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https://github.com/huggingface/text-generation-inference.git
synced 2025-09-11 12:24:53 +00:00
Attempting to reduces the issues (workarounds for now).
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ca8a115adc
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@ -6,6 +6,7 @@ def flash_phi35_moe_handle(launcher):
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with launcher(
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"microsoft/Phi-3.5-MoE-instruct",
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num_shard=4,
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max_batch_prefill_tokens=10000,
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) as handle:
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yield handle
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@ -4,7 +4,10 @@ import asyncio
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@pytest.fixture(scope="module")
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def mllama_handle(launcher):
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with launcher("meta-llama/Llama-3.2-11B-Vision-Instruct", num_shard=2) as handle:
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with launcher(
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"meta-llama/Llama-3.2-11B-Vision-Instruct",
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num_shard=2,
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) as handle:
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yield handle
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@ -75,7 +78,9 @@ async def test_mllama_load(mllama, generate_load, response_snapshot):
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},
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],
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)
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for i in range(4)
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# TODO with v3, 4 breaks here. Nothing accounts of the image VRAM
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# because mllama is the only one doing its thing.
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for i in range(2)
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]
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responses = await asyncio.gather(*futures)
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@ -201,6 +201,11 @@ struct Config {
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impl Config {
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fn flop(&self) -> Option<u64> {
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if self.vision_config.is_some() {
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// VLM are much harder to predict and VRAM requirements
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// Are more complex.
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return None;
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}
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let num_heads = self.num_heads? as u64;
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let num_kv_heads = self.num_kv_heads? as u64;
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let head_dim = self.head_dim? as u64;
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@ -191,7 +191,7 @@ pub enum Config {
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#[serde(rename = "phi-msft")]
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PhiMsft,
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Phi3,
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PhiMoe,
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Phimoe,
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Llama,
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Baichuan,
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Paligemma(Paligemma),
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@ -1598,6 +1598,8 @@ class FlashCausalLM(Model):
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if max_input_tokens is None
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else max_input_tokens
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)
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elif max_input_tokens is None:
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max_input_tokens = max_total_tokens - 1
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del _batch, batch
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self.kv_cache = []
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