instruction stringclasses 100
values | code stringlengths 78 193k | response stringlengths 259 170k | file stringlengths 59 203 |
|---|---|---|---|
Add docstrings to make code maintainable |
# pylint: disable=relative-import
from __future__ import print_function
import os
import re
from config import CONFIG
from .git_adapter import GitRepositoryAdapter
class LearnXinY(GitRepositoryAdapter):
_adapter_name = "learnxiny"
_output_format = "code"
_cache_needed = True
_repository_url = "http... | --- +++ @@ -1,3 +1,10 @@+"""
+Adapters for the cheat sheets from the Learn X in Y project
+
+Configuration parameters:
+
+ log.level
+"""
# pylint: disable=relative-import
@@ -9,6 +16,9 @@
class LearnXinY(GitRepositoryAdapter):
+ """
+ Adapter for the LearnXinY project
+ """
_adapter_name = ... | https://raw.githubusercontent.com/chubin/cheat.sh/HEAD/lib/adapter/learnxiny.py |
Document all public functions with docstrings |
from __future__ import print_function
import sys
import os
import textwrap
import hashlib
import re
from itertools import groupby, chain
from subprocess import Popen
from tempfile import NamedTemporaryFile
from config import CONFIG
from languages_data import VIM_NAME
import cache
FNULL = open(os.devnull, "w")
TEXT ... | --- +++ @@ -1,3 +1,22 @@+"""
+Extract text from the text-code stream and comment it.
+
+Supports three modes of normalization and commenting:
+
+ 1. Don't add any comments
+ 2. Add comments
+ 3. Remove text, leave code only
+
+Since several operations are quite expensive,
+it actively uses caching.
+
+Exported... | https://raw.githubusercontent.com/chubin/cheat.sh/HEAD/lib/fmt/comments.py |
Write documentation strings for class attributes |
from __future__ import print_function
import sys
import logging
def fatal(text):
sys.stderr.write("ERROR: %s\n" % text)
sys.exit(1)
def error(text):
if not text.startswith("Too many queries"):
print(text)
logging.error("ERROR %s", text)
raise RuntimeError(text)
def log(text):
if ... | --- +++ @@ -1,3 +1,8 @@+"""
+Global functions that our used everywhere in the project.
+Please, no global variables here.
+For the configuration related things see `config.py`
+"""
from __future__ import print_function
@@ -6,11 +11,19 @@
def fatal(text):
+ """
+ Fatal error function.
+
+ The function ... | https://raw.githubusercontent.com/chubin/cheat.sh/HEAD/lib/globals.py |
Document functions with detailed explanations | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""Run masked LM/next sentence masked_lm pre-training for BERT."""
from __future__ import absolute_import
fro... | https://raw.githubusercontent.com/google-research/bert/HEAD/run_pretraining.py |
Add docstrings to meet PEP guidelines | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""Extract pre-computed feature vectors from BERT."""
from __future__ import absolute_import
from __future__ ... | https://raw.githubusercontent.com/google-research/bert/HEAD/extract_features.py |
Insert docstrings into my code | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""Functions and classes related to optimization (weight updates)."""
from __future__ import absolute_import
... | https://raw.githubusercontent.com/google-research/bert/HEAD/optimization.py |
Write documentation strings for class attributes | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""BERT finetuning runner."""
from __future__ import absolute_import
from __future__ import division
@@ -124,... | https://raw.githubusercontent.com/google-research/bert/HEAD/run_classifier.py |
Help me document legacy Python code | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""Create masked LM/next sentence masked_lm TF examples for BERT."""
from __future__ import absolute_import
f... | https://raw.githubusercontent.com/google-research/bert/HEAD/create_pretraining_data.py |
Expand my code with proper documentation strings | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""The main BERT model and related functions."""
from __future__ import absolute_import
from __future__ impor... | https://raw.githubusercontent.com/google-research/bert/HEAD/modeling.py |
Write documentation strings for class attributes | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""BERT finetuning runner with TF-Hub."""
from __future__ import absolute_import
from __future__ import divis... | https://raw.githubusercontent.com/google-research/bert/HEAD/run_classifier_with_tfhub.py |
Create docstrings for reusable components | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""Run BERT on SQuAD 1.1 and SQuAD 2.0."""
from __future__ import absolute_import
from __future__ import divi... | https://raw.githubusercontent.com/google-research/bert/HEAD/run_squad.py |
Add docstrings for internal functions | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | --- +++ @@ -12,6 +12,7 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""Tokenization classes."""
from __future__ import absolute_import
from __future__ import division
@@ -25,6 +... | https://raw.githubusercontent.com/google-research/bert/HEAD/tokenization.py |
Generate descriptive docstrings automatically |
import base64
import dataclasses
from enum import auto, IntEnum
from io import BytesIO
import os
from typing import List, Any, Dict, Union, Tuple
class SeparatorStyle(IntEnum):
ADD_COLON_SINGLE = auto()
ADD_COLON_TWO = auto()
ADD_COLON_SPACE_SINGLE = auto()
NO_COLON_SINGLE = auto()
NO_COLON_TWO ... | --- +++ @@ -1,3 +1,9 @@+"""
+Conversation prompt templates.
+
+We kindly request that you import fastchat instead of copying this file if you wish to use it.
+If you have any changes in mind, please contribute back so the community can benefit collectively and continue to maintain these valuable templates.
+"""
impo... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/conversation.py |
Add detailed documentation for each class |
import argparse
from collections import defaultdict
import re
import gradio as gr
from fastchat.llm_judge.common import (
load_questions,
load_model_answers,
load_single_model_judgments,
load_pairwise_model_judgments,
resolve_single_judgment_dict,
resolve_pairwise_judgment_dict,
get_singl... | --- +++ @@ -1,3 +1,7 @@+"""
+Usage:
+python3 qa_browser.py --share
+"""
import argparse
from collections import defaultdict
@@ -111,6 +115,7 @@
def post_process_answer(x):
+ """Fix Markdown rendering problems."""
x = x.replace("\u2022", "- ")
x = re.sub(newline_pattern1, "\n\g<1>", x)
x = re.s... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/llm_judge/qa_browser.py |
Add missing documentation to my Python functions | import dataclasses
import gc
import glob
import os
from accelerate import init_empty_weights
from accelerate.utils import set_module_tensor_to_device
from huggingface_hub import snapshot_download
import torch
from torch import Tensor
from torch.nn import functional as F
import torch.nn as nn
from tqdm import tqdm
from... | --- +++ @@ -22,6 +22,7 @@
@dataclasses.dataclass
class CompressionConfig:
+ """Group-wise quantization."""
num_bits: int
group_size: int
@@ -36,6 +37,7 @@
class CLinear(nn.Module):
+ """Compressed Linear Layer."""
def __init__(self, weight=None, bias=None, device=None):
super().... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/model/compression.py |
Add docstrings to improve readability | import argparse
from concurrent.futures import ProcessPoolExecutor
import json
from typing import Dict, Sequence, Optional
import transformers
from tqdm import tqdm
def make_sample(sample, start_idx, end_idx):
assert (end_idx - start_idx) % 2 == 0
return {
"id": sample["id"] + "_" + str(start_idx),
... | --- +++ @@ -1,3 +1,11 @@+"""
+Split long conversations based on certain max length.
+
+Usage: python3 -m fastchat.data.split_long_conversation \
+ --in sharegpt_clean.json \
+ --out sharegpt_split.json \
+ --model-name-or-path $<model-name>
+"""
import argparse
from concurrent.futures import ProcessPoolExecu... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/data/split_long_conversation.py |
Help me comply with documentation standards |
import ast
import dataclasses
import glob
import json
import os
import re
import time
from typing import Optional
import openai
import anthropic
from fastchat.model.model_adapter import (
get_conversation_template,
ANTHROPIC_MODEL_LIST,
OPENAI_MODEL_LIST,
)
# API setting constants
API_MAX_RETRY = 16
API... | --- +++ @@ -1,3 +1,6 @@+"""
+Common data structures and utilities.
+"""
import ast
import dataclasses
@@ -83,6 +86,7 @@
def load_questions(question_file: str, begin: Optional[int], end: Optional[int]):
+ """Load questions from a file."""
questions = []
with open(question_file, "r") as ques_file:
... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/llm_judge/common.py |
Add inline docstrings for readability | import json
def identity_questions():
content = []
name = "Vicuna"
org = "Large Model Systems Organization (LMSYS)"
def generate_conversations(questions, answers):
for q in questions:
for a in answers:
content.append(
{
... | --- +++ @@ -1,7 +1,13 @@+"""
+Hardcoded question and answers.
+"""
import json
def identity_questions():
+ """ "
+ Adapted from https://github.com/young-geng/koala_data_pipeline/blob/main/process_hard_coded_data.py
+ """
content = []
name = "Vicuna"
@@ -159,4 +165,4 @@ content = []
c... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/data/hardcoded_questions.py |
Write clean docstrings for readability |
import math
import os
import re
import sys
from typing import Dict, List, Optional
import warnings
if sys.version_info >= (3, 9):
from functools import cache
else:
from functools import lru_cache as cache
import psutil
import torch
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCau... | --- +++ @@ -1,3 +1,4 @@+"""Model adapter registration."""
import math
import os
@@ -94,6 +95,7 @@
class BaseModelAdapter:
+ """The base and the default model adapter."""
use_fast_tokenizer = True
@@ -148,11 +150,13 @@
def register_model_adapter(cls):
+ """Register a model adapter."""
mod... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/model/model_adapter.py |
Fully document this Python code with docstrings | import math
from typing import List, Optional, Tuple
import torch
from torch import nn
import transformers
def rotate_half(x):
x1 = x[..., : x.shape[-1] // 2].clone()
x2 = x[..., x.shape[-1] // 2 :].clone()
return torch.cat((-x2, x1), dim=-1)
def apply_rotary_pos_emb(q, k, cos, sin, position_ids):
... | --- +++ @@ -1,3 +1,7 @@+"""
+Monkey patch the llama implementation in the huggingface/transformers library.
+Avoid bugs in mps backend by not using in-place operations.
+"""
import math
from typing import List, Optional, Tuple
@@ -7,6 +11,7 @@
def rotate_half(x):
+ """Rotates half the hidden dims of the inpu... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/model/monkey_patch_non_inplace.py |
Add docstrings to meet PEP guidelines | import argparse
import json
import os
import random
import time
import shortuuid
import torch
from tqdm import tqdm
from fastchat.llm_judge.common import load_questions, temperature_config
from fastchat.model import load_model, get_conversation_template
from fastchat.utils import str_to_torch_dtype
def run_eval(
... | --- +++ @@ -1,3 +1,8 @@+"""Generate answers with local models.
+
+Usage:
+python3 gen_model_answer.py --model-path lmsys/fastchat-t5-3b-v1.0 --model-id fastchat-t5-3b-v1.0
+"""
import argparse
import json
import os
@@ -186,6 +191,7 @@
def reorg_answer_file(answer_file):
+ """Sort by question id and de-duplica... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/llm_judge/gen_model_answer.py |
Add detailed documentation for each class | # Adapted from tatsu-lab@stanford_alpaca. Below is the original copyright:
# Copyright 2023 Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may ob... | --- +++ @@ -73,6 +73,7 @@
def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output_dir: str):
+ """Collects the state dict and dump to disk."""
state_dict = trainer.model.state_dict()
if trainer.args.should_save:
cpu_state_dict = {key: value.cpu() for key, value in state_dict.i... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/train/train_flant5.py |
Expand my code with proper documentation strings | # This code is based on tatsu-lab/stanford_alpaca. Below is the original copyright:
#
# Copyright 2023 Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# ... | --- +++ @@ -69,6 +69,7 @@
def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output_dir: str):
+ """Collects the state dict and dump to disk."""
state_dict = trainer.model.state_dict()
if trainer.args.should_save:
cpu_state_dict = {key: value.cpu() for key, value in state_dict.i... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/train/train_baichuan.py |
Improve my code by adding docstrings | import asyncio
import argparse
import json
import os
from typing import Generator, Optional, Union, Dict, List, Any
import aiohttp
import fastapi
from fastapi import Depends, HTTPException
from fastapi.exceptions import RequestValidationError
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses im... | --- +++ @@ -1,3 +1,12 @@+"""A server that provides OpenAI-compatible RESTful APIs. It supports:
+
+- Chat Completions. (Reference: https://platform.openai.com/docs/api-reference/chat)
+- Completions. (Reference: https://platform.openai.com/docs/api-reference/completions)
+- Embeddings. (Reference: https://platform.open... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/serve/openai_api_server.py |
Auto-generate documentation strings for this file | import os
import math
import multiprocessing as mp
from functools import partial
import numpy as np
from scipy.special import expit
from scipy.optimize import minimize
import pandas as pd
from tqdm import tqdm
STYLE_CONTROL_ELEMENTS_V1 = [
"sum_assistant_a_tokens",
"header_count_a",
"list_count_a",
"b... | --- +++ @@ -29,6 +29,11 @@
def preprocess_for_elo(df):
+ """
+ in Elo we want numpy arrays for matchups and outcomes
+ matchups: int32 (N,2) contains model ids for the competitors in a match
+ outcomes: float64 (N,) contains 1.0, 0.5, or 0.0 representing win, tie, or loss for model_a
+ """
... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/serve/monitor/rating_systems.py |
Add professional docstrings to my codebase | # A JSON logger that sends data to remote endpoint.
# Architecturally, it hosts a background thread that sends logs to a remote endpoint.
import os
import json
import requests
import threading
import queue
import logging
_global_logger = None
def get_remote_logger():
global _global_logger
if _global_logger i... | --- +++ @@ -22,6 +22,7 @@
class EmptyLogger:
+ """Dummy logger that does nothing."""
def __init__(self):
pass
@@ -31,6 +32,7 @@
class RemoteLogger:
+ """A JSON logger that sends data to remote endpoint."""
def __init__(self, url: str):
self.url = url
@@ -54,4 +56,4 @@ ... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/serve/remote_logger.py |
Write docstrings for utility functions | # This code is based on tatsu-lab/stanford_alpaca. Below is the original copyright:
#
# Copyright 2023 Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# ... | --- +++ @@ -69,6 +69,7 @@
def safe_save_model_for_hf_trainer(trainer: transformers.Trainer, output_dir: str):
+ """Collects the state dict and dump to disk."""
state_dict = trainer.model.state_dict()
if trainer.args.should_save:
cpu_state_dict = {key: value.cpu() for key, value in state_dict.i... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/train/train_with_template.py |
Generate docstrings for each module | from asyncio import AbstractEventLoop
from io import BytesIO
import base64
import json
import logging
import logging.handlers
import os
import platform
import sys
import time
from typing import AsyncGenerator, Generator
import warnings
import requests
from fastchat.constants import LOGDIR
handler = None
visited_log... | --- +++ @@ -1,3 +1,6 @@+"""
+Common utilities.
+"""
from asyncio import AbstractEventLoop
from io import BytesIO
import base64
@@ -79,6 +82,9 @@
class StreamToLogger(object):
+ """
+ Fake file-like stream object that redirects writes to a logger instance.
+ """
def __init__(self, logger, log_leve... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/utils.py |
Add documentation for all methods | # This code is based on tatsu-lab/stanford_alpaca. Below is the original copyright:
#
# Copyright 2023 Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# ... | --- +++ @@ -314,6 +314,7 @@
class SupervisedDataset(Dataset):
+ """Dataset for supervised fine-tuning."""
def __init__(
self, raw_data, data_args, tokenizer: transformers.PreTrainedTokenizer
@@ -340,6 +341,7 @@
class LazySupervisedDataset(Dataset):
+ """Dataset for supervised fine-tuning."... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/train/train_yuan2.py |
Turn comments into proper docstrings | # This code is based on tatsu-lab/stanford_alpaca. Below is the original copyright:
#
# Copyright 2023 Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# ... | --- +++ @@ -178,6 +178,7 @@
class SupervisedDataset(Dataset):
+ """Dataset for supervised fine-tuning."""
def __init__(self, raw_data, tokenizer: transformers.PreTrainedTokenizer):
super(SupervisedDataset, self).__init__()
@@ -202,6 +203,7 @@
class LazySupervisedDataset(Dataset):
+ """Data... | https://raw.githubusercontent.com/lm-sys/FastChat/HEAD/fastchat/train/train.py |
Add well-formatted docstrings |
import enum
from typing import Dict, List, Optional, Set, Tuple
from vllm.block import PhysicalTokenBlock
from .sequence import Sequence, SequenceGroup, SequenceStatus
from vllm.utils import Device
# Mapping: logical block number -> physical block.
BlockTable = List[PhysicalTokenBlock]
class BlockAllocator:
d... | --- +++ @@ -1,3 +1,4 @@+"""A block manager that manages token blocks."""
import enum
from typing import Dict, List, Optional, Set, Tuple
@@ -11,6 +12,12 @@
class BlockAllocator:
+ """Manages free physical token blocks for a device.
+
+ The allocator maintains a list of free blocks and allocates a block wh... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/block_manager.py |
Create Google-style docstrings for my code |
from enum import IntEnum
from functools import cached_property
from typing import Callable, List, Optional, Union
import torch
_SAMPLING_EPS = 1e-5
class SamplingType(IntEnum):
GREEDY = 0
RANDOM = 1
BEAM = 2
LogitsProcessor = Callable[[List[int], torch.Tensor], torch.Tensor]
"""LogitsProcessor is a f... | --- +++ @@ -1,3 +1,4 @@+"""Sampling parameters for text generation."""
from enum import IntEnum
from functools import cached_property
@@ -21,6 +22,74 @@
class SamplingParams:
+ """Sampling parameters for text generation.
+
+ Overall, we follow the sampling parameters from the OpenAI text completion
+ A... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/sampling_params.py |
Add docstrings to existing functions | # Copyright (c) 2022-2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# See LICENSE for license information.
#
# From https://github.com/NVIDIA/TransformerEngine/blob/main/docs/examples/te_llama/te_llama.py
#
# Edited by fumiama.
import re
from contextlib import contextmanager
from typing import Dict
imp... | --- +++ @@ -27,6 +27,9 @@
@contextmanager
def replace_decoder(te_decoder_cls, llama_rms_norm_cls):
+ """
+ Replace `LlamaDecoderLayer` with custom `TELlamaDecoderLayer`.
+ """
original_llama_decoder_cls = (
transformers.models.llama.modeling_llama.LlamaDecoderLayer
)
@@ -45,6 +48,15 @@
... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/cuda/te_llama.py |
Document classes and their methods | from typing import List, Optional
import torch
from .sequence import (
PromptLogprobs,
SampleLogprobs,
SequenceGroup,
SequenceStatus,
)
class CompletionOutput:
def __init__(
self,
index: int,
text: str,
token_ids: List[int],
cumulative_logprob: float,
... | --- +++ @@ -10,6 +10,18 @@
class CompletionOutput:
+ """The output data of one completion output of a request.
+
+ Args:
+ index: The index of the output in the request.
+ text: The generated output text.
+ token_ids: The token IDs of the generated output text.
+ cumulative_logprob... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/output.py |
Create docstrings for API functions |
import contextlib
import torch
import torch.nn as nn
from vllm.config import ModelConfig
from vllm.model_executor.models import ModelRegistry
from vllm.model_executor.weight_utils import get_quant_config, initialize_dummy_weights
from .llama import LlamaModel
@contextlib.contextmanager
def _set_default_torch_dtyp... | --- +++ @@ -1,3 +1,4 @@+"""Utilities for selecting and loading models."""
import contextlib
@@ -13,6 +14,7 @@
@contextlib.contextmanager
def _set_default_torch_dtype(dtype: torch.dtype):
+ """Sets the default torch dtype to the given dtype."""
old_dtype = torch.get_default_dtype()
torch.set_default... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/model_loader.py |
Document all endpoints with docstrings | from typing import Optional, Union, Tuple
import os
import torch
from transformers import PretrainedConfig
from vllm.logger import init_logger
from vllm.transformers_utils.config import get_config
from vllm.utils import get_cpu_memory, is_hip
import argparse
import dataclasses
from dataclasses import dataclass
log... | --- +++ @@ -19,6 +19,48 @@
class ModelConfig:
+ """Configuration for the model.
+
+ Args:
+ model: Name or path of the huggingface model to use.
+ tokenizer: Name or path of the huggingface tokenizer to use.
+ tokenizer_mode: Tokenizer mode. "auto" will use the fast tokenizer if
+ ... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/configs.py |
Generate consistent docstrings |
import copy
import enum
from typing import Dict, List, Optional, Union
import torch
from vllm.block import LogicalTokenBlock
from .sampling_params import SamplingParams
PromptLogprobs = List[Optional[Dict[int, float]]]
SampleLogprobs = List[Dict[int, float]]
class SequenceStatus(enum.Enum):
WAITING = enum.auto... | --- +++ @@ -1,3 +1,4 @@+"""Sequence and its related classes."""
import copy
import enum
@@ -11,6 +12,7 @@
class SequenceStatus(enum.Enum):
+ """Status of a sequence."""
WAITING = enum.auto()
RUNNING = enum.auto()
@@ -48,6 +50,17 @@
class SequenceData:
+ """Data associated with a sequence.
... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/sequence.py |
Help me document legacy Python code | from io import BufferedWriter, BytesIO
from pathlib import Path
from typing import Dict, Tuple, Optional, Union, List
import av
from av.audio.frame import AudioFrame
from av.audio.resampler import AudioResampler
import numpy as np
video_format_dict: Dict[str, str] = {
"m4a": "mp4",
}
audio_format_dict: Dict[str... | --- +++ @@ -19,6 +19,9 @@
def wav2(i: BytesIO, o: BufferedWriter, format: str):
+ """
+ https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI/blob/412a9950a1e371a018c381d1bfb8579c4b0de329/infer/lib/audio.py#L20
+ """
inp = av.open(i, "r")
format = video_format_dict.get(format, format)... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/tools/audio/av.py |
Add structured docstrings to improve clarity | import wave
from io import BytesIO
import numpy as np
from .np import float_to_int16
from .av import wav2
def _pcm_to_wav_buffer(wav: np.ndarray, sample_rate: int = 24000) -> BytesIO:
# Create an in-memory byte stream buffer
buf = BytesIO()
# Open a WAV file stream in write mode
with wave.open(buf, "... | --- +++ @@ -6,6 +6,13 @@
def _pcm_to_wav_buffer(wav: np.ndarray, sample_rate: int = 24000) -> BytesIO:
+ """
+ Convert PCM audio data to a WAV format byte stream (internal utility function).
+
+ :param wav: PCM data, NumPy array, typically in float32 format.
+ :param sample_rate: Sample rate (in Hz), de... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/tools/audio/pcm.py |
Generate docstrings with parameter types | import copy
from collections import defaultdict
import os
import time
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Tuple, Union
from vllm.config import CacheConfig, ModelConfig, ParallelConfig, SchedulerConfig
from .scheduler import Scheduler, SchedulerOutputs
from .configs import EngineArgs
... | --- +++ @@ -36,6 +36,31 @@
class LLMEngine:
+ """An LLM engine that receives requests and generates texts.
+
+ This is the main class for the vLLM engine. It receives requests
+ from clients and generates texts from the LLM. It includes a tokenizer, a
+ language model (possibly distributed across multip... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/llm_engine.py |
Create docstrings for all classes and functions | from typing import List, Optional, Union
from tqdm import tqdm
from transformers import PreTrainedTokenizer, PreTrainedTokenizerFast
from vllm.utils import Counter
from .configs import EngineArgs
from .llm_engine import LLMEngine
from .output import RequestOutput
from .sampling_params import SamplingParams
class LL... | --- +++ @@ -11,6 +11,59 @@
class LLM:
+ """An LLM for generating texts from given prompts and sampling parameters.
+
+ This class includes a tokenizer, a language model (possibly distributed
+ across multiple GPUs), and GPU memory space allocated for intermediate
+ states (aka KV cache). Given a batch o... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/llm.py |
Create docstrings for reusable components |
import os
from typing import Dict, List, Optional, Tuple
import torch
import torch.distributed
from vllm.config import CacheConfig, ModelConfig, ParallelConfig, SchedulerConfig
from vllm.model_executor import set_random_seed
from vllm.model_executor.parallel_utils.communication_op import broadcast_object_list
from v... | --- +++ @@ -1,3 +1,4 @@+"""A GPU worker class."""
import os
from typing import Dict, List, Optional, Tuple
@@ -16,6 +17,12 @@
class Worker:
+ """A worker class that executes (a partition of) the model on a GPU.
+
+ Each worker is associated with a single GPU. The worker is responsible for
+ maintaining... | https://raw.githubusercontent.com/2noise/ChatTTS/HEAD/ChatTTS/model/velocity/worker.py |
Add minimal docstrings for each function | # Copyright (c) Microsoft Corporation.
import os
from torch.utils.data import Dataset, DataLoader
import copy
from typing import Text, Union
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Function
from ql... | --- +++ @@ -21,6 +21,19 @@
class ADARNN(Model):
+ """ADARNN Model
+
+ Parameters
+ ----------
+ d_feat : int
+ input dimension for each time step
+ metric: str
+ the evaluation metric used in early stop
+ optimizer : str
+ optimizer name
+ GPU : str
+ the GPU ID(s) u... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_adarnn.py |
Add docstrings to make code maintainable | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from typing import Text, Union
import copy
from ...utils import get_or_create_path
from ...log import get_module_logger
import torch
im... | --- +++ @@ -178,6 +178,21 @@
class SFM(Model):
+ """SFM Model
+
+ Parameters
+ ----------
+ input_dim : int
+ input dimension
+ output_dim : int
+ output dimension
+ lr : float
+ learning rate
+ optimizer : str
+ optimizer name
+ GPU : int
+ the GPU ID used... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_sfm.py |
Add docstrings for utility scripts | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import io
import os
import copy
import math
import json
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
try:
from torch.ut... | --- +++ @@ -31,6 +31,33 @@
class TRAModel(Model):
+ """
+ TRA Model
+
+ Args:
+ model_config (dict): model config (will be used by RNN or Transformer)
+ tra_config (dict): TRA config (will be used by TRA)
+ model_type (str): which backbone model to use (RNN/Transformer)
+ lr (fl... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_tra.py |
Fully document this Python code with docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import copy
from typing import Iterable
import pandas as pd
import plotly.graph_objs as go
from ..graph import ScatterGraph
from ..analysis_position.parse_position import get_position_data
def _get_figure_with_position(
position: dict, la... | --- +++ @@ -14,6 +14,14 @@ def _get_figure_with_position(
position: dict, label_data: pd.DataFrame, start_date=None, end_date=None
) -> Iterable[go.Figure]:
+ """Get average analysis figures
+
+ :param position: position
+ :param label_data:
+ :param start_date:
+ :param end_date:
+ :return:
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/analysis_position/rank_label.py |
Add docstrings explaining edge cases | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import logging
import os
from pathlib import Path
import sys
import fire
from jinja2 import Template, meta
from ruamel.yaml import YAML
import qlib
from qlib.config import C
from qlib.log import get_module_logger
from qlib.model.trainer import... | --- +++ @@ -28,6 +28,16 @@
def sys_config(config, config_path):
+ """
+ Configure the `sys` section
+
+ Parameters
+ ----------
+ config : dict
+ configuration of the workflow.
+ config_path : str
+ path of the configuration
+ """
sys_config = config.get("sys", {})
# a... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/cli/run.py |
Add detailed docstrings explaining each function | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import copy
import torch
import warnings
import numpy as np
import pandas as pd
from qlib.utils.data import guess_horizon
from qlib.utils import init_instance_by_config
from qlib.data.dataset import DatasetH
device = "cuda" if torch.cuda.is_ava... | --- +++ @@ -21,6 +21,13 @@
def _create_ts_slices(index, seq_len):
+ """
+ create time series slices from pandas index
+
+ Args:
+ index (pd.MultiIndex): pandas multiindex with <instrument, datetime> order
+ seq_len (int): sequence length
+ """
assert isinstance(index, pd.MultiIndex), ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/data/dataset.py |
Insert docstrings into my code | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from pathlib import Path
from setuptools_scm import get_version
try:
from ._version import version as __version__
except ImportError:
__version__ = get_version(root="..", relative_to=__file__)
__version__bak = __version__ # This version... | --- +++ @@ -23,6 +23,22 @@
# init qlib
def init(default_conf="client", **kwargs):
+ """
+
+ Parameters
+ ----------
+ default_conf: str
+ the default value is client. Accepted values: client/server.
+ **kwargs :
+ clear_mem_cache: str
+ the default value is True;
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/__init__.py |
Add structured docstrings to improve clarity | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import torch
from torch import nn
from .utils import preds_to_weight_with_clamp, SingleMetaBase
class TimeWeightMeta(SingleMetaBase):
def __init__(self, hist_step_n, clip_weight=None, clip_method="clamp"):
# clip... | --- +++ @@ -42,6 +42,12 @@
class PredNet(nn.Module):
def __init__(self, step, hist_step_n, clip_weight=None, clip_method="tanh", alpha: float = 0.0):
+ """
+ Parameters
+ ----------
+ alpha : float
+ the regularization for sub model (useful when align meta model with linear... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/meta/data_selection/net.py |
Write docstrings describing each step | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import pandas as pd
from datetime import datetime
from qlib.data.cache import H
from qlib.data.data import Cal
from qlib.data.ops import ElemOperator, PairOperator
from qlib.utils.time import time_to_day_index
def get_calenda... | --- +++ @@ -11,6 +11,22 @@
def get_calendar_day(freq="1min", future=False):
+ """
+ Load High-Freq Calendar Date Using Memcache.
+ !!!NOTE: Loading the calendar is quite slow. So loading calendar before start multiprocessing will make it faster.
+
+ Parameters
+ ----------
+ freq : str
+ fr... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/ops/high_freq.py |
Write docstrings that follow conventions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
import warnings
from typing import Union, Literal
from ..log import get_module_logger
from ..utils import get_date_range
from ..utils.r... | --- +++ @@ -24,6 +24,26 @@
def risk_analysis(r, N: int = None, freq: str = "day", mode: Literal["sum", "product"] = "sum"):
+ """Risk Analysis
+ NOTE:
+ The calculation of annualized return is different from the definition of annualized return.
+ It is implemented by design.
+ Qlib tries to cumulate ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/evaluate.py |
Add docstrings for utility scripts | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# pylint: skip-file
# flake8: noqa
import pathlib
import pickle
import pandas as pd
from ruamel.yaml import YAML
from ...data import D
from ...config import C
from ...log import get_module_logger
from ...utils import get_next_trading_date
from .... | --- +++ @@ -19,6 +19,14 @@
def load_instance(file_path):
+ """
+ load a pickle file
+ Parameter
+ file_path : string / pathlib.Path()
+ path of file to be loaded
+ :return
+ An instance loaded from file
+ """
file_path = pathlib.Path(file_path)
if... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/online/utils.py |
Add detailed docstrings explaining each function | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
import numpy as np
from qlib.contrib.report.data.base import FeaAnalyser
from qlib.contrib.report.utils import sub_fig_generator
from qlib.utils.paral import datetime_groupby_apply
from qlib.contrib.eva.alpha import pred_autoc... | --- +++ @@ -1,5 +1,17 @@ # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
+"""
+Here we have a comprehensive set of analysis classes.
+
+Here is an example.
+
+.. code-block:: python
+
+ from qlib.contrib.report.data.ana import FeaMeanStd
+ fa = FeaMeanStd(ret_df)
+ fa.plot_all(wspace=... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/data/ana.py |
Generate docstrings for each module | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import annotations
import os
import re
import copy
import logging
import platform
import multiprocessing
from pathlib import Path
from typing import Callable, Optional, Union
from typing import TYPE_CHECKING
from qlib.constant i... | --- +++ @@ -1,5 +1,15 @@ # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
+"""
+About the configs
+=================
+
+The config will be based on _default_config.
+Two modes are supported
+- client
+- server
+
+"""
from __future__ import annotations
@@ -27,6 +37,17 @@
class QSettings... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/config.py |
Create docstrings for each class method | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# pylint: skip-file
# flake8: noqa
import logging
from ...log import get_module_logger
from ..evaluate import risk_analysis
from ...data import D
class User:
def __init__(self, account, strategy, model, verbose=False):
self.logger... | --- +++ @@ -13,6 +13,19 @@
class User:
def __init__(self, account, strategy, model, verbose=False):
+ """
+ A user in online system, which contains account, strategy and model three module.
+ Parameter
+ account : Account()
+ strategy :
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/online/user.py |
Provide docstrings following PEP 257 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
import numpy as np
from copy import deepcopy
from joblib import Parallel, delayed # pylint: disable=E0401
from typing import Dict, List, Union, Text, Tuple
from qlib.data.dataset.utils import init_task_handler
from qlib.data.d... | --- +++ @@ -27,6 +27,25 @@ self.exp_name = exp_name
def setup(self, trainer=TrainerR, trainer_kwargs={}):
+ """
+ after running this function `self.data_ic_df` will become set.
+ Each col represents a data.
+ Each row represents the Timestamp of performance of that data.
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/meta/data_selection/dataset.py |
Provide clean and structured docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import torch
from torch import nn
from qlib.constant import EPS
from qlib.log import get_module_logger
class ICLoss(nn.Module):
def __init__(self, skip_size=50):
super().__init__()
self.skip_size = skip_s... | --- +++ @@ -15,6 +15,15 @@ self.skip_size = skip_size
def forward(self, pred, y, idx):
+ """forward.
+ FIXME:
+ - Some times it will be a slightly different from the result from `pandas.corr()`
+ - It may be caused by the precision problem of model;
+
+ :param pred:
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/meta/data_selection/utils.py |
Add well-formatted docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
import numpy as np
import torch
from torch import nn
from torch import optim
from tqdm.auto import tqdm
import copy
from typing import Union, List
from ....model.meta.dataset import MetaTaskDataset
from ....model.meta.model i... | --- +++ @@ -38,6 +38,9 @@
class MetaModelDS(MetaTaskModel):
+ """
+ The meta-model for meta-learning-based data selection.
+ """
def __init__(
self,
@@ -52,6 +55,10 @@ alpha=0.0,
loss_skip_thresh=50,
):
+ """
+ loss_skip_size: int
+ The number ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/meta/data_selection/model.py |
Generate docstrings for script automation | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
from collections import defaultdict
import os
import gc
import numpy as np
import pandas as pd
from packaging import version
from typing import Callable, Optional, Text, Unio... | --- +++ @@ -37,6 +37,22 @@
class DNNModelPytorch(Model):
+ """DNN Model
+ Parameters
+ ----------
+ input_dim : int
+ input dimension
+ output_dim : int
+ output dimension
+ layers : tuple
+ layer sizes
+ lr : float
+ learning rate
+ optimizer : str
+ optim... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_nn.py |
Write docstrings describing each step | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import copy
import math
from typing import Text, Union
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch... | --- +++ @@ -27,6 +27,21 @@
class ADD(Model):
+ """ADD Model
+
+ Parameters
+ ----------
+ lr : float
+ learning rate
+ d_feat : int
+ input dimensions for each time step
+ metric : str
+ the evaluation metric used in early stop
+ optimizer : str
+ optimizer n... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_add.py |
Add docstrings that explain logic | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from pathlib import Path
import pickle
from typing import Optional, Union
import pandas as pd
import yaml
from qlib.contrib.meta.data_selection.dataset import InternalData, MetaDatasetDS
from qlib.contrib.meta.data_selection.model import MetaMod... | --- +++ @@ -68,6 +68,13 @@
class DDGDA(Rolling):
+ """
+ It is a rolling based on DDG-DA
+
+ **NOTE**
+ before running the example, please clean your previous results with following command
+ - `rm -r mlruns`
+ """
def __init__(
self,
@@ -82,6 +89,27 @@ working_dir: Optiona... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/rolling/ddgda.py |
Expand my code with proper documentation strings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
from torch.utils.data import DataLoader
import numpy as np
import pandas as pd
from typing import Union
import copy
import torch
import torch.optim as optim
from torch.optim... | --- +++ @@ -31,6 +31,23 @@
class GeneralPTNN(Model):
+ """
+ Motivation:
+ We want to provide a Qlib General Pytorch Model Adaptor
+ You can reuse it for all kinds of Pytorch models.
+ It should include the training and predict process
+
+ Parameters
+ ----------
+ d_feat : int
+... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_general_nn.py |
Write documentation strings for class attributes | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import cvxpy as cp
from typing import Union, Optional, Dict, Any, List
from qlib.log import get_module_logger
from .base import BaseOptimizer
logger = get_module_logger("EnhancedIndexingOptimizer")
class EnhancedIndexingOp... | --- +++ @@ -13,6 +13,35 @@
class EnhancedIndexingOptimizer(BaseOptimizer):
+ """
+ Portfolio Optimizer for Enhanced Indexing
+
+ Notations:
+ w0: current holding weights
+ wb: benchmark weight
+ r: expected return
+ F: factor exposure
+ cov_b: factor covariance
+ v... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/optimizer/enhanced_indexing.py |
Document all public functions with docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from functools import partial
import pandas as pd
import plotly.graph_objs as go
import statsmodels.api as sm
import matplotlib.pyplot as plt
from scipy import stats
from typing import Sequence
from qlib.typehint import Literal
from ..graph ... | --- +++ @@ -19,6 +19,13 @@
def _group_return(pred_label: pd.DataFrame = None, reverse: bool = False, N: int = 5, **kwargs) -> tuple:
+ """
+
+ :param pred_label:
+ :param reverse:
+ :param N:
+ :return:
+ """
if reverse:
pred_label["score"] *= -1
@@ -72,6 +79,12 @@
def _plot_qq... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/analysis_model/analysis_model_performance.py |
Fully document this Python code with docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import warnings
import numpy as np
import pandas as pd
import lightgbm as lgb
from ...model.base import ModelFT
from ...data.dataset import DatasetH
from ...data.dataset.handler import DataHandlerLP
from ...model.interpret.base import LightGBMFI... | --- +++ @@ -13,6 +13,7 @@
class HFLGBModel(ModelFT, LightGBMFInt):
+ """LightGBM Model for high frequency prediction"""
def __init__(self, loss="mse", **kwargs):
if loss not in {"mse", "binary"}:
@@ -22,6 +23,9 @@ self.model = None
def _cal_signal_metrics(self, y_test, l_cut, r_cut... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/highfreq_gdbt_model.py |
Help me write clear docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from typing import Text, Union
import copy
from ...utils import get_or_create_path
from ...log import get_module_logger
import torch
i... | --- +++ @@ -37,6 +37,27 @@ device,
**params,
):
+ """Build a Sandwich model
+
+ Parameters
+ ----------
+ fea_dim : int
+ The feature dimension
+ cnn_dim_1 : int
+ The hidden dimension of the first CNN
+ cnn_dim_2 : int
+ T... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_sandwich.py |
Generate missing documentation strings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
from typing import Dict, Iterable, Union
def align_index(df_dict, join):
res = {}
for k, df in df_dict.items():
if join is not None and k != join:
df = df.reindex(df_dict[join].index)
res[k... | --- +++ @@ -15,12 +15,35 @@
# Mocking the pd.DataFrame class
class SepDataFrame:
+ """
+ (Sep)erate DataFrame
+ We usually concat multiple dataframe to be processed together(Such as feature, label, weight, filter).
+ However, they are usually be used separately at last.
+ This will result in extra cos... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/data/utils/sepdf.py |
Improve my code by adding docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
from ..graph import SubplotsGraph, BaseGraph
def _calculate_maximum(df: pd.DataFrame, is_ex: bool = False):
if is_ex:
end_date = df["cum_ex_return_wo_cost_mdd"].idxmin()
start_date = df.loc[df.index <= e... | --- +++ @@ -7,6 +7,12 @@
def _calculate_maximum(df: pd.DataFrame, is_ex: bool = False):
+ """
+
+ :param df:
+ :param is_ex:
+ :return:
+ """
if is_ex:
end_date = df["cum_ex_return_wo_cost_mdd"].idxmin()
start_date = df.loc[df.index <= end_date]["cum_ex_return_wo_cost"].idxmax(... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/analysis_position/report.py |
Add documentation for all methods | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import warnings
import numpy as np
import pandas as pd
import scipy.optimize as so
from typing import Optional, Union, Callable, List
from .base import BaseOptimizer
class PortfolioOptimizer(BaseOptimizer):
OPT_GMV = "gmv"
OPT_MVO = ... | --- +++ @@ -12,6 +12,17 @@
class PortfolioOptimizer(BaseOptimizer):
+ """Portfolio Optimizer
+
+ The following optimization algorithms are supported:
+ - `gmv`: Global Minimum Variance Portfolio
+ - `mvo`: Mean Variance Optimized Portfolio
+ - `rp`: Risk Parity
+ - `inv`: Inverse V... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/optimizer/optimizer.py |
Add docstrings for internal functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from typing import Iterable
import pandas as pd
import plotly.graph_objs as py
from ...evaluate import risk_analysis
from ..graph import SubplotsGraph, ScatterGraph
def _get_risk_analysis_data_with_report(
report_normal_df: pd.DataFrame... | --- +++ @@ -17,6 +17,13 @@ # report_long_short_df: pd.DataFrame,
date: pd.Timestamp,
) -> pd.DataFrame:
+ """Get risk analysis data with report
+
+ :param report_normal_df: report data
+ :param report_long_short_df: report data
+ :param date: date string
+ :return:
+ """
analysis = di... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/analysis_position/risk_analysis.py |
Write docstrings for algorithm functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import lightgbm as lgb
import numpy as np
import pandas as pd
from typing import Text, Union
from ...model.base import Model
from ...data.dataset import DatasetH
from ...data.dataset.handler import DataHandlerLP
from ...model.interpret.base impor... | --- +++ @@ -13,6 +13,7 @@
class DEnsembleModel(Model, FeatureInt):
+ """Double Ensemble Model"""
def __init__(
self,
@@ -137,6 +138,17 @@ return dtrain, dvalid
def sample_reweight(self, loss_curve, loss_values, k_th):
+ """
+ the SR module of Double Ensemble
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/double_ensemble.py |
Add return value explanations in docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from .order_generator import OrderGenWInteract
from .signal_strategy import WeightStrategyBase
class SoftTopkStrategy(WeightStrategyBase):
def __init__(
self,
model=None,
dataset=None,
topk=None,
orde... | --- +++ @@ -18,6 +18,20 @@ buy_method="first_fill",
**kwargs,
):
+ """
+ Refactored SoftTopkStrategy with a budget-constrained rebalancing engine.
+
+ Parameters
+ ----------
+ topk : int
+ The number of top-N stocks to be held in the portfolio.
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/cost_control.py |
Document this script properly | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import matplotlib.pyplot as plt
import pandas as pd
def sub_fig_generator(sub_figsize=(3, 3), col_n=10, row_n=1, wspace=None, hspace=None, sharex=False, sharey=False):
assert col_n > 1
while True:
fig, axes = plt.subplots(
... | --- +++ @@ -5,6 +5,30 @@
def sub_fig_generator(sub_figsize=(3, 3), col_n=10, row_n=1, wspace=None, hspace=None, sharex=False, sharey=False):
+ """sub_fig_generator.
+ it will return a generator, each row contains <col_n> sub graph
+
+ FIXME: Known limitation:
+ - The last row will not be plotted automat... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/utils.py |
Improve my code by adding docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from scipy.stats import spearmanr, pearsonr
from ..data import D
from collections import OrderedDict
def _get_position_value_from_d... | --- +++ @@ -15,6 +15,14 @@
def _get_position_value_from_df(evaluate_date, position, close_data_df):
+ """Get position value by existed close data df
+ close_data_df:
+ pd.DataFrame
+ multi-index
+ close_data_df['$close'][stock_id][evaluate_date]: close price for (stock_id, evaluate_date)
... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/evaluate_portfolio.py |
Create Google-style docstrings for my code | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import copy
from typing import Iterable
import pandas as pd
import plotly.graph_objs as go
from ..graph import BaseGraph, SubplotsGraph
from ..analysis_position.parse_position import get_position_data
def _get_cum_return_data_with_position(
... | --- +++ @@ -19,6 +19,15 @@ start_date=None,
end_date=None,
):
+ """
+
+ :param position:
+ :param report_normal:
+ :param label_data:
+ :param start_date:
+ :param end_date:
+ :return:
+ """
_cumulative_return_df = get_position_data(
position=position,
report_nor... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/analysis_position/cumulative_return.py |
Write docstrings describing each step |
import pandas as pd
from typing import Tuple
from qlib import get_module_logger
from qlib.utils.paral import complex_parallel, DelayedDict
from joblib import Parallel, delayed
def calc_long_short_prec(
pred: pd.Series, label: pd.Series, date_col="datetime", quantile: float = 0.2, dropna=False, is_alpha=False
) -... | --- +++ @@ -1,3 +1,8 @@+"""
+Here is a batch of evaluation functions.
+
+The interface should be redesigned carefully in the future.
+"""
import pandas as pd
from typing import Tuple
@@ -9,6 +14,30 @@ def calc_long_short_prec(
pred: pd.Series, label: pd.Series, date_col="datetime", quantile: float = 0.2, dropn... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/eva/alpha.py |
Create docstrings for each class method | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import abc
class BaseOptimizer(abc.ABC):
@abc.abstractmethod
def __call__(self, *args, **kwargs) -> object: | --- +++ @@ -5,6 +5,8 @@
class BaseOptimizer(abc.ABC):
+ """Construct portfolio with a optimization related method"""
@abc.abstractmethod
- def __call__(self, *args, **kwargs) -> object:+ def __call__(self, *args, **kwargs) -> object:
+ """Generate a optimized portfolio allocation"""
| https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/optimizer/base.py |
Document functions with clear intent | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from pathlib import Path
import warnings
import numpy as np
import pandas as pd
from typing import IO, List, Tuple, Union
from qlib.data.dataset.utils import convert_index_format
from qlib.utils import lazy_sort_index
from ...utils.resam import ... | --- +++ @@ -20,8 +20,19 @@
class TWAPStrategy(BaseStrategy):
+ """TWAP Strategy for trading
+
+ NOTE:
+ - This TWAP strategy will celling round when trading. This will make the TWAP trading strategy produce the order
+ earlier when the total trade unit of amount is less than the trading step
+... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/rule_strategy.py |
Add docstrings to existing functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
from qlib.log import TimeInspector
from qlib.contrib.report.utils import sub_fig_generator
class FeaAnalyser:
def __init__(self, dataset: pd.DataFrame):
self._dataset = dataset
with TimeInspector.logt("ca... | --- +++ @@ -1,5 +1,12 @@ # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
+"""
+This module is responsible for analysing data
+
+Assumptions
+- The analyse each feature individually
+
+"""
import pandas as pd
from qlib.log import TimeInspector
@@ -8,6 +15,24 @@
class FeaAnalyser:
def... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/data/base.py |
Document all public functions with docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import math
import importlib
from typing import Iterable
import pandas as pd
import plotly.offline as py
import plotly.graph_objs as go
from plotly.subplots import make_subplots
from plotly.figure_factory import create_distplot
class BaseGra... | --- +++ @@ -20,6 +20,18 @@ def __init__(
self, df: pd.DataFrame = None, layout: dict = None, graph_kwargs: dict = None, name_dict: dict = None, **kwargs
):
+ """
+
+ :param df:
+ :param layout:
+ :param graph_kwargs:
+ :param name_dict:
+ :param kwargs:
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/graph.py |
Create docstrings for each class method | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from copy import deepcopy
from pathlib import Path
from ruamel.yaml import YAML
from typing import List, Optional, Union
import fire
import pandas as pd
from qlib import auto_init
from qlib.log import get_module_logger
from qlib.model.ens.ensemb... | --- +++ @@ -22,6 +22,33 @@
class Rolling:
+ """
+ The motivation of Rolling Module
+ - It only focus **offlinely** turn a specific task to rollinng
+ - To make the implementation easier, following factors are ignored.
+ - The tasks is dependent (e.g. time series).
+
+ Related modules and diffe... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/rolling/base.py |
Add detailed docstrings explaining each function | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# pylint: skip-file
# flake8: noqa
import fire
import pandas as pd
import pathlib
import qlib
import logging
from ...data import D
from ...log import get_module_logger
from ...utils import get_pre_trading_date, is_tradable_date
from ..evaluate ... | --- +++ @@ -1,212 +1,320 @@-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
-
-# pylint: skip-file
-# flake8: noqa
-
-import fire
-import pandas as pd
-import pathlib
-import qlib
-import logging
-
-from ...data import D
-from ...log import get_module_logger
-from ...utils import get_pre_tradi... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/online/operator.py |
Write docstrings for utility functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from typing import Text, Union
import copy
from ...utils import get_or_create_path
from ...log import get_module_logger
import torch
imp... | --- +++ @@ -50,6 +50,12 @@ pretrain=True,
pretrain_file=None,
):
+ """
+ TabNet model for Qlib
+
+ Args:
+ ps: probability to generate the bernoulli mask
+ """
# set hyper-parameters.
self.d_feat = d_feat
self.out_dim = out_dim
@@ -351,... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_tabnet.py |
Create structured documentation for my script | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from ...backtest.position import Position
from ...backtest.exchange import Exchange
import pandas as pd
import copy
class OrderGenerator:
def generate_order_list_from_target_weight_position(
self,
current: Position,
... | --- +++ @@ -1,6 +1,9 @@ # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
+"""
+This order generator is for strategies based on WeightStrategyBase
+"""
from ...backtest.position import Position
from ...backtest.exchange import Exchange
@@ -21,10 +24,32 @@ trade_start_time: pd.Times... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/order_generator.py |
Create docstrings for API functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import pandas as pd
import lightgbm as lgb
from typing import List, Text, Tuple, Union
from ...model.base import ModelFT
from ...data.dataset import DatasetH
from ...data.dataset.handler import DataHandlerLP
from ...model.inter... | --- +++ @@ -14,6 +14,7 @@
class LGBModel(ModelFT, LightGBMFInt):
+ """LightGBM Model"""
def __init__(self, loss="mse", early_stopping_rounds=50, num_boost_round=1000, **kwargs):
if loss not in {"mse", "binary"}:
@@ -25,6 +26,10 @@ self.model = None
def _prepare_data(self, dataset: ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/gbdt.py |
Document this code for team use | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import pandas as pd
from ....backtest.profit_attribution import get_stock_weight_df
def parse_position(position: dict = None) -> pd.DataFrame:
position_weight_df = get_stock_weight_df(position)
# If the day does not exist, use the la... | --- +++ @@ -8,6 +8,28 @@
def parse_position(position: dict = None) -> pd.DataFrame:
+ """Parse position dict to position DataFrame
+
+ :param position: position data
+ :return: position DataFrame;
+
+
+ .. code-block:: python
+
+ position_df = parse_position(positions)
+ print(... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/report/analysis_position/parse_position.py |
Generate docstrings with parameter types | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from typing import Text, Union
import copy
from ...utils import get_or_create_path
from ...log import get_module_logger
import torch
i... | --- +++ @@ -1,403 +1,511 @@-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
-
-
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-import pandas as pd
-from typing import Text, Union
-import copy
-from ...utils import get_or_create_path
-from ...log ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/pytorch_krnn.py |
Add docstrings including usage examples | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# pylint: skip-file
# flake8: noqa
import pathlib
import pandas as pd
import shutil
from ruamel.yaml import YAML
from ...backtest.account import Account
from .user import User
from .utils import load_instance, save_instance
from ...utils import ... | --- +++ @@ -16,6 +16,27 @@
class UserManager:
def __init__(self, user_data_path, save_report=True):
+ """
+ This module is designed to manager the users in online system
+ all users' data were assumed to be saved in user_data_path
+ Parameter
+ user_data_path : stri... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/online/manager.py |
Add documentation for all methods | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import pandas as pd
from typing import Text, Union
from qlib.log import get_module_logger
from qlib.data.dataset.weight import Reweighter
from scipy.optimize import nnls
from sklearn.linear_model import LinearRegression, Ridge,... | --- +++ @@ -15,6 +15,15 @@
class LinearModel(Model):
+ """Linear Model
+
+ Solve one of the following regression problems:
+ - `ols`: min_w |y - Xw|^2_2
+ - `nnls`: min_w |y - Xw|^2_2, s.t. w >= 0
+ - `ridge`: min_w |y - Xw|^2_2 + \alpha*|w|^2_2
+ - `lasso`: min_w |y - Xw|^2_2 + \a... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/model/linear.py |
Add docstrings to improve code quality | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os
import copy
import warnings
import numpy as np
import pandas as pd
from typing import Dict, List, Text, Tuple, Union
from abc import ABC
from qlib.data import D
from qlib.data.dataset import Dataset
from qlib.model.base import BaseMode... | --- +++ @@ -35,6 +35,23 @@ common_infra=None,
**kwargs,
):
+ """
+ Parameters
+ -----------
+ signal :
+ the information to describe a signal. Please refer to the docs of `qlib.backtest.signal.create_signal_from`
+ the decision of the strategy will... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/contrib/strategy/signal_strategy.py |
Fully document this Python code with docstrings | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import print_function
from abc import abstractmethod
import re
import pandas as pd
import numpy as np
import abc
from .data import Cal, DatasetD
class BaseDFilter(abc.ABC):
def __init__(self):
pass
@staticmet... | --- +++ @@ -13,28 +13,86 @@
class BaseDFilter(abc.ABC):
+ """Dynamic Instruments Filter Abstract class
+
+ Users can override this class to construct their own filter
+
+ Override __init__ to input filter regulations
+
+ Override filter_main to use the regulations to filter instruments
+ """
d... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/filter.py |
Help me add docstrings to my project | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from typing import Union, List, Type
from scipy.stats import percentileofscore
from .base import Expression, ExpressionOps, Feature, P... | --- +++ @@ -35,6 +35,18 @@
#################### Element-Wise Operator ####################
class ElemOperator(ExpressionOps):
+ """Element-wise Operator
+
+ Parameters
+ ----------
+ feature : Expression
+ feature instance
+
+ Returns
+ ----------
+ Expression
+ feature operation o... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/ops.py |
Add clean documentation to messy code | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import abc
import pandas as pd
from ..log import get_module_logger
class Expression(abc.ABC):
def __str__(self):
return type(self).__name__
def __repr__(s... | --- +++ @@ -11,6 +11,17 @@
class Expression(abc.ABC):
+ """
+ Expression base class
+
+ Expression is designed to handle the calculation of data with the format below
+ data with two dimension for each instrument,
+
+ - feature
+ - time: it could be observation time or period time.
+
+ - ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/base.py |
Add docstrings to meet PEP guidelines | from abc import abstractmethod
import pandas as pd
import numpy as np
from .handler import DataHandler
from typing import Union, List
from qlib.log import get_module_logger
from .utils import get_level_index, fetch_df_by_index, fetch_df_by_col
class BaseHandlerStorage:
@abstractmethod
def fetch(
se... | --- +++ @@ -10,6 +10,11 @@
class BaseHandlerStorage:
+ """
+ Base data storage for datahandler
+ - pd.DataFrame is the default data storage format in Qlib datahandler
+ - If users want to use custom data storage, they should define subclass inherited BaseHandlerStorage, and implement the following metho... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/dataset/storage.py |
Write proper docstrings for these functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import annotations
import pandas as pd
from typing import Union, List, TYPE_CHECKING
from qlib.utils import init_instance_by_config
if TYPE_CHECKING:
from qlib.data.dataset import DataHandler
def get_level_index(df: pd.DataF... | --- +++ @@ -10,6 +10,22 @@
def get_level_index(df: pd.DataFrame, level: Union[str, int]) -> int:
+ """
+
+ get the level index of `df` given `level`
+
+ Parameters
+ ----------
+ df : pd.DataFrame
+ data
+ level : Union[str, int]
+ index level
+
+ Returns
+ -------
+ int:
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/dataset/utils.py |
Add detailed docstrings explaining each function | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import abc
from qlib.model.meta.task import MetaTask
from typing import Dict, Union, List, Tuple, Text
from ...utils.serial import Serializable
class MetaTaskDataset(Serializable, metaclass=abc.ABCMeta):
def __init__(self, segments: Union[... | --- +++ @@ -8,12 +8,56 @@
class MetaTaskDataset(Serializable, metaclass=abc.ABCMeta):
+ """
+ A dataset fetching the data in a meta-level.
+
+ A Meta Dataset is responsible for
+
+ - input tasks(e.g. Qlib tasks) and prepare meta tasks
+
+ - meta task contains more information than normal tasks (e... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/model/meta/dataset.py |
Add docstrings to existing functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import annotations
from typing import TYPE_CHECKING, Generic, Optional, TypeVar
from qlib.typehint import final
from .simulator import StateType
if TYPE_CHECKING:
from .utils.env_wrapper import EnvWrapper
__all__ = ["Aux... | --- +++ @@ -19,6 +19,7 @@
class AuxiliaryInfoCollector(Generic[StateType, AuxInfoType]):
+ """Override this class to collect customized auxiliary information from environment."""
env: Optional[EnvWrapper] = None
@@ -27,4 +28,16 @@ return self.collect(simulator_state)
def collect(self, sim... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/rl/aux_info.py |
Write proper docstrings for these functions | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from __future__ import division
from __future__ import print_function
import os
import sys
import stat
import time
import pickle
import traceback
import redis_lock
import contextlib
import abc
from pathlib import Path
import numpy as np
import ... | --- +++ @@ -42,6 +42,7 @@
class MemCacheUnit(abc.ABC):
+ """Memory Cache Unit."""
def __init__(self, *args, **kwargs):
self.size_limit = kwargs.pop("size_limit", 0)
@@ -83,6 +84,7 @@
@property
def limited(self):
+ """whether memory cache is limited"""
return self.size_l... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/cache.py |
Add docstrings following best practices | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import abc
from pathlib import Path
import warnings
import pandas as pd
from typing import Tuple, Union, List, Dict
from qlib.data import D
from qlib.utils import load_dataset, init_instance_by_config, time_to_slc_point
from qlib.utils.pickle_u... | --- +++ @@ -16,14 +16,75 @@
class DataLoader(abc.ABC):
+ """
+ DataLoader is designed for loading raw data from original data source.
+ """
@abc.abstractmethod
def load(self, instruments, start_time=None, end_time=None) -> pd.DataFrame:
+ """
+ load the data as pd.DataFrame.
+
+ ... | https://raw.githubusercontent.com/microsoft/qlib/HEAD/qlib/data/dataset/loader.py |
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