According to
https://github.com/pytorch/pytorch/blob/64847c7f0b3559c6edc40f001619b80c7dc68ef7/c10/util/Exception.h#L479
all usages of AT_ERROR("msg") should be replace with TORCH_CHECK(false, "msg")
There are currently 29 instances of AT_ERROR being used in c10 codebase:

$ grep AT_ERROR c10 -R|grep -v Exception.h|wc -l
29

Typing code example:

import datetime
import numpy as np
d = np.datetime64(datetime.date(2021, 3, 17))

Run mypy on file

untitled.py:3: error: No overload variant of "datetime64" matches argument type "date"  [call-overload]
untitled.py:3: note: Possible overload variant:
untitled.py:3: note:     def datetime64(self, Union[None, datetime64, Union[str, bytes]

it would be handy to have a passthrough parameter to dd.concat - currently the union_categoricals call is parameter-free:

    dtype = "category"
            if left is not None and right is not None:
                dtype = union_categoricals(
                    [left.astype("category").values, right.astype("category").values]
                ).dtype

This can be made more fle

Hello,

It seems when a cached file is saved from calling dataset.map for preprocessing, it gets the user permissions and none of the user's group permissions. As we share data files across members of our team, this is causing a bit of an issue as we have to continually reset the permission of the files. Do you know any ways around this or a way to correctly set the permissions?

(Noticed whilst reviewing #6695)

From the docs for numba.cuda.atomic.compare_and_swap:

class compare_and_swap(ary, old, val)

Conditionally assign val to the first element of an 1D array ary if the current value matches old.
Returns the current value as if it is loaded atomically.

It seem

Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?

Description

While using tokenizers.create with the model and vocab file for a custom corpus, the code throws an error and is not able to generate the BERT vocab file

Error Message

ValueError: Mismatch vocabulary! All special tokens specified must be control tokens in the sentencepiece vocabulary.

To Reproduce

from gluonnlp.data import tokenizers
tokenizers.create('spm', model_p

Implements {DataFrame,Series}.empty

hi,
if possible, please add these indicators as well:
TDI (Traders Dynamic Index)
chandelier exit
pivot points
BOP (balance of power)
CTM (Chande trend meter)
Coppock Curve
Correlation Coefficient
PMO (DecisionPoint Price Momentum Oscillator)
Ulcer Index
most of them except TDI are available on stockcharts.com
thanks