wehub-resource-sync
73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
# Copyright (c) 2025 PaddlePaddle Authors. 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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from __future__ import annotations
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from typing import TYPE_CHECKING
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from paddle import _C_ops
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# from ....framework import LayerHelper, in_dynamic_or_pir_mode
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from paddle.base.framework import in_dynamic_or_pir_mode
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from paddle.base.layer_helper import LayerHelper
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if TYPE_CHECKING:
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from paddle import Tensor
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def expand_modality_expert_id(
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expert_id: Tensor,
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num_expert_per_modality: int,
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group_size: int,
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modality_offset: int,
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is_group_expert: bool,
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name: str | None = None,
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) -> Tensor:
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"""
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Args:
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expert_id:
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num_expert_per_modality:
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group_size:
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modality_offset:
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is_group_expert:
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Returns:
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"""
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if in_dynamic_or_pir_mode():
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return _C_ops.expand_modality_expert_id(
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expert_id,
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num_expert_per_modality,
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group_size,
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modality_offset,
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is_group_expert,
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)
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helper = LayerHelper('expand_modality_expert_id', **locals())
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expert_id_out = helper.create_variable_for_type_inference(
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dtype=expert_id.dtype
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)
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inputs = {'expert_id': expert_id}
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attrs = {
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'num_expert_per_modality': num_expert_per_modality,
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'group_size': group_size,
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'modality_offset': modality_offset,
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'is_group_expert': is_group_expert,
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}
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helper.append_op(
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type='expand_modality_expert_id',
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inputs=inputs,
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attrs=attrs,
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outputs={'expert_id_out': expert_id_out},
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)
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return expert_id_out
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