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:
@@ -9,7 +9,7 @@
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from collections.abc import Iterable
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from itertools import islice
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from typing import Any, Optional, Union
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from typing import Any
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import torch
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from torch import nn
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@@ -51,7 +51,7 @@ class OrionMLP(nn.Module):
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hidden_size: int,
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intermediate_size: int,
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hidden_act: str,
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quant_config: Optional[QuantizationConfig] = None,
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quant_config: QuantizationConfig | None = None,
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) -> None:
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super().__init__()
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self.gate_up_proj = MergedColumnParallelLinear(
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@@ -80,10 +80,10 @@ class OrionAttention(nn.Module):
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num_heads: int,
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num_kv_heads: int,
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rope_theta: float = 10000,
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rope_scaling: Optional[dict[str, Any]] = None,
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rope_scaling: dict[str, Any] | None = None,
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max_position_embeddings: int = 8192,
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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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) -> None:
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super().__init__()
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@@ -158,8 +158,8 @@ class OrionDecoderLayer(nn.Module):
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def __init__(
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self,
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config: PretrainedConfig,
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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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) -> None:
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super().__init__()
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@@ -250,9 +250,9 @@ class OrionModel(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],
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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,
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inputs_embeds: torch.Tensor | None = 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 not None:
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hidden_states = inputs_embeds
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@@ -340,9 +340,9 @@ class OrionForCausalLM(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.model(
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input_ids, positions, intermediate_tensors, inputs_embeds
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)
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@@ -351,7 +351,7 @@ class OrionForCausalLM(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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