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 ``` <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil -->
This commit is contained in:
parent
4ee0a0c401
commit
99874eae74
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@ -206,12 +206,13 @@ Options:
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[env: MAX_BATCH_SIZE=]
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[env: MAX_BATCH_SIZE=]
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```
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```
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## ENABLE_CUDA_GRAPHS
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## CUDA_GRAPHS
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```shell
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```shell
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--enable-cuda-graphs
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--cuda-graphs <CUDA_GRAPHS>
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Enable experimental support for cuda graphs
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Specify the batch sizes to compute cuda graphs for. Use "0" to disable
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[env: ENABLE_CUDA_GRAPHS=]
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[env: CUDA_GRAPHS=]
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[default: 1,2,4,8,16,32,64,96,128]
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```
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```
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## HOSTNAME
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## HOSTNAME
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@ -383,7 +383,6 @@ def launcher(event_loop):
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env = {
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env = {
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"LOG_LEVEL": "info,text_generation_router=debug",
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"LOG_LEVEL": "info,text_generation_router=debug",
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"ENABLE_CUDA_GRAPHS": "true",
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}
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}
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if not use_flash_attention:
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if not use_flash_attention:
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env["USE_FLASH_ATTENTION"] = "false"
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env["USE_FLASH_ATTENTION"] = "false"
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@ -284,9 +284,15 @@ struct Args {
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#[clap(long, env)]
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#[clap(long, env)]
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max_batch_size: Option<usize>,
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max_batch_size: Option<usize>,
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/// Enable experimental support for cuda graphs
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/// Specify the batch sizes to compute cuda graphs for.
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#[clap(long, env)]
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/// Use "0" to disable.
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enable_cuda_graphs: bool,
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#[clap(
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long,
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env,
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value_delimiter = ',',
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default_value = "1,2,4,8,16,32,64,96,128"
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)]
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cuda_graphs: Vec<usize>,
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/// The IP address to listen on
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/// The IP address to listen on
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#[clap(default_value = "0.0.0.0", long, env)]
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#[clap(default_value = "0.0.0.0", long, env)]
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@ -416,7 +422,7 @@ fn shard_manager(
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disable_custom_kernels: bool,
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disable_custom_kernels: bool,
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watermark_gamma: Option<f32>,
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watermark_gamma: Option<f32>,
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watermark_delta: Option<f32>,
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watermark_delta: Option<f32>,
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enable_cuda_graphs: bool,
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cuda_graphs: Vec<usize>,
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cuda_memory_fraction: f32,
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cuda_memory_fraction: f32,
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rope_scaling: Option<RopeScaling>,
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rope_scaling: Option<RopeScaling>,
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rope_factor: Option<f32>,
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rope_factor: Option<f32>,
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@ -549,8 +555,16 @@ fn shard_manager(
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};
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};
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// Enable experimental support for cuda graphs
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// Enable experimental support for cuda graphs
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if enable_cuda_graphs {
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if !cuda_graphs.is_empty() {
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envs.push(("ENABLE_CUDA_GRAPHS".into(), "True".into()))
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envs.push((
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"CUDA_GRAPHS".into(),
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cuda_graphs
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.into_iter()
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.map(|c| c.to_string())
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.collect::<Vec<_>>()
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.join(",")
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.into(),
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));
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}
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}
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// If disable_custom_kernels is true, pass it to the shard as an env var
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// If disable_custom_kernels is true, pass it to the shard as an env var
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@ -941,7 +955,11 @@ fn spawn_shards(
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let disable_custom_kernels = args.disable_custom_kernels;
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let disable_custom_kernels = args.disable_custom_kernels;
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let watermark_gamma = args.watermark_gamma;
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let watermark_gamma = args.watermark_gamma;
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let watermark_delta = args.watermark_delta;
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let watermark_delta = args.watermark_delta;
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let enable_cuda_graphs = args.enable_cuda_graphs;
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let cuda_graphs: Vec<usize> = args
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.cuda_graphs
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.iter()
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.filter_map(|&c| if c > 0 { Some(c) } else { None })
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.collect();
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let cuda_memory_fraction = args.cuda_memory_fraction;
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let cuda_memory_fraction = args.cuda_memory_fraction;
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let rope_scaling = args.rope_scaling;
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let rope_scaling = args.rope_scaling;
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let rope_factor = args.rope_factor;
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let rope_factor = args.rope_factor;
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@ -963,7 +981,7 @@ fn spawn_shards(
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disable_custom_kernels,
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disable_custom_kernels,
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watermark_gamma,
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watermark_gamma,
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watermark_delta,
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watermark_delta,
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enable_cuda_graphs,
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cuda_graphs,
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cuda_memory_fraction,
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cuda_memory_fraction,
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rope_scaling,
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rope_scaling,
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rope_factor,
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rope_factor,
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@ -28,7 +28,7 @@ from text_generation_server.models.cache_manager import (
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BLOCK_SIZE,
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BLOCK_SIZE,
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)
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)
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from text_generation_server.pb import generate_pb2
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from text_generation_server.pb import generate_pb2
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from text_generation_server.models.globals import MEM_POOL, ENABLE_CUDA_GRAPHS
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from text_generation_server.models.globals import MEM_POOL, CUDA_GRAPHS
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from text_generation_server.utils import StoppingCriteria, HeterogeneousNextTokenChooser
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from text_generation_server.utils import StoppingCriteria, HeterogeneousNextTokenChooser
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from text_generation_server.utils.dist import MEMORY_FRACTION
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from text_generation_server.utils.dist import MEMORY_FRACTION
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@ -798,11 +798,11 @@ class FlashCausalLM(Model):
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self.device,
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self.device,
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)
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)
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if ENABLE_CUDA_GRAPHS:
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if CUDA_GRAPHS:
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try:
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try:
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logger.info("Experimental support for Cuda Graphs is enabled")
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logger.info(f"Cuda Graphs are enabled for sizes {CUDA_GRAPHS}")
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# Warmup cuda graphs
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# Warmup cuda graphs
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for bs in [1, 2, 4] + [8 * i for i in range(1, 9)]:
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for bs in CUDA_GRAPHS:
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if self.speculate is None or self.speculate + 1 <= bs:
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if self.speculate is None or self.speculate + 1 <= bs:
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self.cuda_graph_warmup(bs, max_s, max_bt)
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self.cuda_graph_warmup(bs, max_s, max_bt)
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except Exception:
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except Exception:
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@ -3,4 +3,12 @@ import os
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MEM_POOL = torch.cuda.graph_pool_handle()
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MEM_POOL = torch.cuda.graph_pool_handle()
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# This is overridden by the cli
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# This is overridden by the cli
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ENABLE_CUDA_GRAPHS = os.getenv("ENABLE_CUDA_GRAPHS", "false").lower() in {"1", "true"}
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cuda_graphs = os.getenv("CUDA_GRAPHS")
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if cuda_graphs is not None:
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try:
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cuda_graphs = [int(item) for item in cuda_graphs.split(",")]
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except Exception as e:
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raise RuntimeError(
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f"Could not parse cuda graphs {cuda_graphs}, expected comma separated list for batch sizes to run on: {e}"
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)
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CUDA_GRAPHS = cuda_graphs
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@ -13,7 +13,7 @@ from text_generation_server.utils import (
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weight_files,
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weight_files,
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Weights,
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Weights,
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)
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)
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from text_generation_server.models.globals import ENABLE_CUDA_GRAPHS, MEM_POOL
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from text_generation_server.models.globals import CUDA_GRAPHS, MEM_POOL
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import time
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import time
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from text_generation_server.models.custom_modeling.mamba_modeling import (
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from text_generation_server.models.custom_modeling.mamba_modeling import (
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MambaModel,
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MambaModel,
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@ -465,12 +465,12 @@ class Mamba(Model):
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def warmup(self, batch) -> Optional[int]:
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def warmup(self, batch) -> Optional[int]:
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# TODO: implement warmup for Mamba if needed
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# TODO: implement warmup for Mamba if needed
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if ENABLE_CUDA_GRAPHS:
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if CUDA_GRAPHS:
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if self.speculate is None or self.speculate == 0:
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if self.speculate is None or self.speculate == 0:
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try:
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try:
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logger.info("Experimental support for Cuda Graphs is enabled")
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logger.info(f"Cuda Graphs are enabled for sizes {CUDA_GRAPHS}")
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# Warmup cuda graphs
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# Warmup cuda graphs
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for bs in [1, 2, 4] + [8 * i for i in range(1, 9)]:
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for bs in CUDA_GRAPHS:
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self.cuda_graph_warmup(bs)
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self.cuda_graph_warmup(bs)
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except Exception:
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except Exception:
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logger.exception(f"Decode cuda graph warmup failed")
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logger.exception(f"Decode cuda graph warmup failed")
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