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https://github.com/unslothai/unsloth
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Fix Gemma fast inference (#215)
* Update save.py * save * trainer * spaces * original * Gemma * Update pyproject.toml * Update mapper.py * Update fast_lora.py * FastGemmaModel * model_type * Update llama.py * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update llama.py * Update fast_lora.py * Update llama.py * Update llama.py * Update cross_entropy_loss.py * Update llama.py * Update llama.py * gemma * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Fast CE Loss * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * CE * Update llama.py * Update llama.py * Update cross_entropy_loss.py * Update geglu.py * Update cross_entropy_loss.py * revert * Update llama.py * Update llama.py * norm * Update gemma.py * Update gemma.py * position_ids * Update gemma.py * Update gemma.py * pos * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update cross_entropy_loss.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * revert * revert * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update cross_entropy_loss.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * rope * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * llama * Update llama.py * gemma * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update save.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update gemma.py * correct_dtype * Update gemma.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Chat Templates * Update README.md * Update README.md * Update llama.py * DoRA * Update _utils.py * Update chat_templates.py * Update llama.py * Hotfix - fix DoRA, Gemma prompt template (#202) (#203) * Update save.py * saving * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update __init__.py * Update save.py * Update save.py * Update save.py * save * trainer * spaces * original * Gemma * Update pyproject.toml * Update mapper.py * Update fast_lora.py * FastGemmaModel * model_type * Update llama.py * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update llama.py * Update fast_lora.py * Update llama.py * Update llama.py * Update cross_entropy_loss.py * Update llama.py * Update llama.py * gemma * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update fast_lora.py * Update fast_lora.py * Fast CE Loss * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * CE * Update llama.py * Update llama.py * Update cross_entropy_loss.py * Update geglu.py * Update cross_entropy_loss.py * revert * Update llama.py * Update llama.py * norm * Update gemma.py * Update gemma.py * position_ids * Update gemma.py * Update gemma.py * pos * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update cross_entropy_loss.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * revert * revert * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update cross_entropy_loss.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * rope * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * llama * Update llama.py * gemma * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update gemma.py * Update save.py * RoPE * Update llama.py * Update llama.py * Update llama.py * Update gemma.py * correct_dtype * Update gemma.py * Update cross_entropy_loss.py * Update cross_entropy_loss.py * Chat Templates * Update README.md * Update README.md * Update llama.py * DoRA * Update _utils.py * Update chat_templates.py * Update pyproject.toml * Small fixes * Update pyproject.toml * Approx gelu * Update geglu.py * Approx gelu * Update llama.py * Update __init__.py * Update __init__.py * Update _utils.py * Update geglu.py * Update gemma.py
This commit is contained in:
Daniel Han
GitHub
parent
fa2a43baf3
commit
7b7665d9d6
1 changed files with 89 additions and 1 deletions
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@ -173,6 +173,94 @@ def GemmaModel_fast_forward_inference(
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pass
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def GemmaForCausalLM_fast_forward(
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self,
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input_ids: torch.LongTensor = None,
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causal_mask: Optional[xformers.attn_bias.BlockDiagonalCausalMask] = None,
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attention_mask: Optional[torch.Tensor] = None,
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position_ids: Optional[torch.LongTensor] = None,
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past_key_values: Optional[List[torch.FloatTensor]] = None,
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inputs_embeds: Optional[torch.FloatTensor] = None,
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labels: Optional[torch.LongTensor] = None,
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use_cache: Optional[bool] = None,
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output_attentions: Optional[bool] = None,
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output_hidden_states: Optional[bool] = None,
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return_dict: Optional[bool] = None,
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*args, **kwargs,
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) -> Union[Tuple, CausalLMOutputWithPast]:
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if causal_mask is None and past_key_values is None:
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causal_mask = xformers.attn_bias.LowerTriangularMask()
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output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
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output_hidden_states = (
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output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
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)
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return_dict = return_dict if return_dict is not None else self.config.use_return_dict
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# decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn)
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self.model._has_no_labels = labels is None
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if past_key_values is not None and \
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hasattr(self.model.layers[0].self_attn, "paged_attention"):
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outputs = GemmaModel_fast_forward_inference(
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self.model,
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input_ids,
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past_key_values,
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)
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else:
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outputs = self.model(
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input_ids=input_ids,
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causal_mask=causal_mask,
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attention_mask=attention_mask,
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position_ids=position_ids,
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past_key_values=past_key_values,
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inputs_embeds=inputs_embeds,
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use_cache=use_cache,
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output_attentions=output_attentions,
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output_hidden_states=output_hidden_states,
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return_dict=return_dict,
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)
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pass
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hidden_states = outputs[0]
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bsz, q_len, hd = hidden_states.shape
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if bsz == 1 and q_len == 1:
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logits = torch.mv(self.lm_head.weight, hidden_states.ravel())
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logits = logits.unsqueeze(0).unsqueeze(0)
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else:
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logits = self.lm_head(hidden_states)
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pass
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loss = None
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if labels is not None:
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shift_logits = logits
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if not hasattr(self, "extra_ignored_labels"):
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# Fixes https://github.com/unslothai/unsloth/issues/10
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self.extra_ignored_labels = torch.full((self.max_seq_length, 1), -100, device = "cuda")
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pass
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shift_labels = torch.hstack((labels[..., 1:], self.extra_ignored_labels[:labels.shape[0]]))
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loss = fast_cross_entropy_loss(
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logits = shift_logits,
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labels = shift_labels,
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)
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pass
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if not return_dict:
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output = (logits,) + outputs[1:]
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return (loss,) + output if loss is not None else output
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return CausalLMOutputWithPast(
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loss=loss,
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logits=logits,
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past_key_values=outputs.past_key_values,
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hidden_states=outputs.hidden_states,
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attentions=outputs.attentions,
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)
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pass
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class FastGemmaModel(FastLlamaModel):
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@staticmethod
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@ -182,7 +270,7 @@ class FastGemmaModel(FastLlamaModel):
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GemmaFlashAttention2.forward = LlamaAttention_fast_forward
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GemmaDecoderLayer .forward = GemmaDecoderLayer_fast_forward
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GemmaModel .forward = LlamaModel_fast_forward
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GemmaForCausalLM .forward = LlamaForCausalLM_fast_forward
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GemmaForCausalLM .forward = GemmaForCausalLM_fast_forward
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PeftModelForCausalLM.forward = PeftModelForCausalLM_fast_forward
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# Solves https://github.com/unslothai/unsloth/issues/168
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# Static KV Cache was introduced in 4.38.0, causing training to be much slower.
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