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Enable intel devices CPU/XPU/HPU for python backend #245

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@yuanwu2017 yuanwu2017 commented Apr 22, 2024

What does this PR do?

Enable CPU device for python backend

Fixes # (issue)

Before submitting

  • This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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    to it if that's the case.
  • Did you make sure to update the documentation with your changes? Here are the
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    here are tips on formatting docstrings.
  • Did you write any new necessary tests?

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@OlivierDehaene OR @Narsil

@yuanwu2017 yuanwu2017 marked this pull request as draft April 23, 2024 01:17
@yuanwu2017 yuanwu2017 changed the title Enable the IPEX optimization for python backend Enable CPU device for python backend Apr 23, 2024
Signed-off-by: yuanwu <yuan.wu@intel.com>
Signed-off-by: yuanwu <yuan.wu@intel.com>
Signed-off-by: yuanwu <yuan.wu@intel.com>
Signed-off-by: yuanwu <yuan.wu@intel.com>
@yuanwu2017 yuanwu2017 marked this pull request as ready for review June 23, 2024 14:40
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@OlivierDehaene @Narsil Please help to review.

yuanwu2017 and others added 11 commits July 17, 2024 16:22
add python backend support for xlm-roberta type model
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
Signed-off-by: yuanwu <yuan.wu@intel.com>
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
Signed-off-by: Liu, Kaixuan <kaixuan.liu@intel.com>
add XPU and HPU support
@yuanwu2017 yuanwu2017 changed the title Enable CPU device for python backend Enable intel devices CPU/XPU/HPU for python backend Aug 20, 2024
kaixuanliu and others added 2 commits August 22, 2024 05:10
Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
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Yes, they are the same, except here I delete some unused python packages.

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I was asking because they seem outdated (e.g. optimum-habana == 1.12.0), probably because this PR was opened before the release of optimum-habana 1.13. Can you update this file?

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Oh, Yes. I will change it~

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Have updated. BTW, we just updated the HPU model forward side implementation(using FlashBert), can you help take another look?

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LGTM

Comment on lines 99 to 194
#[instrument(skip(self))]
pub async fn warmup_hpu(
&self,
mut max_input_length: usize,
max_token: usize,
max_bs: Option<usize>
) -> Result<(), BackendError> {
let read_env_var = |key: &str, default: usize| -> usize {
env::var(key).ok().map_or(default, |value| value.parse::<usize>().unwrap())
};
let seq_bucket_size: usize = read_env_var("PAD_SEQUENCE_TO_MULTIPLE_OF", 128);
let max_warmup_length: usize = read_env_var("MAX_WARMUP_SEQUENCE_LENGTH", 1024);

let max_batch_size = match max_bs {
Some(value) => value as usize,
None => read_env_var("MAX_WARMUP_BATCH_SIZE", 8),
};

let mut batch_sizes: Vec<usize> = powers_of_two(max_batch_size);
if let Some(&last) = batch_sizes.last() {
if last < max_batch_size {
batch_sizes.push(max_batch_size);
}
}
if max_warmup_length > max_input_length {
return Err(BackendError::Start(
format!("max_warmup_length ({max_warmup_length}) exceeds model's max_input_length ({max_input_length}), you can modify this value adding `-e MAX_WARMUP_SEQUENCE_LENGTH=<new_warmup_length>` to your Docker run command")
));
}
if seq_bucket_size > max_warmup_length {
return Err(BackendError::Start(
format!("PAD_SEQUENCE_TO_MULTIPLE_OF ({seq_bucket_size}) exceeds model's max warmup length ({max_warmup_length}), you can modify these values adding `-e PAD_SEQUENCE_TO_MULTIPLE_OF=<new_value>` or `-e MAX_WARMUP_SEQUENCE_LENGTH=<new_value> to your Docker run command`")
));
}

max_input_length = std::cmp::min(max_input_length, max_warmup_length);
let mut seq_lengths: Vec<usize> = (seq_bucket_size..max_input_length+1).step_by(seq_bucket_size as usize).collect();
if let Some(&last) = seq_lengths.last() {
if last < max_input_length {
seq_lengths.push(max_input_length);
}
}

let mut shapes: Vec<(u32, u32)> = Vec::with_capacity(batch_sizes.len() * seq_lengths.len());
for batch_size in &batch_sizes {
for seq_length in &seq_lengths {
shapes.push((*batch_size as u32, *seq_length as u32));
}
}
for shape in shapes.iter() {
let batch = self.create_warmup_batch(*shape, max_token as u32);
match &self.model_type {
ModelType::Classifier => self.predict(batch).await.map(|_| ()),
ModelType::Embedding(_) => self.embed(batch).await.map(|_| ()),
}?;
tracing::info!("finish warmup for batch: {}, length: {}", shape.0, shape.1);
}
Ok(())
}

#[instrument(skip_all)]
pub fn create_warmup_batch(
&self,
shape: (u32, u32),
max_token: u32,
) -> Batch {
let (batch_size, length) = shape;
let mut batched_input_ids = Vec::new();
let mut batched_token_type_ids = Vec::new();
let mut batched_position_ids = Vec::new();
let mut cumulative_seq_lengths = Vec::with_capacity(batch_size as usize + 1);
let mut pooled_indices = Vec::with_capacity(batch_size as usize);
cumulative_seq_lengths.push(0);
let input_ids: Vec<u32> = (0..length).map(|_| rand::thread_rng().gen_range(0..max_token)).collect();
let token_type_ids: Vec<u32> = vec![0; length as usize];
let position_ids: Vec<u32> = (0..length).collect();
let mut current_length = 0;
for batch_id in 0..batch_size {
batched_input_ids.extend(input_ids.iter().cloned());
batched_token_type_ids.extend(token_type_ids.iter().cloned());
batched_position_ids.extend(position_ids.iter().cloned());
current_length += input_ids.len();
cumulative_seq_lengths.push(current_length as u32);
pooled_indices.push(batch_id);
}
Batch {
input_ids: batched_input_ids,
token_type_ids: batched_token_type_ids,
position_ids: batched_position_ids,
cumulative_seq_lengths,
max_length: length,
pooled_indices,
raw_indices: vec![],
}
}

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Yes

kaixuanliu and others added 2 commits August 29, 2024 06:54
Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
add hpu flashBert support
Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
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The HPU-specific changes look good to me, I didn't check the rest.

kaixuanliu and others added 2 commits August 29, 2024 08:40
Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
Dockerfile-intel Outdated
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Maybe better to call this file Dockerfile-hpu since it is for Gaudi only right? To stay consistent with requirements-hpu.txt and requirements-intel.txt.

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Well, Dockerfile-intel is for all intel platform(CPU,XPU and HPU). We use build-args to separate them. And requirements-intel.txt is for CPU and XPU; requirements-hpu.txt is for HPU only.

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Ah okay, I didn't see the build-args. Thanks!

@yao-matrix
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@OlivierDehaene , could you help review? Thx

@kaixuanliu
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@OlivierDehaene , Hi, can you help review? Thx

@yao-matrix
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@OlivierDehaene , could you help review? Thx

yuanwu2017 and others added 4 commits September 19, 2024 13:41
Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
Signed-off-by: kaixuanliu <kaixuan.liu@intel.com>
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kaixuanliu commented Sep 24, 2024

@OlivierDehaene @Narsil , Can you help take a review? Thanks!
cmd line to build docker image:

#CPU 
 
docker build --build-arg PLATFORM="cpu" -f Dockerfile-intel -t tei_cpu .
#XPU    

docker build --build-arg PLATFORM="xpu" -f Dockerfile-intel -t tei_xpu .
#HPU  

docker build --build-arg PLATFORM="hpu" -f Dockerfile-intel -t tei_hpu .

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@mfuntowicz @kding1

upgrade xpu-ipex to 2.3.110
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5 participants