NumPy is an open source library for the Python programming language, adding support for large, multidimensional arrays, and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
Streaming Datasets can't be pickled, so any interaction between them and multiprocessing results in a crash.
import transformers
from transformers import Trainer, AutoModelForCausalLM, TrainingArguments
import datasets
ds = datasets.load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True).with_format("
This is a suggestion to simplify reporting the dask version in the issue template by providing a suggested code snippet to run (in the Environment section of the issue template):
import dask; print("- Dask version:", dask.__version__)
import sys; print("- Python version:", sys.version)
Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?
https://numpy.org/doc/stable/reference/generated/numpy.corrcoef.html
https://docs.cupy.dev/en/stable/reference/generated/cupy.corrcoef.html
Seems args are different
dtype argument added in NumPy version 1.20.
1.系统环境：
2.MegEngine版本：1.6.0rc1
3.python版本：Python 3.8.10
The program stuck at net.load when I was trying to use the MegFlow. I wait for more than 10min and there is no sign of finishing it.
Wondering if this already exists? If not happy to create if valuable.
I'm looking for a mapping from the column names outputted, to the actual technical indicator it represents.
examples:
momentum_ao == "Momentum, Awesome Oscilator"
momentum_kama == "Momentum, Kaufman’s Adaptive Moving Average (KAMA)"
Can help quickly grasp what the features represent without having to refer back to do
Created by Travis Oliphant
Latest release 4 days ago
Followup to pytorch/pytorch#74955 (comment).
It turns out that that cmake version was just bad and we can now unpin cmake once again.
cc @seemethere @malfet @pytorch/pytorch-dev-infra