code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
import riemann
from riemann import utils
from riemann.tx import shared
from riemann.tx.tx import TxIn, TxOut
from riemann.tx import zcash_shared as z
from typing import cast, Optional, Sequence, Tuple
class OverwinterTx(z.ZcashByteData):
tx_ins: Tuple[TxIn, ...]
tx_outs: Tuple[TxOut, ...]
lock_time: byt... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/tx/overwinter.py | 0.756223 | 0.254243 | overwinter.py | pypi |
import riemann
from riemann import utils
from riemann.tx import shared
from riemann.tx.tx import TxIn, TxOut
from riemann.tx import zcash_shared as z
from typing import cast, Optional, Sequence, Tuple
class SproutTx(z.ZcashByteData):
tx_ins: Tuple[TxIn, ...]
tx_outs: Tuple[TxOut, ...]
lock_time: bytes
... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/tx/sprout.py | 0.761982 | 0.268306 | sprout.py | pypi |
import riemann
from riemann import utils
from riemann.tx import shared
from riemann.tx.tx import TxIn, TxOut
from riemann.tx import zcash_shared as z
from typing import cast, Optional, Sequence, Tuple
class SaplingZkproof(z.ZcashByteData):
pi_sub_a: bytes
pi_sub_b: bytes
pi_sub_c: bytes
def __init_... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/tx/sapling.py | 0.861902 | 0.27113 | sapling.py | pypi |
import riemann
from riemann import utils
from riemann.script.opcodes import CODE_TO_INT, INT_TO_CODE
def serialize(script_string: str) -> bytes:
'''
Serialize a human-readable script to bytes
Example:
serialize('OP_DUP OP_CAT OP_HASH160 0011deadbeef')
Args:
script_string: A human-rea... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/script/serialization.py | 0.710829 | 0.266572 | serialization.py | pypi |
from typing import Dict, List, Tuple
OPCODE_LIST: List[Tuple[str, int]] = [
("OP_0", 0),
("OP_PUSHDATA1", 76),
("OP_PUSHDATA2", 77),
("OP_PUSHDATA4", 78),
("OP_1NEGATE", 79),
("OP_RESERVED", 80),
("OP_1", 81),
("OP_2", 82),
("OP_3", 83),
("OP_4", 84),
("OP_5", 85),
("OP_... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/script/opcodes.py | 0.477067 | 0.238362 | opcodes.py | pypi |
from riemann.encoding import base58, bech32, cashaddr
from typing import Dict, List, Optional, Tuple
class Network:
'''
Basic Network class.
holding space for the various prefixes.
Not all features are used by all coins.
'''
SYMBOL: Optional[str] = None
NETWORK_NAME: Optional[str] = None
... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/networks/networks.py | 0.684159 | 0.234089 | networks.py | pypi |
# To add a new coin
# 1. define a class in networks.py
# 2. add it to SUPPORTED
from .networks import *
SUPPORTED = {
'bitcoin_main': BitcoinMain,
'bitcoin_test': BitcoinTest,
'bitcoin_reg': BitcoinRegtest,
'litecoin_main': LitecoinMain,
'litecoin_test': LitecoinTest,
'litecoin_reg': Litecoi... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/networks/__init__.py | 0.512205 | 0.345423 | __init__.py | pypi |
from riemann import tx
from riemann import utils as rutils
from riemann.encoding import addresses as addr
from riemann.script import serialization as ser
from riemann.script import opcodes
MAX_STANDARD_TX_WEIGHT = 400000
MIN_STANDARD_TX_NONWITNESS_SIZE = 82
def check_is_standard_tx(t: tx.Tx) -> bool:
'''
Ana... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/networks/standard.py | 0.676406 | 0.264602 | standard.py | pypi |
import riemann
CHARSET = 'qpzry9x8gf2tvdw0s3jn54khce6mua7l'
def encode(data: bytes) -> str:
'''Convert bytes to cashaddr-bech32'''
if riemann.network.CASHADDR_PREFIX is None:
raise ValueError('Network {} does not support cashaddresses.'
.format(riemann.get_current_network_n... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/encoding/cashaddr.py | 0.512693 | 0.245893 | cashaddr.py | pypi |
import riemann
CHARSET = "qpzry9x8gf2tvdw0s3jn54khce6mua7l"
def encode(data: bytes) -> str:
'''Convert bytes to bech32'''
if riemann.network.BECH32_HRP is None:
raise ValueError(
'Network ({}) does not support bech32 encoding.'
.format(riemann.get_current_network_name()))
... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/encoding/bech32.py | 0.461502 | 0.432183 | bech32.py | pypi |
from riemann import utils
from typing import Callable, Tuple
BASE58_ALPHABET = b'123456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijkmnopqrstuvwxyz'
BASE58_BASE = len(BASE58_ALPHABET)
BASE58_LOOKUP = dict((c, i) for i, c in enumerate(BASE58_ALPHABET))
def encode(data: bytes, checksum: bool = True) -> str:
'''Convert bin... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/encoding/base58.py | 0.866613 | 0.393909 | base58.py | pypi |
import riemann
from riemann import utils
from riemann.script import serialization as script_ser
def _hash_to_sh_address(
script_hash: bytes,
witness: bool = False,
cashaddr: bool = True) -> str:
'''
Turns a script hash into a SH address. Prefers Cashaddrs to legacy
addresses whenev... | /riemann-tx-2.1.0.tar.gz/riemann-tx-2.1.0/riemann/encoding/addresses.py | 0.876066 | 0.269746 | addresses.py | pypi |
import asyncio
from zeta import electrum, utils
from zeta.db import checkpoint, headers
from typing import cast, List, Optional, Union
from zeta.zeta_types import Header, ElectrumHeaderNotification, ElectrumHeader
async def sync(
outq: Optional['asyncio.Queue[Header]'] = None,
network: str = 'bitcoi... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/sync/chain.py | 0.758779 | 0.198977 | chain.py | pypi |
import os
from typing import Any, Dict, List
null = None # NB: I copied the list from elsewhere
SERVERS: Dict[str, List[Dict[str, Any]]] = {
'bitcoin_test': [
# {
# "nickname": null,
# "hostname": "testnet.qtornado.com",
# "ip_addr": null,
# "ports": [
# "s... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/electrum/servers.py | 0.455683 | 0.345519 | servers.py | pypi |
import sqlite3
from zeta import crypto
from zeta.db import connection
from riemann.encoding import addresses as addr
from typing import cast, Optional, List
from zeta.zeta_types import KeyEntry
def key_from_row(
row: sqlite3.Row,
secret_phrase: Optional[str] = None,
get_priv: bool = False) ... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/db/keys.py | 0.729616 | 0.160628 | keys.py | pypi |
import math
import sqlite3
from riemann import utils as rutils
from zeta.db import connection
from zeta.zeta_types import Header
from typing import cast, List, Optional, Tuple, Union
def header_from_row(row: sqlite3.Row) -> Header:
'''
Does what it says on the tin
'''
return cast(Header, dict((k, r... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/db/headers.py | 0.753648 | 0.479016 | headers.py | pypi |
import sqlite3
from riemann import utils as rutils
from riemann.encoding import addresses as addr
from zeta import utils
from zeta.db import connection
from zeta.zeta_types import Outpoint, Prevout, PrevoutEntry, TransactionEntry
from typing import List, Optional
def prevout_from_row(row: sqlite3.Row) -> Prevout:
... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/db/prevouts.py | 0.670932 | 0.196981 | prevouts.py | pypi |
import os
from zeta.db import connection
from zeta.zeta_types import Header
from typing import Dict, List
network: str = os.environ.get('ZETA_NETWORK', 'bitcoin_main')
CHECKPOINTS: Dict[str, List[Header]] = {
'bitcoin_main': [
{
'hash': '000000000019d6689c085ae165831e934ff763ae46a2a6... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/db/checkpoint.py | 0.487795 | 0.179279 | checkpoint.py | pypi |
import sqlite3
from riemann import utils as rutils
from riemann.encoding import addresses as addr
from riemann.script import serialization as script_ser
from zeta import crypto
from zeta.db import connection
from zeta.zeta_types import AddressEntry
from typing import cast, List, Union, Optional
def address_from_ro... | /riemann-zeta-6.0.0.tar.gz/riemann-zeta-6.0.0/zeta/db/addresses.py | 0.664758 | 0.232332 | addresses.py | pypi |
r"""
**Riemann**, a pure-Python package for computing :math:`n`-dimensional Riemann sums.
"""
from decimal import Decimal
import functools
import inspect
import itertools
from numbers import Number
import operator
import typing
@typing.runtime_checkable
class FunctionSRV(typing.Protocol):
r"""
Callable type ... | /riemann-1.0.0a2-py3-none-any.whl/riemann.py | 0.960249 | 0.817137 | riemann.py | pypi |
### how to enable ncnn vulkan capability
follow [the build and install instruction](https://github.com/Tencent/ncnn/blob/master/docs/how-to-build/how-to-build.md)
make sure you have installed vulkan sdk from [lunarg vulkan sdk website](https://vulkan.lunarg.com/sdk/home)
Usually, you can enable the vulkan compute in... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/docs/how-to-use-and-FAQ/FAQ-ncnn-vulkan.md | 0.44553 | 0.794185 | FAQ-ncnn-vulkan.md | pypi |
### caffemodel should be row-major
`caffe2ncnn` tool assumes the caffemodel is row-major (produced by c++ caffe train command).
The kernel 3x3 weights should be stored as
```
a b c
d e f
g h i
```
However, matlab caffe produced col-major caffemodel.
You have to transpose all the kernel weights by yourself or re-tra... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/docs/how-to-use-and-FAQ/FAQ-ncnn-produce-wrong-result.md | 0.659624 | 0.885928 | FAQ-ncnn-produce-wrong-result.md | pypi |
# implement elementwise addition with/without broadcast using BinaryOp operation
* input must be fp32 storage without packing
* output is expected to be fp32 storage without packing
```cpp
void binary_add(const ncnn::Mat& a, const ncnn::Mat& b, ncnn::Mat& c)
{
ncnn::Option opt;
opt.num_threads = 2;
opt.us... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/docs/developer-guide/low-level-operation-api.md | 0.559892 | 0.655384 | low-level-operation-api.md | pypi |
|operation|param id|param phase|default value|weight order|
|:---:|:---:|:---:|:---:|:---:|
|AbsVal|||
|ArgMax|0|out_max_val|0|
||1|topk|1|
|BatchNorm|0|channels|0|slope mean variance bias|
||1|eps|0.f|
|Bias|0|bias_data_size|0|
|BinaryOp|0|op_type|0|
||1|with_scalar|0|
||2|b|0.f|
|BNLL|||
|Cast|0|type_from|0|
||1|typ... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/docs/developer-guide/operation-param-weight-table.md | 0.833596 | 0.776411 | operation-param-weight-table.md | pypi |
* [AbsVal](#absval)
* [ArgMax](#argmax)
* [BatchNorm](#batchnorm)
* [Bias](#bias)
* [BinaryOp](#binaryop)
* [BNLL](#bnll)
* [Cast](#cast)
* [Clip](#clip)
* [Concat](#concat)
* [Convolution](#convolution)
* [Convolution1D](#convolution1d)
* [Convolution3D](#convolution3d)
* [ConvolutionDepthWise](#convolutiondepthwise)... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/docs/developer-guide/operators.md | 0.547464 | 0.975225 | operators.md | pypi |
.. figure:: https://github.com/pybind/pybind11/raw/master/docs/pybind11-logo.png
:alt: pybind11 logo
**pybind11 — Seamless operability between C++11 and Python**
|Latest Documentation Status| |Stable Documentation Status| |Gitter chat| |GitHub Discussions| |CI| |Build status|
|Repology| |PyPI package| |Conda-forg... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/pybind11/README.rst | 0.922478 | 0.822011 | README.rst | pypi |
import numpy as np
def xywh2xyxy(x):
# Convert nx4 boxes from [x, y, w, h] to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
y = np.zeros_like(x)
y[:, 0] = x[:, 0] - x[:, 2] / 2 # top left x
y[:, 1] = x[:, 1] - x[:, 3] / 2 # top left y
y[:, 2] = x[:, 0] + x[:, 2] / 2 # bottom right x
... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/utils/functional.py | 0.921394 | 0.821975 | functional.py | pypi |
import os
import hashlib
import requests
from tqdm import tqdm
def check_sha1(filename, sha1_hash):
"""Check whether the sha1 hash of the file content matches the expected hash.
Parameters
----------
filename : str
Path to the file.
sha1_hash : str
Expected sha1 hash in hexadecimal... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/utils/download.py | 0.696062 | 0.314024 | download.py | pypi |
from math import sqrt
import numpy as np
import cv2
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
from ..utils.functional import sigmoid, nms
class Yolact:
def __init__(
self,
target_size=550,
confidence_threshold=0.05,
nms_threshold... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/yolact.py | 0.726037 | 0.244961 | yolact.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class YoloV4_Base:
def __init__(self, tiny, target_size, num_threads=1, use_gpu=False):
self.target_size = target_size
self.num_threads = num_threads
self.use_gpu = use_gpu
self.mean_val... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/yolov4.py | 0.654895 | 0.247828 | yolov4.py | pypi |
import numpy as np
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
def clamp(v, lo, hi):
if v < lo:
return lo
elif hi < v:
return hi
else:
return v
class MobileNetV3_SSDLite:
def __init__(self, target_size=300, num_threads=1, use... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/mobilenetv3ssdlite.py | 0.643329 | 0.300962 | mobilenetv3ssdlite.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class PeleeNet_SSD:
def __init__(self, target_size=304, num_threads=1, use_gpu=False):
self.target_size = target_size
self.num_threads = num_threads
self.use_gpu = use_gpu
self.mean_vals... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/peleenetssd.py | 0.556641 | 0.264198 | peleenetssd.py | pypi |
"""Model store which provides pretrained models."""
from __future__ import print_function
__all__ = ["get_model_file", "purge"]
import os
import zipfile
import logging
import portalocker
from ..utils import download, check_sha1
_model_sha1 = {
name: checksum
for checksum, name in [
("4ff279e78cdb0b... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/model_store.py | 0.674479 | 0.179351 | model_store.py | pypi |
import numpy as np
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class Faster_RCNN:
def __init__(
self,
img_width=600,
img_height=600,
num_threads=1,
use_gpu=False,
max_per_image=100,
confidence_thresh=0.05,
... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/fasterrcnn.py | 0.632049 | 0.205475 | fasterrcnn.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class MobileNet_SSD:
def __init__(self, target_size=300, num_threads=1, use_gpu=False):
self.target_size = target_size
self.num_threads = num_threads
self.use_gpu = use_gpu
self.mean_val... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/mobilenetssd.py | 0.523664 | 0.258993 | mobilenetssd.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class SqueezeNet_SSD:
def __init__(self, target_size=300, num_threads=1, use_gpu=False):
self.target_size = target_size
self.num_threads = num_threads
self.use_gpu = use_gpu
self.mean_va... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/squeezenetssd.py | 0.527317 | 0.264952 | squeezenetssd.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class MobileNet_YoloV2:
def __init__(self, target_size=416, num_threads=1, use_gpu=False):
self.target_size = target_size
self.num_threads = num_threads
self.use_gpu = use_gpu
self.mean_... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/yolov2.py | 0.635788 | 0.262369 | yolov2.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class MobileNetV2_YoloV3:
def __init__(self, target_size=352, num_threads=1, use_gpu=False):
self.target_size = target_size
self.num_threads = num_threads
self.use_gpu = use_gpu
self.mea... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/yolov3.py | 0.521471 | 0.263884 | yolov3.py | pypi |
import time
import numpy as np
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
from ..utils.functional import *
import cv2
class NanoDet:
def __init__(
self,
target_size=320,
prob_threshold=0.4,
nms_threshold=0.3,
num_threads=1... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/nanodet.py | 0.645567 | 0.212579 | nanodet.py | pypi |
import numpy as np
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class RFCN:
def __init__(
self,
target_size=224,
max_per_image=100,
confidence_thresh=0.6,
nms_threshold=0.3,
num_threads=1,
use_gpu=False,
... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/rfcn.py | 0.680242 | 0.242026 | rfcn.py | pypi |
import numpy as np
import ncnn
from .model_store import get_model_file
from ..utils.objects import Point, Face_Object
class RetinaFace:
def __init__(
self, prob_threshold=0.8, nms_threshold=0.4, num_threads=1, use_gpu=False
):
self.prob_threshold = prob_threshold
self.nms_threshold = ... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/retinaface.py | 0.765243 | 0.245334 | retinaface.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import Detect_Object
class Noop(ncnn.Layer):
pass
def Noop_layer_creator():
return Noop()
class MobileNetV2_SSDLite:
def __init__(self, target_size=300, num_threads=1, use_gpu=False):
self.target_size = target_size
... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/mobilenetv2ssdlite.py | 0.625438 | 0.280296 | mobilenetv2ssdlite.py | pypi |
import ncnn
from .model_store import get_model_file
from ..utils.objects import KeyPoint
class SimplePose:
def __init__(
self, target_width=192, target_height=256, num_threads=1, use_gpu=False
):
self.target_width = target_width
self.target_height = target_height
self.num_thre... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/python/ncnn/model_zoo/simplepose.py | 0.632503 | 0.15704 | simplepose.py | pypi |
# PNNX
PyTorch Neural Network eXchange(PNNX) is an open standard for PyTorch model interoperability. PNNX provides an open model format for PyTorch. It defines computation graph as well as high level operators strictly matches PyTorch.
# Rationale
PyTorch is currently one of the most popular machine learning framework... | /rife-ncnn-vulkan-python-1.2.1.tar.gz/rife-ncnn-vulkan-python-1.2.1/rife_ncnn_vulkan_python/rife-ncnn-vulkan/src/ncnn/tools/pnnx/README.md | 0.809464 | 0.983769 | README.md | pypi |
import base64
from random import randbytes
from time import time
from rift.fift.fift import Fift
from rift.fift.types.cell import Cell
from rift.fift.types.factory import Factory
from rift.fift.types.null import Null
from rift.fift.types.tuple import Tuple
from rift.fift.types.util import create_entry
from rift.fift.u... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/fift/tvm.py | 0.430985 | 0.252782 | tvm.py | pypi |
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from rift.fift.types.cell import Cell
from rift.fift.types.tuple import Tuple
from rift.fift.types._fift_base import _FiftBaseType
from rift.fift.types.factory import Factory
from rift.util import type_id
class Slice(_FiftBaseType):
__type_id__ = type_i... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/fift/types/slice.py | 0.68784 | 0.348922 | slice.py | pypi |
import base64
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from rift.fift.types.slice import Slice
from rift.fift.types.builder import Builder
from rift.fift.types.int import Int
from rift.fift.types.bytes import Bytes
from rift.fift.types._fift_base import _FiftBaseType
from rift.fift.types.fac... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/fift/types/cell.py | 0.72331 | 0.24243 | cell.py | pypi |
from typing import TYPE_CHECKING, Union
from rift.fift.types.dict import Dict
if TYPE_CHECKING:
from rift.fift.types.slice import Slice
from rift.fift.types.builder import Builder
from rift.fift.types.int import Int
class GDict(Dict):
def __init__(self, __value__=None, __g_id__=None):
super(... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/fift/types/gdict.py | 0.748168 | 0.160463 | gdict.py | pypi |
from rift.ast.ref_table import ReferenceTable
from rift.ast.types import (
AsmMethod,
Contract,
IfFlow,
Method,
Node,
Statement,
WhileLoop,
)
class CallStacks(object):
"""Class responsible for tracking the calls."""
contracts = {}
current_contract: Contract = None
current_... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/ast/calls.py | 0.649579 | 0.196884 | calls.py | pypi |
from rift.ast.ref_table import ReferenceTable
class Expr:
EXPR_AR2 = 0
EXPR_CALL = 1
EXPR_FUNC = 2
EXPR_AR1 = 3
EXPR_VAR = 4
EXPR_CONST = 5
def __init__(self, type, *args, annotations=None):
self.type = type
self.args = args
self.annotations = annotations
i... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/ast/types/expr.py | 0.619241 | 0.532121 | expr.py | pypi |
from rift.ast.printer import Printer
from rift.ast.types.block import Block
from rift.ast.types.node import Node
from rift.ast.types.statement import Statement
from rift.ast.utils import _type_name
class Method(Node):
active_statement: list[Statement] = []
block: Block
def __init__(self, name, args, anno... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/ast/types/method.py | 0.445047 | 0.199483 | method.py | pypi |
import ast
from typing import Any
class IfPatcher(ast.NodeTransformer):
_counter = 0
"""Transforms the AST to handle conditions."""
def visit_If(self, node: ast.If) -> Any:
# WHY?: This causes visitor to visit all children too,
# otherwise we had to visit manually
self.generic_vis... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/ast/patchers/if_patcher.py | 0.657868 | 0.197832 | if_patcher.py | pypi |
import ast
from copy import deepcopy
from typing import Any
class AssignPatcher(ast.NodeTransformer):
"""Transforms the AST to capture assginments."""
def visit_Assign(self, node):
tg = node.targets[0]
if isinstance(tg, ast.Tuple):
node.targets = [
ast.Name(
... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/ast/patchers/assign_patcher.py | 0.599016 | 0.25682 | assign_patcher.py | pypi |
import re
from os import getcwd, path
from tomlkit import parse
class ContractConfig:
name: str | None
contract: str
tests: list[str]
deploy: str | None
def get_file_name(self) -> str:
name = self.name
if name is None:
name = self.contract
# CamelCase -> s... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/cli/config.py | 0.503418 | 0.167695 | config.py | pypi |
from typing import Type, TypeVar
from rift.core.annots import impure, is_method, method
from rift.core.invokable import InvokableFunc
from rift.fift.contract import ExecutableContract
from rift.fift.types.cell import Cell as FiftCell
from rift.func.meta_contract import ContractMeta
from rift.func.types.types import Ce... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/func/contract.py | 0.797517 | 0.206554 | contract.py | pypi |
from rift.ast.types import Expr
from rift.core import Entity
from rift.core.factory import Factory
from rift.core.utils import init_abstract_type
from rift.func.types.builder_base import _BuilderBase
from rift.func.types.cell_base import _CellBase
from rift.func.types.cont_base import _ContBase
from rift.func.types.dic... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/func/types/types.py | 0.681303 | 0.158337 | types.py | pypi |
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from rift.func.types.types import Slice, Cell, UDict, Builder
from rift.core.invokable import typed_invokable
from rift.func.types.dict_base import _DictBase
class _UDictBase(_DictBase):
@typed_invokable(name="udict_set_ref")
def set_ref(self, key_len: ... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/func/types/udict_base.py | 0.701406 | 0.213398 | udict_base.py | pypi |
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from rift.func.types.types import (
Slice,
Cont,
Cell,
Tuple,
Dict,
IDict,
UDict,
PfxDict,
)
from rift.core.invokable import typed_invokable
from rift.func.types.entity_base import _EntityBase
... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/func/types/slice_base.py | 0.747063 | 0.344333 | slice_base.py | pypi |
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from rift.core import Entity
from rift.func.types.types import Slice, Dict, Builder
from rift.core.invokable import typed_invokable
from rift.func.types.cell_base import _CellBase
class _DictBase(_CellBase):
@typed_invokable(name="dict_set")
def dic... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/func/types/dict_base.py | 0.75274 | 0.24663 | dict_base.py | pypi |
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from rift.func.types.types import Slice, Cell, IDict, Builder
from rift.core.invokable import typed_invokable
from rift.func.types.dict_base import _DictBase
class _IDictBase(_DictBase):
@typed_invokable(name="idict_set_ref")
def set_ref(self, key_len: ... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/func/types/idict_base.py | 0.671255 | 0.238628 | idict_base.py | pypi |
from rift.core.annots import asm, impure
from rift.core.entity import Entity
from rift.func.library import Library
from rift.func.types.types import Builder, Cell, Cont, Slice, Tuple
# noinspection PyTypeChecker,SpellCheckingInspection,PyUnusedLocal
class Stdlib(Library):
__ignore__ = True
@asm(hide=True)
... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/library/std.py | 0.631026 | 0.296193 | std.py | pypi |
from rift.ast import CallStacks
from rift.ast.types import Expr, Node, Statement
from rift.core.factory import Factory
from rift.core.invokable import Invokable
from rift.core.mark import mark
class Entity(Node):
__magic__ = 0x050794
N_ID = 0
def __init__(self, data=None, name=None) -> None:
supe... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/core/entity.py | 0.467332 | 0.223282 | entity.py | pypi |
from typing import TYPE_CHECKING
from rift.core import Entity
from rift.fift.types._fift_base import _FiftBaseType
from rift.logging import log_system
from rift.runtime.config import Config
from rift.types.bases import Builder, Cell, Slice
from rift.types.utils import CachingSubscriptable
from rift.util.type_id import... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/types/ref.py | 0.78789 | 0.159185 | ref.py | pypi |
from rift.core import Entity
from rift.fift.fift import Fift
from rift.library import std
from rift.logging import log_system
from rift.runtime.config import Config
from rift.types.bases import Builder, Cell, Int, Slice, String
from rift.types.int_aliases import int8, integer, uint256
from rift.types.maybe import Maybe... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/types/addr.py | 0.508544 | 0.201322 | addr.py | pypi |
from copy import deepcopy
from rift.types.addr import MsgAddress
from rift.types.bases import Cell, Dict
from rift.types.bool import Bool
from rift.types.coin import Coin
from rift.types.either import Either
from rift.types.either_ref import EitherRef
from rift.types.int_aliases import uint5, uint32, uint64
from rift.... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/types/msg.py | 0.587943 | 0.277085 | msg.py | pypi |
from rift.core.entity import Entity
from rift.library.std import std
from rift.runtime.config import Config
from rift.types.bases import Builder
class Model:
__magic__ = 0xBB10C0
_pointer: int
_skipped_ones: dict[str, Entity]
def __init__(self, **kwargs):
self.annotations = self.__annotations... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/types/model.py | 0.578329 | 0.163947 | model.py | pypi |
from rift.core import Entity
from rift.core.condition import Cond
from rift.library import std
from rift.logging import log_system
from rift.runtime.config import Config
from rift.types.bases import Builder, Cell, Slice
from rift.types.ref import Ref
from rift.types.type_helper import type_matches
from rift.types.utils... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/types/either_ref.py | 0.531209 | 0.197503 | either_ref.py | pypi |
from typing import TYPE_CHECKING
from rift.fift.types.slice import Slice as FiftSlice
from rift.func.types.types import Slice as FunCSlice
from rift.meta.behaviors import stub
if TYPE_CHECKING:
from rift.func.types.types import Cont, Tuple
from rift.types.bases.cell import Cell
class Slice(FunCSlice + FiftS... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/types/bases/slice.py | 0.721939 | 0.467818 | slice.py | pypi |
words = [
"abandon",
"ability",
"able",
"about",
"above",
"absent",
"absorb",
"abstract",
"absurd",
"abuse",
"access",
"accident",
"account",
"accuse",
"achieve",
"acid",
"acoustic",
"acquire",
"across",
"act",
"action",
"actor",
... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/keys/mnemonic/bip39/english.py | 0.45302 | 0.597784 | english.py | pypi |
import base64
import json
import os
from hashlib import sha256
from os import path
from typing import Union
from cryptography.fernet import Fernet
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
from rift.fift.types.builder import Builder
from rift.fi... | /rift_framework-1.0.0rc1-py3-none-any.whl/rift/runtime/keystore.py | 0.575469 | 0.182098 | keystore.py | pypi |
import codecs
import json
from hashlib import sha256
from math import ceil
from bitarray import bitarray
from crcset import crc32c
reach_boc_magic_prefix = b"\xB5\xEE\x9C\x72"
lean_boc_magic_prefix = b"\x68\xff\x65\xf3"
lean_boc_magic_prefix_crc = b"\xac\xc3\xa7\x28"
class CellData:
def __init__(self, max_lengt... | /rift-tonlib-0.0.3.tar.gz/rift-tonlib-0.0.3/rift_tonlib/types/cell.py | 0.503662 | 0.234385 | cell.py | pypi |
import codecs
from .cell import Slice, deserialize_boc, deserialize_cell_from_json
def render_tvm_element(element_type, element):
if element_type in ["num", "number", "int"]:
element = str(int(str(element), 0))
return {
"@type": "tvm.stackEntryNumber",
"number": {"@type": ... | /rift-tonlib-0.0.3.tar.gz/rift-tonlib-0.0.3/rift_tonlib/types/stack_utils.py | 0.425367 | 0.535766 | stack_utils.py | pypi |
import asyncio
import base64
import codecs
import functools
import logging
import struct
from functools import wraps
from crcset import crc16xmodem
logger = logging.getLogger(__name__)
def b64str_to_bytes(b64str):
b64bytes = codecs.encode(b64str, "utf8")
return codecs.decode(b64bytes, "base64")
def b64st... | /rift-tonlib-0.0.3.tar.gz/rift-tonlib-0.0.3/rift_tonlib/utils/common.py | 0.499512 | 0.286568 | common.py | pypi |
import codecs
import json
import math
from hashlib import sha256
from bitarray import bitarray
from bitarray.util import ba2hex, ba2int
from rift_tonlib.types.cell import Cell, deserialize_boc
from rift_tonlib.types.dict_utils import parse_hashmap
class Slice:
def __init__(self, cell: Cell):
self._data =... | /rift-tonlib-0.0.3.tar.gz/rift-tonlib-0.0.3/rift_tonlib/utils/tlb.py | 0.425725 | 0.349921 | tlb.py | pypi |
from rift_tonlib.utils.address import detect_address
from rift_tonlib.utils.tlb import MsgAddress, MsgAddressInt, TokenData, parse_tlb_object
def read_stack_num(entry: list):
assert entry[0] == "num"
return int(entry[1], 16)
def read_stack_cell(entry: list):
assert entry[0] == "cell"
return entry[1]... | /rift-tonlib-0.0.3.tar.gz/rift-tonlib-0.0.3/rift_tonlib/utils/tokens.py | 0.610802 | 0.475179 | tokens.py | pypi |
from six import iteritems
class Style(object):
"""Defines the style of a polygon to be drawn.
Thie Style object defines a set of Cairo drawing parameters (see
:py:meth:`.FIELDS`) for the drawing of certain elements in Rig P&R Diagram
diagrams. For example, :py:class:`.Style`s are used to define ho... | /rig-par-diagram-0.0.4.tar.gz/rig-par-diagram-0.0.4/rig_par_diagram/style.py | 0.93402 | 0.654384 | style.py | pypi |
import argparse
import pickle
import sys
import time
from importlib import import_module
import logging
import cairocffi as cairo
from rig.machine import Machine, Links, Cores
from rig.place_and_route.constraints import ReserveResourceConstraint
from rig_par_diagram import \
Diagram, \
default_chip_sty... | /rig-par-diagram-0.0.4.tar.gz/rig-par-diagram-0.0.4/rig_par_diagram/cli.py | 0.419291 | 0.213931 | cli.py | pypi |
from Queue import Queue, Empty, Full
import logging
from rig_remote.constants import QUEUE_MAX_SIZE
# logging configuration
logger = logging.getLogger(__name__)
class QueueComms (object):
def __init__(self):
"""Queue instantiation. The queues are used for handling the
communication between thread... | /rig-remote-2.0.tar.gz/rig-remote-2.0/rig_remote/queue_comms.py | 0.686685 | 0.222299 | queue_comms.py | pypi |
import csv
import logging
import os.path
from rig_remote.exceptions import InvalidPathError
from rig_remote.constants import BM
from rig_remote.constants import LOG_FILE_NAME
import datetime
import time
# logging configuration
logger = logging.getLogger(__name__)
class IO(object):
"""IO wrapper class
"""
... | /rig-remote-2.0.tar.gz/rig-remote-2.0/rig_remote/disk_io.py | 0.466116 | 0.174024 | disk_io.py | pypi |
# SPDX-License-Identifier: MIT
# Copyright © 2021 André Santos
PREDICATE_GRAMMAR = r"""
predicate: "{" condition "}"
top_level_condition: condition
condition: [condition IF_OPERATOR] disjunction
disjunction: [disjunction OR_OPERATOR] conjunction
conjunction: [conjunction AND_OPERATOR] _logic_expr
_logic_expr: ne... | /rigel-hpl-0.1.0.tar.gz/rigel-hpl-0.1.0/src/hpl/grammar.py | 0.580233 | 0.175803 | grammar.py | pypi |
from .ast import (
HplArrayAccess,
HplAstObject,
HplBinaryOperator,
HplContradiction,
HplEvent,
HplEventDisjunction,
HplExpression,
HplFieldAccess,
HplFunctionCall,
HplLiteral,
HplPattern,
HplPredicate,
HplProperty,
HplQuantifier,
HplRange,
HplScope,
H... | /rigel-hpl-0.1.0.tar.gz/rigel-hpl-0.1.0/src/hpl/visitor.py | 0.677261 | 0.560012 | visitor.py | pypi |
import docker
import uuid
from rigelcore.clients import (
DockerClient,
ROSBridgeClient
)
from rigelcore.loggers import MessageLogger
from rigelcore.simulations.requirements import SimulationRequirementsManager
from pydantic import BaseModel, PrivateAttr
from typing import Any, Dict, List, Optional
class ROSP... | /rigel_local_simulation_plugin-0.1.2.tar.gz/rigel_local_simulation_plugin-0.1.2/rigel_local_simulation_plugin/plugin.py | 0.861261 | 0.335324 | plugin.py | pypi |
import os
from pydantic import BaseModel, PrivateAttr
from rigelcore.clients import DockerClient
from rigelcore.exceptions import UndeclaredEnvironmentVariableError
from rigelcore.loggers import MessageLogger
from typing import Any
class GenericCredentials(BaseModel):
"""
Pair of login credentials to be used ... | /rigel_registry_plugin-0.1.6.tar.gz/rigel_registry_plugin-0.1.6/rigel_registry_plugin/registries/generic.py | 0.786664 | 0.170439 | generic.py | pypi |
from typing import Any, Dict, List, Optional, Type
import gym
import torch as th
from torch import nn
from stable_baselines3.common.policies import BasePolicy
from stable_baselines3.common.torch_layers import (
BaseFeaturesExtractor,
CombinedExtractor,
FlattenExtractor,
NatureCNN,
create_mlp,
)
fr... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/dqn/policies.py | 0.966068 | 0.517083 | policies.py | pypi |
import warnings
from typing import Any, Dict, List, Optional, Tuple, Type, Union
import gym
import numpy as np
import torch as th
from torch.nn import functional as F
from stable_baselines3.common.buffers import ReplayBuffer
from stable_baselines3.common.off_policy_algorithm import OffPolicyAlgorithm
from stable_base... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/dqn/dqn.py | 0.930899 | 0.590071 | dqn.py | pypi |
from typing import Any, Dict, Optional, Tuple, Type, Union
import torch as th
from stable_baselines3.common.buffers import ReplayBuffer
from stable_baselines3.common.noise import ActionNoise
from stable_baselines3.common.off_policy_algorithm import OffPolicyAlgorithm
from stable_baselines3.common.type_aliases import ... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/ddpg/ddpg.py | 0.92853 | 0.602909 | ddpg.py | pypi |
import warnings
from typing import Any, Dict, Optional, Type, Union
import numpy as np
import torch as th
from gym import spaces
from torch.nn import functional as F
from stable_baselines3.common.on_policy_algorithm import OnPolicyAlgorithm
from stable_baselines3.common.policies import ActorCriticCnnPolicy, ActorCrit... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/ppo/ppo.py | 0.933537 | 0.575827 | ppo.py | pypi |
from typing import Any, Dict, Optional, Type, Union
import torch as th
from gym import spaces
from torch.nn import functional as F
from stable_baselines3.common.on_policy_algorithm import OnPolicyAlgorithm
from stable_baselines3.common.policies import ActorCriticCnnPolicy, ActorCriticPolicy, BasePolicy, MultiInputAct... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/a2c/a2c.py | 0.967349 | 0.484014 | a2c.py | pypi |
from typing import Any, Dict, List, Optional, Tuple, Type, Union
import gym
import numpy as np
import torch as th
from torch.nn import functional as F
from stable_baselines3.common.buffers import ReplayBuffer
from stable_baselines3.common.noise import ActionNoise
from stable_baselines3.common.off_policy_algorithm imp... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/td3/td3.py | 0.954827 | 0.651715 | td3.py | pypi |
import warnings
from typing import Union
import gym
import numpy as np
from gym import spaces
from stable_baselines3.common.preprocessing import is_image_space_channels_first
from stable_baselines3.common.vec_env import DummyVecEnv, VecCheckNan
def _is_numpy_array_space(space: spaces.Space) -> bool:
"""
Ret... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/env_checker.py | 0.940817 | 0.687525 | env_checker.py | pypi |
import io
import pathlib
import time
import warnings
from copy import deepcopy
from typing import Any, Dict, List, Optional, Tuple, Type, Union
import gym
import numpy as np
import torch as th
from stable_baselines3.common.base_class import BaseAlgorithm
from stable_baselines3.common.buffers import DictReplayBuffer, ... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/off_policy_algorithm.py | 0.876463 | 0.469095 | off_policy_algorithm.py | pypi |
import copy
from abc import ABC, abstractmethod
from typing import Iterable, List, Optional
import numpy as np
class ActionNoise(ABC):
"""
The action noise base class
"""
def __init__(self):
super().__init__()
def reset(self) -> None:
"""
call end of episode reset for th... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/noise.py | 0.920923 | 0.625581 | noise.py | pypi |
import warnings
from typing import Dict, Tuple, Union
import numpy as np
import torch as th
from gym import spaces
from torch.nn import functional as F
def is_image_space_channels_first(observation_space: spaces.Box) -> bool:
"""
Check if an image observation space (see ``is_image_space``)
is channels-fi... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/preprocessing.py | 0.936183 | 0.713694 | preprocessing.py | pypi |
import time
from typing import Any, Dict, List, Optional, Tuple, Type, Union
import gym
import numpy as np
import torch as th
from stable_baselines3.common.base_class import BaseAlgorithm
from stable_baselines3.common.buffers import DictRolloutBuffer, RolloutBuffer
from stable_baselines3.common.callbacks import BaseC... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/on_policy_algorithm.py | 0.938794 | 0.448909 | on_policy_algorithm.py | pypi |
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional, Tuple, Union
import gym
import torch as th
from gym import spaces
from torch import nn
from torch.distributions import Bernoulli, Categorical, Normal
from stable_baselines3.common.preprocessing import get_action_dim
class Distributio... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/distributions.py | 0.948953 | 0.643875 | distributions.py | pypi |
import os
from typing import Any, Callable, Dict, Optional, Type, Union
import gym
from stable_baselines3.common.atari_wrappers import AtariWrapper
from stable_baselines3.common.monitor import Monitor
from stable_baselines3.common.vec_env import DummyVecEnv, SubprocVecEnv, VecEnv
def unwrap_wrapper(env: gym.Env, wr... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/env_util.py | 0.863852 | 0.341583 | env_util.py | pypi |
import warnings
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import gym
import numpy as np
from stable_baselines3.common import base_class
from stable_baselines3.common.vec_env import DummyVecEnv, VecEnv, VecMonitor, is_vecenv_wrapped
def evaluate_policy(
model: "base_class.BaseAlgorithm... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/evaluation.py | 0.921329 | 0.601242 | evaluation.py | pypi |
__all__ = ["Monitor", "ResultsWriter", "get_monitor_files", "load_results"]
import csv
import json
import os
import time
from glob import glob
from typing import Dict, List, Optional, Tuple, Union
import gym
import numpy as np
import pandas
from stable_baselines3.common.type_aliases import GymObs, GymStepReturn
cl... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/monitor.py | 0.825801 | 0.291535 | monitor.py | pypi |
from itertools import zip_longest
from typing import Dict, List, Tuple, Type, Union
import gym
import torch as th
from torch import nn
from stable_baselines3.common.preprocessing import get_flattened_obs_dim, is_image_space
from stable_baselines3.common.type_aliases import TensorDict
from stable_baselines3.common.uti... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/torch_layers.py | 0.93133 | 0.717829 | torch_layers.py | pypi |
from typing import Tuple, Union
import numpy as np
class RunningMeanStd:
def __init__(self, epsilon: float = 1e-4, shape: Tuple[int, ...] = ()):
"""
Calulates the running mean and std of a data stream
https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Parallel_algorithm
... | /rigged_sb3-0.0.1-py3-none-any.whl/stable_baselines3/common/running_mean_std.py | 0.95321 | 0.626467 | running_mean_std.py | pypi |
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