Hi, I've moved to Cuda 11.0 and I am getting warnings below while compiling. I just can't remember exactly, but I don't think I saw these with 10.2. I don't know if it related, but run_test.py is also failing when it comes to Distribution related tests. I can post test's log when the build is complete, if it is helpful. Thank you.

[3950/5005] Building NVCC (Device) object caffe2/CMakeF

Improve navigation of the I/O how-to by prepending a decision tree/flowchart using an image or graphviz, as suggested by @mattip.

PR #6447 adds a public API to get the maximum number of registers per thread (numba.cuda.Dispatcher.get_regs_per_thread()). There are other attributes that might be nice to provide - shared memory per block, local memory per thread, const memory usage, maximum block size.

These are all available in the FuncAttr named tuple: https://github.com/numba/numba/blob/master/numba/cuda/cudadrv/drive

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

When grouping by variable in Pivot Table, it would be nice if Group By would output an actual date for datetime variables.

E.g.:

• A mean of [2020-01-01, 2020-01-02, 2020-01-03] would output 2020-01-02.
• A median of [2020-01-01, 2020-01-02, 2020-01-03, 2020-01-03, 2020-01-04] would output 2020-01-03.
• A sum ... Don't know. Probably output a float?
• Min, max ... This one is obvious.
• Va

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 iteration methods of DataFrame objects, including

• items
• iteritems
• keys
• values

Is your feature request related to a problem? Please describe.

I am trying to drop particular indices from a dimension that doesn't have coordinates.

Following: [drop_sel() documentation](http://xarray.pydata.org/en/stable/generated/xarray.Dataset.drop_sel.html#xarray.Dataset.drop_se