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chore: update copyright, minor reformatting
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@ -1,4 +1,4 @@
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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
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<!--Copyright 2024, 2025 NXAI GmbH. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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@ -1,4 +1,4 @@
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# Copyright 2024 The HuggingFace Team. All rights reserved.
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# Copyright 2024, 2025 NXAI GmbH. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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@ -12,6 +12,7 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import TYPE_CHECKING
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from ...utils import (
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@ -1,5 +1,4 @@
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# coding=utf-8
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# Copyright 2024 The HuggingFace Inc. team.
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# Copyright 2024, 2025 NXAI GmbH. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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@ -12,7 +11,9 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""XLSTM configuration"""
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"""xLSTM configuration."""
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from ...configuration_utils import PretrainedConfig
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from ...utils import is_xlstm_available, logging
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@ -1,3 +1,18 @@
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# Copyright 2024, 2025 NXAI GmbH. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""PyTorch xLSTM Model."""
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from dataclasses import dataclass
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@ -716,9 +731,13 @@ else:
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DHHV = v.shape[-1]
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c_state = (
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c_initial if c_initial is not None else torch.zeros(B, NH, DHQK, DHHV, device=k.device, dtype=torch.float32)
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c_initial
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if c_initial is not None
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else torch.zeros(B, NH, DHQK, DHHV, device=k.device, dtype=torch.float32)
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)
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n_state = (
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n_initial if n_initial is not None else torch.zeros(B, NH, DHQK, device=k.device, dtype=torch.float32)
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)
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n_state = n_initial if n_initial is not None else torch.zeros(B, NH, DHQK, device=k.device, dtype=torch.float32)
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m_state = m_initial if m_initial is not None else torch.zeros(B, NH, 1, device=k.device, dtype=torch.float32)
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if S > 1:
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@ -877,9 +896,9 @@ else:
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return_last_states = self.config.return_last_states
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if self.config.mode == "train_with_padding":
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assert (
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not return_last_states
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), "return_last_states=True is not supported with train_with_padding mode."
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assert not return_last_states, (
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"return_last_states=True is not supported with train_with_padding mode."
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)
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return self._train_fn(
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q=q,
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# coding=utf-8
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# Copyright 2024 The HuggingFace Team. All rights reserved.
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# Copyright 2024, 2025 NXAI GmbH. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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