diff --git a/doc/source/templates/04_finetuning_llms_with_deepspeed/finetune_hf_llm.py b/doc/source/templates/04_finetuning_llms_with_deepspeed/finetune_hf_llm.py index 6438f7e9c1c20..91ba4f37a3c2f 100644 --- a/doc/source/templates/04_finetuning_llms_with_deepspeed/finetune_hf_llm.py +++ b/doc/source/templates/04_finetuning_llms_with_deepspeed/finetune_hf_llm.py @@ -9,7 +9,7 @@ import pandas as pd from pathlib import Path import torch.nn as nn -from ray import tune +from ray import tune # noqa: F401 import tqdm import tempfile diff --git a/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_13b.sh b/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_13b.sh index 57349ccf171e2..e868a82e912cf 100755 --- a/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_13b.sh +++ b/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_13b.sh @@ -59,6 +59,6 @@ python finetune_hf_llm.py \ --train_path ${TRAIN_PATH} \ --test_path ${TEST_PATH} \ --special_token_path ${TOKEN_PATH} \ - $additional_args + "$additional_args" echo "Process completed." diff --git a/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_70b.sh b/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_70b.sh index 922cbb957349b..ea6aa6c43490e 100755 --- a/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_70b.sh +++ b/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_70b.sh @@ -59,6 +59,6 @@ python finetune_hf_llm.py \ --train_path ${TRAIN_PATH} \ --test_path ${TEST_PATH} \ --special_token_path ${TOKEN_PATH} \ - $additional_args + "$additional_args" echo "Process completed." diff --git a/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_7b.sh b/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_7b.sh index 41ca7a2c569f1..94e9e2d8d31cf 100755 --- a/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_7b.sh +++ b/doc/source/templates/04_finetuning_llms_with_deepspeed/run_llama_7b.sh @@ -59,6 +59,6 @@ python finetune_hf_llm.py \ --train_path ${TRAIN_PATH} \ --test_path ${TEST_PATH} \ --special_token_path ${TOKEN_PATH} \ - $additional_args + "$additional_args" echo "Process completed." diff --git a/doc/source/templates/04_finetuning_llms_with_deepspeed/setup_aws.sh b/doc/source/templates/04_finetuning_llms_with_deepspeed/setup_aws.sh index 65aa0d257f7e3..8a3a1b4ae1b1c 100755 --- a/doc/source/templates/04_finetuning_llms_with_deepspeed/setup_aws.sh +++ b/doc/source/templates/04_finetuning_llms_with_deepspeed/setup_aws.sh @@ -1,2 +1,2 @@ - +#!/bin/bash python run_on_every_node.py run "awsv2 configure set s3.max_concurrent_requests 32 && awsv2 configure set default.s3.preferred_transfer_client crt && awsv2 configure set default.s3.target_bandwidth 100Gb/s && awsv2 configure set default.s3.multipart_chunksize 8MB" \ No newline at end of file diff --git a/python/ray/data/dataset.py b/python/ray/data/dataset.py index d95f0fea252c9..92ff487b7f922 100644 --- a/python/ray/data/dataset.py +++ b/python/ray/data/dataset.py @@ -1946,8 +1946,8 @@ def sum( ignore_nulls: Whether to ignore null values. If ``True``, null values are ignored when computing the sum. If ``False``, when a null value is encountered, the output is ``None``. - Ray Data considers ``np.nan``, ``None``, and ``pd.NaT`` to be null values. - Default is ``True``. + Ray Data considers ``np.nan``, ``None``, and ``pd.NaT`` to be null + values. Default is ``True``. Returns: The sum result. @@ -1988,8 +1988,8 @@ def min( ignore_nulls: Whether to ignore null values. If ``True``, null values are ignored when computing the min; if ``False``, when a null value is encountered, the output is ``None``. - This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null values. - Default is ``True``. + This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null + values. Default is ``True``. Returns: The min result. @@ -2030,8 +2030,8 @@ def max( ignore_nulls: Whether to ignore null values. If ``True``, null values are ignored when computing the max; if ``False``, when a null value is encountered, the output is ``None``. - This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null values. - Default is ``True``. + This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null + values. Default is ``True``. Returns: The max result. @@ -2072,8 +2072,8 @@ def mean( ignore_nulls: Whether to ignore null values. If ``True``, null values are ignored when computing the mean; if ``False``, when a null value is encountered, the output is ``None``. - This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null values. - Default is ``True``. + This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null + values. Default is ``True``. Returns: The mean result. @@ -2108,7 +2108,8 @@ def std( numerical stability, and is computable in a single pass. This may give different (but more accurate) results than NumPy, Pandas, and sklearn, which use a less numerically stable two-pass algorithm. - To learn more, see `the Wikapedia article `_. + To learn more, see + `the Wikapedia article `_. Examples: >>> import ray @@ -2127,8 +2128,8 @@ def std( ignore_nulls: Whether to ignore null values. If ``True``, null values are ignored when computing the std; if ``False``, when a null value is encountered, the output is ``None``. - This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null values. - Default is ``True``. + This method considers ``np.nan``, ``None``, and ``pd.NaT`` to be null + values. Default is ``True``. Returns: The standard deviation result. @@ -2144,7 +2145,7 @@ def std( If the dataset is empty, all values are null. If ``ignore_nulls`` is ``False`` and any value is null, then the output is ``None``. - """ + """ # noqa: E501 ret = self._aggregate_on(Std, on, ignore_nulls, ddof=ddof) return self._aggregate_result(ret)