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Add cuda graphs sizes and make it default. (#1703) 

# What does this PR do?

```
text-generation-launcher --model-id XXX # Uses cuda graphs by default
text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
```
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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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guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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This commit is contained in:
Nicolas Patry 2024-04-04 23:01:56 +02:00 committed by GitHub
parent 4ee0a0c401
commit 99874eae74
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GPG Key ID: B5690EEEBB952194
6 changed files with 48 additions and 22 deletions
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9
docs/source/basic_tutorials/launcher.md
View File

@ -206,12 +206,13 @@ Options:
[env: MAX_BATCH_SIZE=]
```
## ENABLE_CUDA_GRAPHS
## CUDA_GRAPHS
```shell
--enable-cuda-graphs
Enable experimental support for cuda graphs
--cuda-graphs <CUDA_GRAPHS>
Specify the batch sizes to compute cuda graphs for. Use "0" to disable
[env: ENABLE_CUDA_GRAPHS=]
[env: CUDA_GRAPHS=]
[default: 1,2,4,8,16,32,64,96,128]
```
## HOSTNAME

1
integration-tests/conftest.py
View File

@ -383,7 +383,6 @@ def launcher(event_loop):
env = {
"LOG_LEVEL": "info,text_generation_router=debug",
"ENABLE_CUDA_GRAPHS": "true",
}
if not use_flash_attention:
env["USE_FLASH_ATTENTION"] = "false"

34
launcher/src/main.rs
View File

@ -284,9 +284,15 @@ struct Args {
#[clap(long, env)]
max_batch_size: Option<usize>,
/// Enable experimental support for cuda graphs
#[clap(long, env)]
enable_cuda_graphs: bool,
/// Specify the batch sizes to compute cuda graphs for.
/// Use "0" to disable.
#[clap(
long,
env,
value_delimiter = ',',
default_value = "1,2,4,8,16,32,64,96,128"
)]
cuda_graphs: Vec<usize>,
/// The IP address to listen on
#[clap(default_value = "0.0.0.0", long, env)]
@ -416,7 +422,7 @@ fn shard_manager(
disable_custom_kernels: bool,
watermark_gamma: Option<f32>,
watermark_delta: Option<f32>,
enable_cuda_graphs: bool,
cuda_graphs: Vec<usize>,
cuda_memory_fraction: f32,
rope_scaling: Option<RopeScaling>,
rope_factor: Option<f32>,
@ -549,8 +555,16 @@ fn shard_manager(
};
// Enable experimental support for cuda graphs
if enable_cuda_graphs {
envs.push(("ENABLE_CUDA_GRAPHS".into(), "True".into()))
if !cuda_graphs.is_empty() {
envs.push((
"CUDA_GRAPHS".into(),
cuda_graphs
.into_iter()
.map(|c| c.to_string())
.collect::<Vec<_>>()
.join(",")
.into(),
));
}
// If disable_custom_kernels is true, pass it to the shard as an env var
@ -941,7 +955,11 @@ fn spawn_shards(
let disable_custom_kernels = args.disable_custom_kernels;
let watermark_gamma = args.watermark_gamma;
let watermark_delta = args.watermark_delta;
let enable_cuda_graphs = args.enable_cuda_graphs;
let cuda_graphs: Vec<usize> = args
.cuda_graphs
.iter()
.filter_map(|&c| if c > 0 { Some(c) } else { None })
.collect();
let cuda_memory_fraction = args.cuda_memory_fraction;
let rope_scaling = args.rope_scaling;
let rope_factor = args.rope_factor;
@ -963,7 +981,7 @@ fn spawn_shards(
disable_custom_kernels,
watermark_gamma,
watermark_delta,
enable_cuda_graphs,
cuda_graphs,
cuda_memory_fraction,
rope_scaling,
rope_factor,

8
server/text_generation_server/models/flash_causal_lm.py
View File

@ -28,7 +28,7 @@ from text_generation_server.models.cache_manager import (
BLOCK_SIZE,
)
from text_generation_server.pb import generate_pb2
from text_generation_server.models.globals import MEM_POOL, ENABLE_CUDA_GRAPHS
from text_generation_server.models.globals import MEM_POOL, CUDA_GRAPHS
from text_generation_server.utils import StoppingCriteria, HeterogeneousNextTokenChooser
from text_generation_server.utils.dist import MEMORY_FRACTION
@ -798,11 +798,11 @@ class FlashCausalLM(Model):
self.device,
)
if ENABLE_CUDA_GRAPHS:
if CUDA_GRAPHS:
try:
logger.info("Experimental support for Cuda Graphs is enabled")
logger.info(f"Cuda Graphs are enabled for sizes {CUDA_GRAPHS}")
# Warmup cuda graphs
for bs in [1, 2, 4] + [8 * i for i in range(1, 9)]:
for bs in CUDA_GRAPHS:
if self.speculate is None or self.speculate + 1 <= bs:
self.cuda_graph_warmup(bs, max_s, max_bt)
except Exception:

10
server/text_generation_server/models/globals.py
View File

@ -3,4 +3,12 @@ import os
MEM_POOL = torch.cuda.graph_pool_handle()
# This is overridden by the cli
ENABLE_CUDA_GRAPHS = os.getenv("ENABLE_CUDA_GRAPHS", "false").lower() in {"1", "true"}
cuda_graphs = os.getenv("CUDA_GRAPHS")
if cuda_graphs is not None:
try:
cuda_graphs = [int(item) for item in cuda_graphs.split(",")]
except Exception as e:
raise RuntimeError(
f"Could not parse cuda graphs {cuda_graphs}, expected comma separated list for batch sizes to run on: {e}"
)
CUDA_GRAPHS = cuda_graphs

8
server/text_generation_server/models/mamba.py
View File

@ -13,7 +13,7 @@ from text_generation_server.utils import (
weight_files,
Weights,
)
from text_generation_server.models.globals import ENABLE_CUDA_GRAPHS, MEM_POOL
from text_generation_server.models.globals import CUDA_GRAPHS, MEM_POOL
import time
from text_generation_server.models.custom_modeling.mamba_modeling import (
MambaModel,
@ -465,12 +465,12 @@ class Mamba(Model):
def warmup(self, batch) -> Optional[int]:
# TODO: implement warmup for Mamba if needed
if ENABLE_CUDA_GRAPHS:
if CUDA_GRAPHS:
if self.speculate is None or self.speculate == 0:
try:
logger.info("Experimental support for Cuda Graphs is enabled")
logger.info(f"Cuda Graphs are enabled for sizes {CUDA_GRAPHS}")
# Warmup cuda graphs
for bs in [1, 2, 4] + [8 * i for i in range(1, 9)]:
for bs in CUDA_GRAPHS:
self.cuda_graph_warmup(bs)
except Exception:
logger.exception(f"Decode cuda graph warmup failed")