Update Optional[x] -> x | None and Union[x, y] to x | y (#26633)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
@@ -22,7 +22,6 @@
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from collections.abc import Iterable
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from itertools import islice
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from typing import Optional, Union
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import torch
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from torch import nn
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@@ -65,8 +64,8 @@ class GPT2Attention(nn.Module):
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def __init__(
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self,
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config: GPT2Config,
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cache_config: Optional[CacheConfig] = None,
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quant_config: Optional[QuantizationConfig] = None,
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cache_config: CacheConfig | None = None,
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quant_config: QuantizationConfig | None = None,
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prefix: str = "",
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):
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super().__init__()
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@@ -118,7 +117,7 @@ class GPT2MLP(nn.Module):
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self,
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intermediate_size: int,
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config: GPT2Config,
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quant_config: Optional[QuantizationConfig] = None,
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quant_config: QuantizationConfig | None = None,
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prefix: str = "",
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):
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super().__init__()
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@@ -150,8 +149,8 @@ class GPT2Block(nn.Module):
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def __init__(
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self,
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config: GPT2Config,
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cache_config: Optional[CacheConfig] = None,
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quant_config: Optional[QuantizationConfig] = None,
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cache_config: CacheConfig | None = None,
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quant_config: QuantizationConfig | None = None,
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prefix: str = "",
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):
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super().__init__()
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@@ -221,9 +220,9 @@ class GPT2Model(nn.Module):
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self,
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input_ids: torch.Tensor,
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position_ids: torch.Tensor,
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intermediate_tensors: Optional[IntermediateTensors],
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inputs_embeds: Optional[torch.Tensor],
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) -> Union[torch.Tensor, IntermediateTensors]:
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intermediate_tensors: IntermediateTensors | None,
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inputs_embeds: torch.Tensor | None,
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) -> torch.Tensor | IntermediateTensors:
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if get_pp_group().is_first_rank:
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if inputs_embeds is None:
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inputs_embeds = self.get_input_embeddings(input_ids)
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@@ -301,9 +300,9 @@ class GPT2LMHeadModel(nn.Module, SupportsPP):
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self,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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intermediate_tensors: Optional[IntermediateTensors] = None,
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inputs_embeds: Optional[torch.Tensor] = None,
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) -> Union[torch.Tensor, IntermediateTensors]:
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intermediate_tensors: IntermediateTensors | None = None,
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inputs_embeds: torch.Tensor | None = None,
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) -> torch.Tensor | IntermediateTensors:
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hidden_states = self.transformer(
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input_ids, positions, intermediate_tensors, inputs_embeds
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)
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@@ -312,7 +311,7 @@ class GPT2LMHeadModel(nn.Module, SupportsPP):
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def compute_logits(
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self,
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hidden_states: torch.Tensor,
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) -> Optional[torch.Tensor]:
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) -> torch.Tensor | None:
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logits = self.logits_processor(self.lm_head, hidden_states)
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return logits
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@@ -367,8 +366,8 @@ class GPT2ForSequenceClassification(nn.Module):
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self,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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intermediate_tensors: Optional[IntermediateTensors] = None,
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inputs_embeds: Optional[torch.Tensor] = None,
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intermediate_tensors: IntermediateTensors | None = None,
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inputs_embeds: torch.Tensor | None = None,
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) -> torch.Tensor:
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hidden_states = self.transformer(
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input_ids=input_ids,
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