985.0, "qsc_code_mean_word_length": 3.02982107, "qsc_code_frac_words_unique": 0.11729622, "qsc_code_frac_chars_top_2grams": 0.17322835, "qsc_code_frac_chars_top_3grams": 0.17913386, "qsc_code_frac_chars_top_4grams": 0.16732283, "qsc_code_frac_chars_dupe_5grams": 0.6732... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 1, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day17/cublas3.cu | #include <stdio.h>
#include <cublas_v2.h>
#include <cuda_runtime.h>
#define n 10
int main()
{
cudaError_t cudaStat;
cublasStatus_t stat;
cublasHandle_t handle;
int j;
float *x, *y;
x = (float *)malloc(sizeof(float) * n);
y = (float *)malloc(sizeof(float) * n);
for (j = 0; j < n; ++j)
... | 1,149 | cublas3 | cu | en | cuda | code | {"qsc_code_num_words": 168, "qsc_code_num_chars": 1149.0, "qsc_code_mean_word_length": 3.4047619, "qsc_code_frac_words_unique": 0.29166667, "qsc_code_frac_chars_top_2grams": 0.11538462, "qsc_code_frac_chars_top_3grams": 0.08391608, "qsc_code_frac_chars_top_4grams": 0.03146853, "qsc_code_frac_chars_dupe_5grams": 0.25874... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day98/kernel.cpp | #include <cuda_runtime.h>
#include <device_launch_parameters.h>
#include <stdio.h>
// Constants for MoE configuration
#define NUM_EXPERTS 8
#define EXPERT_HIDDEN_SIZE 256
#define INPUT_SIZE 1024
#define OUTPUT_SIZE 512
#define TOP_K 2 // Number of experts to route to per token
// Error checking macro
#define CHECK_C... | 5,764 | kernel | cpp | en | cpp | code | {"qsc_code_num_words": 654, "qsc_code_num_chars": 5764.0, "qsc_code_mean_word_length": 4.79051988, "qsc_code_frac_words_unique": 0.28746177, "qsc_code_frac_chars_top_2grams": 0.0242579, "qsc_code_frac_chars_top_3grams": 0.01915097, "qsc_code_frac_chars_top_4grams": 0.01532078, "qsc_code_frac_chars_dupe_5grams": 0.09990... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day35/layernorm.cpp | #include <hip/hip_runtime.h>
#include <cstdio>
#include <cstdlib>
#include <cmath>
#define HIP_CALL(call) \
{ \
hipError_t err = call; ... | 8,236 | layernorm | cpp | en | cpp | code | {"qsc_code_num_words": 1028, "qsc_code_num_chars": 8236.0, "qsc_code_mean_word_length": 3.74027237, "qsc_code_frac_words_unique": 0.09338521, "qsc_code_frac_chars_top_2grams": 0.04551365, "qsc_code_frac_chars_top_3grams": 0.05617685, "qsc_code_frac_chars_top_4grams": 0.05149545, "qsc_code_frac_chars_dupe_5grams": 0.517... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1xyz/coolbeans | README.md | [](https://github.com/1xyz/coolbeans/actions?query=workflow%3ABuild)
[](https://github.com/1xyz/coolbeans/actions?query=workflow%3ARelease)
[![Docker](https://img.shields.io/dock... | 4,027 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.19188596, "qsc_doc_num_sentences": 77.0, "qsc_doc_num_words": 569, "qsc_doc_num_chars": 4027.0, "qsc_doc_num_lines": 79.0, "qsc_doc_mean_word_length": 5.35149385, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmor... | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_... |
1c-syntax/ssl_3_1 | src/cf/Reports/АнализПравДоступа/Templates/Макет/Ext/Template.xml | <?xml version="1.0" encoding="UTF-8"?>
<DataCompositionSchema xmlns="http://v8.1c.ru/8.1/data-composition-system/schema" xmlns:dcscom="http://v8.1c.ru/8.1/data-composition-system/common" xmlns:dcscor="http://v8.1c.ru/8.1/data-composition-system/core" xmlns:dcsset="http://v8.1c.ru/8.1/data-composition-system/settings" ... | 438,600 | Template | xml | ru | xml | data | {"qsc_code_num_words": 45889, "qsc_code_num_chars": 438600.0, "qsc_code_mean_word_length": 6.5449672, "qsc_code_frac_words_unique": 0.01497091, "qsc_code_frac_chars_top_2grams": 0.057894, "qsc_code_frac_chars_top_3grams": 0.05305951, "qsc_code_frac_chars_top_4grams": 0.06916782, "qsc_code_frac_chars_dupe_5grams": 0.957... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 1, "qsc_code... |
1y0n/AV_Evasion_Tool | 掩日2.0/AboutBox1.Designer.cs | namespace 掩日2._0
{
partial class AboutBox1
{
/// <summary>
/// 必需的设计器变量。
/// </summary>
private System.ComponentModel.IContainer components = null;
/// <summary>
/// 清理所有正在使用的资源。
/// </summary>
protected override void Dispose(bool disposing)
... | 10,686 | AboutBox1.Designer | cs | zh | csharp | code | {"qsc_code_num_words": 1038, "qsc_code_num_chars": 10686.0, "qsc_code_mean_word_length": 6.59248555, "qsc_code_frac_words_unique": 0.1734104, "qsc_code_frac_chars_top_2grams": 0.11018559, "qsc_code_frac_chars_top_3grams": 0.15256466, "qsc_code_frac_chars_top_4grams": 0.07978957, "qsc_code_frac_chars_dupe_5grams": 0.422... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/templates/demo/table/params.html | <!DOCTYPE html>
<html lang="zh" xmlns:th="http://www.thymeleaf.org" xmlns:shiro="http://www.pollix.at/thymeleaf/shiro">
<head>
<th:block th:include="include :: header('自定义查询参数')" />
</head>
<body class="gray-bg">
<div class="container-div">
<div class="row">
<div class="col-sm-12 select-table table-striped">... | 4,191 | params | html | en | html | code | {"qsc_code_num_words": 378, "qsc_code_num_chars": 4191.0, "qsc_code_mean_word_length": 4.88888889, "qsc_code_frac_words_unique": 0.30687831, "qsc_code_frac_chars_top_2grams": 0.02597403, "qsc_code_frac_chars_top_3grams": 0.04329004, "qsc_code_frac_chars_top_4grams": 0.06060606, "qsc_code_frac_chars_dupe_5grams": 0.6704... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 1, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1x-technologies/halodi-unity-package-registry-manager | Editor/Halodi/PackageRegistry/NPM/WebExceptionParser.cs | using System.Net;
namespace Halodi.PackageRegistry.NPM
{
public class WebExceptionParser
{
public static string ParseWebException(WebException e)
{
if (e.Status == WebExceptionStatus.ProtocolError)
{
HttpWebResponse response = (HttpWebResponse)e.Response;... | 1,162 | WebExceptionParser | cs | en | csharp | code | {"qsc_code_num_words": 74, "qsc_code_num_chars": 1162.0, "qsc_code_mean_word_length": 7.32432432, "qsc_code_frac_words_unique": 0.62162162, "qsc_code_frac_chars_top_2grams": 0.13284133, "qsc_code_frac_chars_top_3grams": 0.13284133, "qsc_code_frac_chars_top_4grams": 0.0, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_code... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1xyz/pryrite | executors/read_writer_proxy.go | package executor
import (
"io"
"regexp"
"sync"
"time"
"github.com/1xyz/pryrite/tools"
)
type readWriterProxy struct {
name string
markerRE *regexp.Regexp
markerFound func(string)
writer io.WriteCloser
wlock sync.Mutex
lastWrite time.Time
}
func (proxy *readWriterProxy) Monitor(output io.Reader) {
... | 2,854 | read_writer_proxy | go | en | go | code | {"qsc_code_num_words": 392, "qsc_code_num_chars": 2854.0, "qsc_code_mean_word_length": 4.80867347, "qsc_code_frac_words_unique": 0.33163265, "qsc_code_frac_chars_top_2grams": 0.03713528, "qsc_code_frac_chars_top_3grams": 0.05092838, "qsc_code_frac_chars_top_4grams": 0.02068966, "qsc_code_frac_chars_dupe_5grams": 0.1156... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1xyz/coolbeans | Contributing.md | Contributing
============
Coolbeans is currently at `alpha` release quality. It is all about improving the quality by adoption and testing.
By participating in this project you agree to abide by the [code of conduct](https://www.contributor-covenant.org/version/2/0/code_of_conduct/).
- [Building coolbeans](#buildin... | 3,222 | Contributing | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.18461538, "qsc_doc_num_sentences": 41.0, "qsc_doc_num_words": 469, "qsc_doc_num_chars": 3222.0, "qsc_doc_num_lines": 115.0, "qsc_doc_mean_word_length": 4.95095949, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmo... | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_... |
1c-syntax/ssl_3_1 | src/cf/Reports/АнализПравДоступа/Forms/ВыборСтрокиРегистра/Ext/Form.xml | <?xml version="1.0" encoding="UTF-8"?>
<Form xmlns="http://v8.1c.ru/8.3/xcf/logform" xmlns:app="http://v8.1c.ru/8.2/managed-application/core" xmlns:cfg="http://v8.1c.ru/8.1/data/enterprise/current-config" xmlns:dcscor="http://v8.1c.ru/8.1/data-composition-system/core" xmlns:dcssch="http://v8.1c.ru/8.1/data-composition... | 6,502 | Form | xml | ru | xml | data | {"qsc_code_num_words": 656, "qsc_code_num_chars": 6502.0, "qsc_code_mean_word_length": 7.23932927, "qsc_code_frac_words_unique": 0.34756098, "qsc_code_frac_chars_top_2grams": 0.01895136, "qsc_code_frac_chars_top_3grams": 0.02526848, "qsc_code_frac_chars_top_4grams": 0.0315856, "qsc_code_frac_chars_dupe_5grams": 0.20846... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1zb/deformable-convolution-pytorch | src/deform_conv_cuda_kernel.h | template <typename DType>
void deformable_im2col(cudaStream_t stream, const DType *data_im,
const DType *data_offset, const int channels,
const int height, const int width, const int ksize_h,
const int ksize_w, const int pad_h, const int pad_w,
... | 1,667 | deform_conv_cuda_kernel | h | en | c | code | {"qsc_code_num_words": 200, "qsc_code_num_chars": 1667.0, "qsc_code_mean_word_length": 4.445, "qsc_code_frac_words_unique": 0.14, "qsc_code_frac_chars_top_2grams": 0.32395951, "qsc_code_frac_chars_top_3grams": 0.12148481, "qsc_code_frac_chars_top_4grams": 0.08436445, "qsc_code_frac_chars_dupe_5grams": 0.97075366, "qsc_... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 1, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 1, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1zb/deformable-convolution-pytorch | src/deform_conv_cuda.h | int deform_conv_forward_cuda(THCudaTensor *input,
THCudaTensor *weight, /*THCudaTensor * bias, */
THCudaTensor *offset, THCudaTensor *output,
THCudaTensor *columns, THCudaTensor *ones, int kW,
int kH, int... | 1,136 | deform_conv_cuda | h | en | c | code | {"qsc_code_num_words": 118, "qsc_code_num_chars": 1136.0, "qsc_code_mean_word_length": 6.10169492, "qsc_code_frac_words_unique": 0.27118644, "qsc_code_frac_chars_top_2grams": 0.0375, "qsc_code_frac_chars_top_3grams": 0.05416667, "qsc_code_frac_chars_top_4grams": 0.1375, "qsc_code_frac_chars_dupe_5grams": 0.675, "qsc_co... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1zb/deformable-convolution-pytorch | modules/deform_conv.py | import math
import torch
import torch.nn as nn
from torch.nn.modules.module import Module
from torch.nn.modules.utils import _pair
from functions import conv_offset2d
class ConvOffset2d(Module):
def __init__(self,
in_channels,
out_channels,
kernel_size,
... | 1,345 | deform_conv | py | en | python | code | {"qsc_code_num_words": 154, "qsc_code_num_chars": 1345.0, "qsc_code_mean_word_length": 4.97402597, "qsc_code_frac_words_unique": 0.31168831, "qsc_code_frac_chars_top_2grams": 0.06527415, "qsc_code_frac_chars_top_3grams": 0.09921671, "qsc_code_frac_chars_top_4grams": 0.04699739, "qsc_code_frac_chars_dupe_5grams": 0.0809... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day03/anotherMatrix.cu | #include <iostream>
#include <cuda_runtime.h>
__device__ float randomFunction(float x, float y)
{
return x + y * 2;
}
__global__ void matrixFunction(const float *A, const float *B, float *C, const int size)
{
int i = blockIdx.x * blockDim.x + threadIdx.x;
int j = blockIdx.y * blockDim.y + threadIdx.y;
... | 1,441 | anotherMatrix | cu | en | cuda | code | {"qsc_code_num_words": 211, "qsc_code_num_chars": 1441.0, "qsc_code_mean_word_length": 3.63981043, "qsc_code_frac_words_unique": 0.26540284, "qsc_code_frac_chars_top_2grams": 0.08203125, "qsc_code_frac_chars_top_3grams": 0.03125, "qsc_code_frac_chars_top_4grams": 0.0390625, "qsc_code_frac_chars_dupe_5grams": 0.078125, ... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day03/addMatrix.cu | #include <iostream>
#include <cmath>
#include <cuda_runtime.h>
#include <chrono>
void printMatrix(const float *Matrix, const int size = 16) {
int rootSize = sqrt(size);
for (int i = 0; i < rootSize; i++) {
for (int j = 0; j < rootSize; j++) {
std::cout << Matrix[i * rootSize + j] << " ";
... | 3,181 | addMatrix | cu | en | cuda | code | {"qsc_code_num_words": 413, "qsc_code_num_chars": 3181.0, "qsc_code_mean_word_length": 4.67312349, "qsc_code_frac_words_unique": 0.20096852, "qsc_code_frac_chars_top_2grams": 0.05699482, "qsc_code_frac_chars_top_3grams": 0.05803109, "qsc_code_frac_chars_top_4grams": 0.03523316, "qsc_code_frac_chars_dupe_5grams": 0.3202... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/ИзменениеУчастниковГруппПользователей/Templates/Макет/Ext/Template.xml | <?xml version="1.0" encoding="UTF-8"?>
<DataCompositionSchema xmlns="http://v8.1c.ru/8.1/data-composition-system/schema" xmlns:dcscom="http://v8.1c.ru/8.1/data-composition-system/common" xmlns:dcscor="http://v8.1c.ru/8.1/data-composition-system/core" xmlns:dcsset="http://v8.1c.ru/8.1/data-composition-system/settings" ... | 54,422 | Template | xml | ru | xml | data | {"qsc_code_num_words": 6133, "qsc_code_num_chars": 54422.0, "qsc_code_mean_word_length": 5.89841839, "qsc_code_frac_words_unique": 0.04973096, "qsc_code_frac_chars_top_2grams": 0.05708362, "qsc_code_frac_chars_top_3grams": 0.05705598, "qsc_code_frac_chars_top_4grams": 0.06612301, "qsc_code_frac_chars_dupe_5grams": 0.91... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 1, "qsc_code... |
1zb/deformable-convolution-pytorch | functions/deform_conv.py | import torch
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from _ext import deform_conv
def conv_offset2d(input,
offset,
weight,
stride=1,
padding=0,
dilation=1,
deform_groups=1)... | 4,295 | deform_conv | py | en | python | code | {"qsc_code_num_words": 491, "qsc_code_num_chars": 4295.0, "qsc_code_mean_word_length": 4.86354379, "qsc_code_frac_words_unique": 0.18533605, "qsc_code_frac_chars_top_2grams": 0.02303183, "qsc_code_frac_chars_top_3grams": 0.03559464, "qsc_code_frac_chars_top_4grams": 0.05025126, "qsc_code_frac_chars_dupe_5grams": 0.4237... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day81/main.py | import triton
import triton.language as tl
@triton.jit
def fused_layernorm_ff_dropout_kernel(
x_ptr, out_ptr,
gamma_ptr, beta_ptr,
weight1_ptr, bias1_ptr,
weight2_ptr, bias2_ptr,
seed,
dropout_p: tl.constexpr,
N: tl.constexpr,
M: tl.constexpr,
BLOCK: tl.constexpr
):
row_idx = tl... | 2,118 | main | py | en | python | code | {"qsc_code_num_words": 334, "qsc_code_num_chars": 2118.0, "qsc_code_mean_word_length": 3.61377246, "qsc_code_frac_words_unique": 0.2245509, "qsc_code_frac_chars_top_2grams": 0.09942005, "qsc_code_frac_chars_top_3grams": 0.11184756, "qsc_code_frac_chars_top_4grams": 0.04971002, "qsc_code_frac_chars_dupe_5grams": 0.16321... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | pytorch_binding/benchmark.py | import argparse
import torch
import torch.nn.functional as F
from timeit import default_timer as timer
def run_benchmark(loss, E, N, T, U, V, random_length=False, device="cuda"):
torch.manual_seed(N)
elapsed_time = 0
for i in range(E):
xs = torch.randn((N, T, U, V), dtype=torch.float32, requ... | 3,287 | benchmark | py | en | python | code | {"qsc_code_num_words": 449, "qsc_code_num_chars": 3287.0, "qsc_code_mean_word_length": 3.80846325, "qsc_code_frac_words_unique": 0.28062361, "qsc_code_frac_chars_top_2grams": 0.02339181, "qsc_code_frac_chars_top_3grams": 0.03157895, "qsc_code_frac_chars_top_4grams": 0.03274854, "qsc_code_frac_chars_dupe_5grams": 0.2345... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rna | core.cu | #include "core.h"
#include <stdio.h>
#include <assert.h>
#include <algorithm>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define W 32
#define G 1024
#define B 256
__forceinline__ __device__ static int idx2(int n, int u, int U1) {
return n * U1 + u;
}
... | 10,911 | core | cu | en | cuda | code | {"qsc_code_num_words": 1706, "qsc_code_num_chars": 10911.0, "qsc_code_mean_word_length": 3.20750293, "qsc_code_frac_words_unique": 0.08616647, "qsc_code_frac_chars_top_2grams": 0.08040936, "qsc_code_frac_chars_top_3grams": 0.00712719, "qsc_code_frac_chars_top_4grams": 0.01315789, "qsc_code_frac_chars_dupe_5grams": 0.75... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1y33/100Days | day14/conv.cu | #include <cuda_runtime.h>
#include <iostream>
#define BLOCK_SIZE 32
#define FILTER_SIZE 5
__global__ void convolutionkernel(float *input, float *output, float *kernel,
int kernel_size, int w, int h)
{
int tx = threadIdx.x, ty = threadIdx.y;
int bx = blockIdx.x, by = blockIdx.... | 3,258 | conv | cu | en | cuda | code | {"qsc_code_num_words": 417, "qsc_code_num_chars": 3258.0, "qsc_code_mean_word_length": 4.22541966, "qsc_code_frac_words_unique": 0.20623501, "qsc_code_frac_chars_top_2grams": 0.11918275, "qsc_code_frac_chars_top_3grams": 0.0476731, "qsc_code_frac_chars_top_4grams": 0.04540295, "qsc_code_frac_chars_dupe_5grams": 0.22360... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/СогласияНаОбработкуПерсональныхДанныхИстекающие/Templates/ОсновнаяСхемаКомпоновкиДанных.xml | <?xml version="1.0" encoding="UTF-8"?>
<MetaDataObject xmlns="http://v8.1c.ru/8.3/MDClasses" xmlns:app="http://v8.1c.ru/8.2/managed-application/core" xmlns:cfg="http://v8.1c.ru/8.1/data/enterprise/current-config" xmlns:cmi="http://v8.1c.ru/8.2/managed-application/cmi" xmlns:ent="http://v8.1c.ru/8.1/data/enterprise" xm... | 1,286 | ОсновнаяСхемаКомпоновкиДанных | xml | ru | xml | data | {"qsc_code_num_words": 226, "qsc_code_num_chars": 1286.0, "qsc_code_mean_word_length": 3.99557522, "qsc_code_frac_words_unique": 0.34070796, "qsc_code_frac_chars_top_2grams": 0.09966777, "qsc_code_frac_chars_top_3grams": 0.13289037, "qsc_code_frac_chars_top_4grams": 0.16611296, "qsc_code_frac_chars_dupe_5grams": 0.4064... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 1, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1y33/100Days | day66/kernel.cpp | #include <hip/hip_runtime.h>
#include <cmath>
#include <cstdio>
__device__ inline float gelu(float x) {
const float k0 = 0.7978845608f;
const float k1 = 0.044715f;
float t = tanhf(k0 * (x + k1 * x * x * x));
return 0.5f * x * (1.0f + t);
}
__device__ inline float gelu_grad(float x) {
const float k... | 4,299 | kernel | cpp | en | cpp | code | {"qsc_code_num_words": 571, "qsc_code_num_chars": 4299.0, "qsc_code_mean_word_length": 3.93870403, "qsc_code_frac_words_unique": 0.117338, "qsc_code_frac_chars_top_2grams": 0.1680747, "qsc_code_frac_chars_top_3grams": 0.06669631, "qsc_code_frac_chars_top_4grams": 0.04979991, "qsc_code_frac_chars_dupe_5grams": 0.6785237... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day26/gradientdescent.cu | #include <cuda_runtime.h>
#include <iostream>
// CUDA kernel: performs one gradient descent update for a linear regression weight vector.
// It uses the previous weight vector w_old (read-only) to compute predictions and then writes
// the updated weights to w. Each thread computes the gradient and update for one weig... | 3,161 | gradientdescent | cu | en | cuda | code | {"qsc_code_num_words": 421, "qsc_code_num_chars": 3161.0, "qsc_code_mean_word_length": 3.72209026, "qsc_code_frac_words_unique": 0.25653207, "qsc_code_frac_chars_top_2grams": 0.01531589, "qsc_code_frac_chars_top_3grams": 0.05360562, "qsc_code_frac_chars_top_4grams": 0.03318443, "qsc_code_frac_chars_dupe_5grams": 0.1793... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rna | pytorch_binding/binding.cpp | #include <tuple>
#include <string>
#include <THC/THC.h>
#include <torch/types.h>
#include <torch/extension.h>
#include "core.h"
#ifndef TORCH_CHECK
#define TORCH_CHECK AT_CHECK
#endif
#define CHECK_CONTIGUOUS(x) \
TORCH_CHECK((x).is_contiguous(), \... | 3,485 | binding | cpp | en | cpp | code | {"qsc_code_num_words": 465, "qsc_code_num_chars": 3485.0, "qsc_code_mean_word_length": 4.17634409, "qsc_code_frac_words_unique": 0.2172043, "qsc_code_frac_chars_top_2grams": 0.05664264, "qsc_code_frac_chars_top_3grams": 0.02265705, "qsc_code_frac_chars_top_4grams": 0.02471679, "qsc_code_frac_chars_dupe_5grams": 0.15036... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/СогласияНаОбработкуПерсональныхДанныхИстекающие/Ext/Help/ru.html | <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"><html><head><meta content="text/html;charset=utf-8" http-equiv="content-type"></meta><link rel="stylesheet" type="text/css" href="v8help://service_book/service_style"></link><meta name="GENERATOR" content="MSHTML 9.00.8112.16421"></meta></head><body>
<p>Пре... | 1,618 | ru | html | ru | html | code | {"qsc_code_num_words": 219, "qsc_code_num_chars": 1618.0, "qsc_code_mean_word_length": 5.56164384, "qsc_code_frac_words_unique": 0.51141553, "qsc_code_frac_chars_top_2grams": 0.00656814, "qsc_code_frac_chars_top_3grams": 0.08538588, "qsc_code_frac_chars_top_4grams": 0.11165846, "qsc_code_frac_chars_dupe_5grams": 0.2036... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day19/cublasMM.cu | #include <iostream>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cassert>
#define CHECK_CUDA_CALL(x) \
if ((x) != cudaSuccess) \
{ ... | 3,794 | cublasMM | cu | en | cuda | code | {"qsc_code_num_words": 466, "qsc_code_num_chars": 3794.0, "qsc_code_mean_word_length": 3.89270386, "qsc_code_frac_words_unique": 0.19957082, "qsc_code_frac_chars_top_2grams": 0.07276736, "qsc_code_frac_chars_top_3grams": 0.07883131, "qsc_code_frac_chars_top_4grams": 0.04961411, "qsc_code_frac_chars_dupe_5grams": 0.3335... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | pytorch_binding/core_compact.cu | #include "core.h"
#include <algorithm>
#include <assert.h>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define G 1024
#define WL 512
#define B 256
#define W 32
#define H 16
__forceinline__ __device__ static float logaddexpf(float a, float b) {
float co... | 15,512 | core_compact | cu | en | cuda | code | {"qsc_code_num_words": 2068, "qsc_code_num_chars": 15512.0, "qsc_code_mean_word_length": 3.59719536, "qsc_code_frac_words_unique": 0.094294, "qsc_code_frac_chars_top_2grams": 0.15230542, "qsc_code_frac_chars_top_3grams": 0.06022315, "qsc_code_frac_chars_top_4grams": 0.01693776, "qsc_code_frac_chars_dupe_5grams": 0.6625... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/bootstrap-select/bootstrap-select.min.css | /*!
* Bootstrap-select v1.13.18 (https://developer.snapappointments.com/bootstrap-select)
*
* Copyright 2012-2020 SnapAppointments, LLC
* Licensed under MIT (https://github.com/snapappointments/bootstrap-select/blob/master/LICENSE)
*/@-webkit-keyframes bs-notify-fadeOut{0%{opacity:.9}100%{opacity:0}}@-o-keyframes ... | 11,179 | bootstrap-select.min | css | en | css | data | {"qsc_code_num_words": 1649, "qsc_code_num_chars": 11179.0, "qsc_code_mean_word_length": 5.50333535, "qsc_code_frac_words_unique": 0.13159491, "qsc_code_frac_chars_top_2grams": 0.19504132, "qsc_code_frac_chars_top_3grams": 0.1368595, "qsc_code_frac_chars_top_4grams": 0.12782369, "qsc_code_frac_chars_dupe_5grams": 0.607... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1c-syntax/ssl_3_1 | src/cf/Reports/СогласияНаОбработкуПерсональныхДанныхИстекающие/Ext/ManagerModule.bsl | ///////////////////////////////////////////////////////////////////////////////////////////////////////
// Copyright (c) 2024, ООО 1С-Софт
// Все права защищены. Эта программа и сопроводительные материалы предоставляются
// в соответствии с условиями лицензии Attribution 4.0 International (CC BY 4.0)
// Текст лицензи... | 1,443 | ManagerModule | bsl | ru | 1c enterprise | code | {"qsc_code_num_words": 112, "qsc_code_num_chars": 1443.0, "qsc_code_mean_word_length": 9.0, "qsc_code_frac_words_unique": 0.72321429, "qsc_code_frac_chars_top_2grams": 0.00595238, "qsc_code_frac_chars_top_3grams": 0.00793651, "qsc_code_frac_chars_top_4grams": 0.04365079, "qsc_code_frac_chars_dupe_5grams": 0.0, "qsc_cod... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day48/kernel.py | import torch
import triton
import triton.language as tl
@triton.jit
def gelu_kernel(
x_ptr,
output_ptr,
n_elements,
BLOCK_SIZE: tl.constexpr,
):
pid = tl.program_id(axis=0)
block_start = pid * BLOCK_SIZE
offsets = block_start + tl.arange(0, BLOCK_SIZE)
mask = offsets < n_elements
... | 1,264 | kernel | py | en | python | code | {"qsc_code_num_words": 181, "qsc_code_num_chars": 1264.0, "qsc_code_mean_word_length": 4.25966851, "qsc_code_frac_words_unique": 0.40883978, "qsc_code_frac_chars_top_2grams": 0.05836576, "qsc_code_frac_chars_top_3grams": 0.03631647, "qsc_code_frac_chars_top_4grams": 0.04669261, "qsc_code_frac_chars_dupe_5grams": 0.0, "... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rna | README.md | # Recurrent Neural Aligner
Recurrent Neural Aligner (RNA) is a restricted version of RNN-Transducer loss (RNN-T). It assumes that the length of input sequence is equal to or greater than the length of target sequence ([Sak, et al., 2017](https://www.isca-speech.org/archive/Interspeech_2017/pdfs/1705.PDF); [Dong, et al... | 1,448 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.29375, "qsc_doc_num_sentences": 25.0, "qsc_doc_num_words": 251, "qsc_doc_num_chars": 1448.0, "qsc_doc_num_lines": 31.0, "qsc_doc_mean_word_length": 4.39043825, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore":... | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_... |
1ytic/warp-rnnt | pytorch_binding/core.cu | #include "core.h"
#include <stdio.h>
#include <assert.h>
#include <algorithm>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define W 32
#define G 1024
#define B 256
__forceinline__ __device__ static int idx2(int n, int u, int U1) {
return n * U1 + u;
}
... | 11,104 | core | cu | en | cuda | code | {"qsc_code_num_words": 1704, "qsc_code_num_chars": 11104.0, "qsc_code_mean_word_length": 3.26115023, "qsc_code_frac_words_unique": 0.09037559, "qsc_code_frac_chars_top_2grams": 0.02303401, "qsc_code_frac_chars_top_3grams": 0.01133705, "qsc_code_frac_chars_top_4grams": 0.01583588, "qsc_code_frac_chars_dupe_5grams": 0.74... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1ytic/warp-rnnt | pytorch_binding/setup.py | import io
import os
import torch
from setuptools import setup, find_packages
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
def get_requirements():
req_file = os.path.join(os.path.dirname(__file__), "requirements.txt")
with io.open(req_file, "r", encoding="utf-8") as f:
return [l... | 2,286 | setup | py | en | python | code | {"qsc_code_num_words": 251, "qsc_code_num_chars": 2286.0, "qsc_code_mean_word_length": 5.60557769, "qsc_code_frac_words_unique": 0.47808765, "qsc_code_frac_chars_top_2grams": 0.06396588, "qsc_code_frac_chars_top_3grams": 0.10660981, "qsc_code_frac_chars_top_4grams": 0.1108742, "qsc_code_frac_chars_dupe_5grams": 0.08102... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | tensorflow_binding/warp_rnnt_tf/__init__.py | import imp
import tensorflow as tf
from tensorflow.python.framework import ops
from typing import Optional, AnyStr
lib_file = imp.find_module('kernels', __path__)[1]
_warp_transducer = tf.load_op_library(lib_file)
def gather_log_probs(log_probs, labels, blank=0):
""" Gather log_probs with the shape (N, T, U, V) ... | 5,691 | __init__ | py | en | python | code | {"qsc_code_num_words": 847, "qsc_code_num_chars": 5691.0, "qsc_code_mean_word_length": 3.96340024, "qsc_code_frac_words_unique": 0.21959858, "qsc_code_frac_chars_top_2grams": 0.01251117, "qsc_code_frac_chars_top_3grams": 0.01608579, "qsc_code_frac_chars_top_4grams": 0.00953232, "qsc_code_frac_chars_dupe_5grams": 0.3428... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day78/rmsnorm.py | import torch
import triton
import triton.language as tl
def next_power_of_2(n):
n -= 1
n |= n >> 1
n |= n >> 2
n |= n >> 4
n |= n >> 8
n |= n >> 16
n += 1
return n
@triton.jit
def _rms_norm_fwd_fused(
X_ptr,
Y_ptr,
W_ptr,
stride_x_row,
stride_y_row,
N,
eps,
... | 4,283 | rmsnorm | py | en | python | code | {"qsc_code_num_words": 669, "qsc_code_num_chars": 4283.0, "qsc_code_mean_word_length": 3.84753363, "qsc_code_frac_words_unique": 0.22421525, "qsc_code_frac_chars_top_2grams": 0.00621601, "qsc_code_frac_chars_top_3grams": 0.03108003, "qsc_code_frac_chars_top_4grams": 0.01398601, "qsc_code_frac_chars_dupe_5grams": 0.3453... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/АнализВерсийОбъектов/Templates/ОсновнаяСхемаКомпоновкиДанных.xml | <?xml version="1.0" encoding="UTF-8"?>
<MetaDataObject xmlns="http://v8.1c.ru/8.3/MDClasses" xmlns:app="http://v8.1c.ru/8.2/managed-application/core" xmlns:cfg="http://v8.1c.ru/8.1/data/enterprise/current-config" xmlns:cmi="http://v8.1c.ru/8.2/managed-application/cmi" xmlns:ent="http://v8.1c.ru/8.1/data/enterprise" xm... | 1,286 | ОсновнаяСхемаКомпоновкиДанных | xml | ru | xml | data | {"qsc_code_num_words": 226, "qsc_code_num_chars": 1286.0, "qsc_code_mean_word_length": 3.99557522, "qsc_code_frac_words_unique": 0.34070796, "qsc_code_frac_chars_top_2grams": 0.09966777, "qsc_code_frac_chars_top_3grams": 0.13289037, "qsc_code_frac_chars_top_4grams": 0.16611296, "qsc_code_frac_chars_dupe_5grams": 0.4064... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 1, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1y33/100Days | day100/delta.cu | #include <cuda.h>
#include <cuda_fp16.h>
using namespace nvcuda;
// Block layout: one block per (batch, head)
template<int D>
__global__ void delta_net_attention(
const half* __restrict__ K, // [B, S, D]
const half* __restrict__ V, // [B, S, D]
const half* __restrict__ Q, // [B, S, D]
half* __res... | 2,230 | delta | cu | en | cuda | code | {"qsc_code_num_words": 304, "qsc_code_num_chars": 2230.0, "qsc_code_mean_word_length": 3.25, "qsc_code_frac_words_unique": 0.25, "qsc_code_frac_chars_top_2grams": 0.048583, "qsc_code_frac_chars_top_3grams": 0.07591093, "qsc_code_frac_chars_top_4grams": 0.09109312, "qsc_code_frac_chars_dupe_5grams": 0.25303644, "qsc_cod... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/cropper/cropper.min.css | /*!
* Cropper.js v1.5.12
* https://fengyuanchen.github.io/cropperjs
*
* Copyright 2015-present Chen Fengyuan
* Released under the MIT license
*
* Date: 2021-06-12T08:00:11.623Z
*/.cropper-container{direction:ltr;font-size:0;line-height:0;position:relative;-ms-touch-action:none;touch-action:none;-webkit-user-sel... | 3,742 | cropper.min | css | en | css | data | {"qsc_code_num_words": 588, "qsc_code_num_chars": 3742.0, "qsc_code_mean_word_length": 5.05782313, "qsc_code_frac_words_unique": 0.24659864, "qsc_code_frac_chars_top_2grams": 0.06052455, "qsc_code_frac_chars_top_3grams": 0.06859449, "qsc_code_frac_chars_top_4grams": 0.03362475, "qsc_code_frac_chars_dupe_5grams": 0.1842... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1c-syntax/ssl_3_1 | src/cf/Reports/АнализВерсийОбъектов/Ext/Help/ru.html | <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"><html><head><meta content="text/html;charset=utf-8" http-equiv="content-type"></meta><link rel="stylesheet" type="text/css" href="v8help://service_book/service_style"></link><meta name="GENERATOR" content="MSHTML 9.00.8112.16421"></meta></head><body>
<p>Пре... | 1,702 | ru | html | ru | html | code | {"qsc_code_num_words": 242, "qsc_code_num_chars": 1702.0, "qsc_code_mean_word_length": 5.28512397, "qsc_code_frac_words_unique": 0.47107438, "qsc_code_frac_chars_top_2grams": 0.07662236, "qsc_code_frac_chars_top_3grams": 0.05942142, "qsc_code_frac_chars_top_4grams": 0.06333073, "qsc_code_frac_chars_dupe_5grams": 0.2173... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day65/quant.cpp | #include <hip/hip_runtime.h>
#include <iostream>
#include <cmath>
#include <cfloat>
#include <cstdlib>
#define QMIN -128
#define QMAX 127
__global__ void reduceMinMaxKernel(const float* __restrict__ input,
float* __restrict__ partialMins,
float* __... | 6,241 | quant | cpp | en | cpp | code | {"qsc_code_num_words": 641, "qsc_code_num_chars": 6241.0, "qsc_code_mean_word_length": 5.29953198, "qsc_code_frac_words_unique": 0.17784711, "qsc_code_frac_chars_top_2grams": 0.03238151, "qsc_code_frac_chars_top_3grams": 0.02119517, "qsc_code_frac_chars_top_4grams": 0.01354136, "qsc_code_frac_chars_dupe_5grams": 0.0453... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day36/random.cpp | #include <hip/hip_runtime.h>
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#define BLOCK_SIZE 256
__global__ void reductionKernelOptimized(const float *g_in, float *g_out, int n) {
extern __shared__ float sdata[];
unsigned int tid = threadIdx.x;
unsigned int idx = blockIdx.x * (BLOCK_SIZE * 2)... | 2,082 | random | cpp | en | cpp | code | {"qsc_code_num_words": 280, "qsc_code_num_chars": 2082.0, "qsc_code_mean_word_length": 4.125, "qsc_code_frac_words_unique": 0.25714286, "qsc_code_frac_chars_top_2grams": 0.08311688, "qsc_code_frac_chars_top_3grams": 0.06753247, "qsc_code_frac_chars_top_4grams": 0.08311688, "qsc_code_frac_chars_dupe_5grams": 0.07792208,... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | tensorflow_binding/binding.cpp | #define EIGEN_USE_GPU
#include <cuda.h>
#include <iostream>
#include <algorithm>
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/bounds_check.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "core.h"
static const char* transducerGetStatusString(rnntStatus_t sta... | 7,182 | binding | cpp | en | cpp | code | {"qsc_code_num_words": 853, "qsc_code_num_chars": 7182.0, "qsc_code_mean_word_length": 4.99531067, "qsc_code_frac_words_unique": 0.1887456, "qsc_code_frac_chars_top_2grams": 0.04693734, "qsc_code_frac_chars_top_3grams": 0.03097864, "qsc_code_frac_chars_top_4grams": 0.0387233, "qsc_code_frac_chars_dupe_5grams": 0.345458... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1zb/deformable-convolution-pytorch | src/deform_conv_cuda_kernel.cu | #include "deform_conv_cuda_kernel.h"
#include <cstdio>
#define CUDA_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < (n); \
i += blockDim.x * gridDim.x)
const int CUDA_NUM_THREADS = 1024;
inline int GET_BLOCKS(const ... | 18,705 | deform_conv_cuda_kernel | cu | en | cuda | code | {"qsc_code_num_words": 2753, "qsc_code_num_chars": 18705.0, "qsc_code_mean_word_length": 3.80021794, "qsc_code_frac_words_unique": 0.05448602, "qsc_code_frac_chars_top_2grams": 0.11852418, "qsc_code_frac_chars_top_3grams": 0.03699102, "qsc_code_frac_chars_top_4grams": 0.03345441, "qsc_code_frac_chars_dupe_5grams": 0.81... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 1, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1ytic/warp-rnnt | tensorflow_binding/core_gather.cu | #include "core.h"
#include <stdio.h>
#include <assert.h>
#include <algorithm>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define W 32
#define G 1024
#define B 256
__forceinline__ __device__ static int idx3(int n, int t, int u, int T, int U) {
return n... | 10,472 | core_gather | cu | en | cuda | code | {"qsc_code_num_words": 1585, "qsc_code_num_chars": 10472.0, "qsc_code_mean_word_length": 3.24605678, "qsc_code_frac_words_unique": 0.09589905, "qsc_code_frac_chars_top_2grams": 0.02487852, "qsc_code_frac_chars_top_3grams": 0.00816327, "qsc_code_frac_chars_top_4grams": 0.01710398, "qsc_code_frac_chars_dupe_5grams": 0.72... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1y33/100Days | nvidiadocs/addition.cu | #include <iostream>
#include <cuda_runtime.h>
__global__ void addition(float* A , float* B, float*C){
int idx = threadIdx.x;
C[idx] = A[idx] + B[idx];
}
int main(){
int N = 10;
addition<<<1,N>>>(A,B,C); // simple addition kernle that will launch N threads
}
//////////////////////////////////////
// ... | 1,329 | addition | cu | en | cuda | code | {"qsc_code_num_words": 199, "qsc_code_num_chars": 1329.0, "qsc_code_mean_word_length": 3.53768844, "qsc_code_frac_words_unique": 0.27638191, "qsc_code_frac_chars_top_2grams": 0.02272727, "qsc_code_frac_chars_top_3grams": 0.03977273, "qsc_code_frac_chars_top_4grams": 0.01704545, "qsc_code_frac_chars_dupe_5grams": 0.3096... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1y33/100Days | day03/addMatrix.py | import triton
import torch
import triton.language as tl
@triton.jit
def addMatrix(Matrix_A,Matrix_B,Matrix_C,sizeX,sizeY,BLOCK_SIZE:tl.constexpr):
pid_x = tl.program_id(0) # we have the rows
pid_y = tl.program_id(1) # we have the collumns
row_start = pid_x*BLOCK_SIZE
col_start = pid_y*BLOCK_SIZE... | 1,875 | addMatrix | py | en | python | code | {"qsc_code_num_words": 287, "qsc_code_num_chars": 1875.0, "qsc_code_mean_word_length": 4.2195122, "qsc_code_frac_words_unique": 0.23344948, "qsc_code_frac_chars_top_2grams": 0.06358382, "qsc_code_frac_chars_top_3grams": 0.03633361, "qsc_code_frac_chars_top_4grams": 0.04954583, "qsc_code_frac_chars_dupe_5grams": 0.23451... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1ytic/warp-rnnt | tensorflow_binding/README.md | # TensorFlow binding for warp-rnnt
This package provides TensorFlow kernels that wrap the warp-rnnt library.
## Installation
Compile CUDA files:
```bash
git clone https://github.com/1ytic/warp-rnnt
cd warp-rnnt/tensorflow_binding
mkdir build && cd build && cmake .. && make
```
Install the package into current Pyt... | 2,157 | README | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.1748072, "qsc_doc_num_sentences": 20.0, "qsc_doc_num_words": 288, "qsc_doc_num_chars": 2157.0, "qsc_doc_num_lines": 69.0, "qsc_doc_mean_word_length": 4.98958333, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmore... | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_... |
1ytic/warp-rnnt | tensorflow_binding/core.cu | #include "core.h"
#include <stdio.h>
#include <assert.h>
#include <algorithm>
#include <cuda_runtime_api.h>
#include <device_atomic_functions.h>
#include <device_launch_parameters.h>
#define W 32
#define G 1024
#define B 256
__forceinline__ __device__ static int idx2(int n, int u, int U1) {
return n * U1 + u;
}
... | 11,104 | core | cu | en | cuda | code | {"qsc_code_num_words": 1704, "qsc_code_num_chars": 11104.0, "qsc_code_mean_word_length": 3.26115023, "qsc_code_frac_words_unique": 0.09037559, "qsc_code_frac_chars_top_2grams": 0.02303401, "qsc_code_frac_chars_top_3grams": 0.01133705, "qsc_code_frac_chars_top_4grams": 0.01583588, "qsc_code_frac_chars_dupe_5grams": 0.74... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 1, "qsc... |
1ytic/warp-rnnt | tensorflow_binding/setup.py | import os
import setuptools
import tensorflow as tf
from setuptools.command.build_ext import build_ext
CUDA_HOME = os.environ.get("CUDA_HOME", "/usr/local/cuda")
include_dirs = [tf.sysconfig.get_include(), os.path.join(CUDA_HOME, "include")]
core_dir = os.path.realpath("./build")
extra_link_args = ["-L" + tf.sysco... | 1,178 | setup | py | en | python | code | {"qsc_code_num_words": 137, "qsc_code_num_chars": 1178.0, "qsc_code_mean_word_length": 4.8540146, "qsc_code_frac_words_unique": 0.47445255, "qsc_code_frac_chars_top_2grams": 0.06015038, "qsc_code_frac_chars_top_3grams": 0.05864662, "qsc_code_frac_chars_top_4grams": 0.05413534, "qsc_code_frac_chars_dupe_5grams": 0.0, "q... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/datapicker/bootstrap-datetimepicker.min.js | (function(factory){if(typeof define==="function"&&define.amd){define(["jquery"],factory)}else{if(typeof exports==="object"){factory(require("jquery"))}else{factory(jQuery)}}}(function($,undefined){if(!("indexOf" in Array.prototype)){Array.prototype.indexOf=function(find,i){if(i===undefined){i=0}if(i<0){i+=this.length}i... | 46,208 | bootstrap-datetimepicker.min | js | en | javascript | code | {"qsc_code_num_words": 6514, "qsc_code_num_chars": 46208.0, "qsc_code_mean_word_length": 5.3297513, "qsc_code_frac_words_unique": 0.09226282, "qsc_code_frac_chars_top_2grams": 0.02851547, "qsc_code_frac_chars_top_3grams": 0.01987442, "qsc_code_frac_chars_top_4grams": 0.0098508, "qsc_code_frac_chars_dupe_5grams": 0.3990... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/datapicker/bootstrap-datetimepicker.css | /*!
* Datetimepicker for Bootstrap
*
* Copyright 2012 Stefan Petre
* Improvements by Andrew Rowls
* Licensed under the Apache License v2.0
* http://www.apache.org/licenses/LICENSE-2.0
*
*/
.datetimepicker {
padding: 4px;
margin-top: 1px;
-webkit-border-radius: 4px;
-moz-border-radius: 4px;
border-radius: 4... | 12,339 | bootstrap-datetimepicker | css | en | css | data | {"qsc_code_num_words": 1634, "qsc_code_num_chars": 12339.0, "qsc_code_mean_word_length": 5.74541004, "qsc_code_frac_words_unique": 0.09424725, "qsc_code_frac_chars_top_2grams": 0.0842565, "qsc_code_frac_chars_top_3grams": 0.10737111, "qsc_code_frac_chars_top_4grams": 0.26704303, "qsc_code_frac_chars_dupe_5grams": 0.792... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 1, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1c-syntax/ssl_3_1 | src/cf/Reports/МестаИспользованияСсылок/Templates/ОсновнаяСхемаКомпоновкиДанных.xml | <?xml version="1.0" encoding="UTF-8"?>
<MetaDataObject xmlns="http://v8.1c.ru/8.3/MDClasses" xmlns:app="http://v8.1c.ru/8.2/managed-application/core" xmlns:cfg="http://v8.1c.ru/8.1/data/enterprise/current-config" xmlns:cmi="http://v8.1c.ru/8.2/managed-application/cmi" xmlns:ent="http://v8.1c.ru/8.1/data/enterprise" xm... | 1,286 | ОсновнаяСхемаКомпоновкиДанных | xml | ru | xml | data | {"qsc_code_num_words": 226, "qsc_code_num_chars": 1286.0, "qsc_code_mean_word_length": 3.99557522, "qsc_code_frac_words_unique": 0.34070796, "qsc_code_frac_chars_top_2grams": 0.09966777, "qsc_code_frac_chars_top_3grams": 0.13289037, "qsc_code_frac_chars_top_4grams": 0.16611296, "qsc_code_frac_chars_dupe_5grams": 0.4064... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 1, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1y33/100Days | ReadMe.md | # Project Progress and Tasks
Bro in CUDA 📗 : https://github.com/a-hamdi/cuda
Mentor 🚀 : https://github.com/hkproj | https://github.com/hkproj/100-days-of-gpu
### Mandatory and Optional Tasks
| Day | Task Description |
|-------|---... | 6,658 | ReadMe | md | en | markdown | text | {"qsc_doc_frac_chars_curly_bracket": 0.0, "qsc_doc_frac_words_redpajama_stop": 0.10280374, "qsc_doc_num_sentences": 134.0, "qsc_doc_num_words": 733, "qsc_doc_num_chars": 6658.0, "qsc_doc_num_lines": 46.0, "qsc_doc_mean_word_length": 5.45839018, "qsc_doc_frac_words_full_bracket": 0.0, "qsc_doc_frac_lines_end_with_readmo... | 1 | {"qsc_doc_frac_chars_replacement_symbols": 0, "qsc_doc_entropy_unigram": 0, "qsc_doc_frac_chars_top_2grams": 0, "qsc_doc_frac_chars_top_3grams": 0, "qsc_doc_frac_chars_top_4grams": 0, "qsc_doc_frac_chars_dupe_5grams": 0, "qsc_doc_frac_chars_dupe_6grams": 0, "qsc_doc_frac_chars_dupe_7grams": 0, "qsc_doc_frac_chars_dupe_... |
1c-syntax/ssl_3_1 | src/cf/Reports/МестаИспользованияСсылок/Ext/Help/ru.html | <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN"><html><head><meta content="text/html;charset=utf-8" http-equiv="content-type"></meta><link rel="stylesheet" type="text/css" href="v8help://service_book/service_style"></link><meta name="GENERATOR" content="MSHTML 11.00.10570.1001"></meta></head><body>
<p>От... | 2,209 | ru | html | ru | html | code | {"qsc_code_num_words": 318, "qsc_code_num_chars": 2209.0, "qsc_code_mean_word_length": 5.38993711, "qsc_code_frac_words_unique": 0.55660377, "qsc_code_frac_chars_top_2grams": 0.00466744, "qsc_code_frac_chars_top_3grams": 0.042007, "qsc_code_frac_chars_top_4grams": 0.01516919, "qsc_code_frac_chars_dupe_5grams": 0.025670... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1diot9/MyJavaSecStudy | CodeAudit/RuoYi/RuoYi-4.7.5/ruoyi-admin/src/main/resources/static/ajax/libs/fullscreen/jquery.fullscreen.js | /**
* 基于jQuery FullScreen修改
* 新增支持IE全屏显示
* Copyright (c) 2019 ruoyi
*/
(function(jQuery) {
/**
* Sets or gets the fullscreen state.
*
* @param {boolean=} state
* True to enable fullscreen mode, false to disable it. If not
* specified then the current fullscre... | 6,192 | jquery.fullscreen | js | en | javascript | code | {"qsc_code_num_words": 498, "qsc_code_num_chars": 6192.0, "qsc_code_mean_word_length": 6.38955823, "qsc_code_frac_words_unique": 0.27108434, "qsc_code_frac_chars_top_2grams": 0.0565682, "qsc_code_frac_chars_top_3grams": 0.04714016, "qsc_code_frac_chars_top_4grams": 0.01414205, "qsc_code_frac_chars_dupe_5grams": 0.26398... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
1c-syntax/ssl_3_1 | src/cf/Reports/МестаИспользованияСсылок/Templates/ОсновнаяСхемаКомпоновкиДанных/Ext/Template.xml | <?xml version="1.0" encoding="UTF-8"?>
<DataCompositionSchema xmlns="http://v8.1c.ru/8.1/data-composition-system/schema" xmlns:dcscom="http://v8.1c.ru/8.1/data-composition-system/common" xmlns:dcscor="http://v8.1c.ru/8.1/data-composition-system/core" xmlns:dcsset="http://v8.1c.ru/8.1/data-composition-system/settings" ... | 9,827 | Template | xml | ru | xml | data | {"qsc_code_num_words": 1094, "qsc_code_num_chars": 9827.0, "qsc_code_mean_word_length": 6.14625229, "qsc_code_frac_words_unique": 0.15630713, "qsc_code_frac_chars_top_2grams": 0.04997026, "qsc_code_frac_chars_top_3grams": 0.04253421, "qsc_code_frac_chars_top_4grams": 0.04550863, "qsc_code_frac_chars_dupe_5grams": 0.674... | 0 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 1, "qsc_code_mean_word_length": 0, "qsc_code_frac_words_unique": 1, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code... |
1y33/100Days | day41/MLA.cu | #include <cuda_runtime.h>
#include <iostream>
#include <cmath>
#include <cstdlib>
#define DIM 128
#define NHEADS 4
#define QPROJ_DIM 64
#define KVPROJ_DIM 85
#define HEADDIM 32
__global__ void matmul_kernel(const float* A, const float* B, float* C, int M, int N, int K) {
int row = blockIdx.y * blockDim.y + thread... | 8,535 | MLA | cu | en | cuda | code | {"qsc_code_num_words": 1266, "qsc_code_num_chars": 8535.0, "qsc_code_mean_word_length": 3.73538705, "qsc_code_frac_words_unique": 0.09083728, "qsc_code_frac_chars_top_2grams": 0.07443434, "qsc_code_frac_chars_top_3grams": 0.07105096, "qsc_code_frac_chars_top_4grams": 0.02030027, "qsc_code_frac_chars_dupe_5grams": 0.443... | 1 | {"qsc_code_frac_chars_replacement_symbols": 0, "qsc_code_num_words": 0, "qsc_code_num_chars": 0, "qsc_code_mean_word_length": 0, "qsc_code_frac_chars_top_2grams": 0, "qsc_code_frac_chars_top_3grams": 0, "qsc_code_frac_chars_top_4grams": 0, "qsc_code_frac_chars_dupe_5grams": 0, "qsc_code_frac_chars_dupe_6grams": 0, "qsc... |
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