Update deprecated type hinting in models (#18132)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
@@ -1,6 +1,7 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
"""PyTorch MAMBA model."""
|
||||
from typing import Iterable, Optional, Set, Tuple
|
||||
from collections.abc import Iterable
|
||||
from typing import Optional
|
||||
|
||||
import torch
|
||||
from torch import nn
|
||||
@@ -30,7 +31,7 @@ from .utils import (AutoWeightsLoader, is_pp_missing_parameter,
|
||||
make_empty_intermediate_tensors_factory, make_layers,
|
||||
maybe_prefix)
|
||||
|
||||
KVCache = Tuple[torch.Tensor, torch.Tensor]
|
||||
KVCache = tuple[torch.Tensor, torch.Tensor]
|
||||
|
||||
|
||||
class MambaDecoderLayer(nn.Module):
|
||||
@@ -153,10 +154,10 @@ class MambaModel(nn.Module):
|
||||
|
||||
return hidden_states
|
||||
|
||||
def load_weights(self, weights: Iterable[Tuple[str,
|
||||
torch.Tensor]]) -> Set[str]:
|
||||
def load_weights(self, weights: Iterable[tuple[str,
|
||||
torch.Tensor]]) -> set[str]:
|
||||
params_dict = dict(self.named_parameters())
|
||||
loaded_params: Set[str] = set()
|
||||
loaded_params: set[str] = set()
|
||||
for name, loaded_weight in weights:
|
||||
if "A_log" in name:
|
||||
name = name.replace("A_log", "A")
|
||||
@@ -247,7 +248,7 @@ class MambaForCausalLM(nn.Module, HasInnerState, IsAttentionFree, SupportsPP,
|
||||
return self.mamba_cache.get_seqlen_agnostic_capture_inputs(batch_size)
|
||||
|
||||
def _get_mamba_cache_shape(
|
||||
self) -> Tuple[Tuple[int, int], Tuple[int, int]]:
|
||||
self) -> tuple[tuple[int, int], tuple[int, int]]:
|
||||
world_size = get_tensor_model_parallel_world_size()
|
||||
conv_state_shape = (
|
||||
self.config.intermediate_size // world_size,
|
||||
@@ -265,7 +266,7 @@ class MambaForCausalLM(nn.Module, HasInnerState, IsAttentionFree, SupportsPP,
|
||||
sampling_metadata)
|
||||
return logits
|
||||
|
||||
def load_weights(self, weights: Iterable[Tuple[str,
|
||||
torch.Tensor]]) -> Set[str]:
|
||||
def load_weights(self, weights: Iterable[tuple[str,
|
||||
torch.Tensor]]) -> set[str]:
|
||||
loader = AutoWeightsLoader(self)
|
||||
return loader.load_weights(weights)
|
||||
|
||||
Reference in New Issue
Block a user