75 lines
3.3 KiB
Python
75 lines
3.3 KiB
Python
# Copyright 2024 Bytedance Ltd. and/or its affiliates
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# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.
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#
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# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
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# and OPT implementations in this library. It has been modified from its
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# original forms to accommodate minor architectural differences compared
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# to GPT-NeoX and OPT used by the Meta AI team that trained the model.
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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 megatron.core import parallel_state as mpu
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from megatron.core import tensor_parallel
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from megatron.core import ModelParallelConfig
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from torch import nn
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from transformers.activations import ACT2FN
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from verl.models.llama.megatron.layers.parallel_linear import MergedColumnParallelLinear
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from verl.utils.megatron import tensor_parallel as tp_utils
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class ParallelLlamaMLP(nn.Module):
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def __init__(self, config, megatron_config: ModelParallelConfig = None) -> None:
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super().__init__()
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self.config = config
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self.hidden_size = config.hidden_size
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self.intermediate_size = config.intermediate_size
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# The weight is only [hidden_size, intermediate_size // model_parallel_world_size]
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column_kwargs = tp_utils.get_default_kwargs_for_column_parallel_linear()
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row_kwargs = tp_utils.get_default_kwargs_for_row_parallel_linear()
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if megatron_config is not None:
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assert column_kwargs.get('config', False), 'must have ModelParallelConfig'
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assert row_kwargs.get('config', False), 'must have ModelParallelConfig'
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tp_utils.update_kwargs_with_config(row_kwargs, megatron_config)
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tp_utils.update_kwargs_with_config(column_kwargs, megatron_config)
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tp_size = mpu.get_tensor_model_parallel_world_size()
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self.gate_up_proj = MergedColumnParallelLinear(
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input_size=self.hidden_size,
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gate_ouput_size=self.intermediate_size,
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up_output_size=self.intermediate_size,
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bias=False,
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gather_output=False,
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skip_bias_add=False,
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**column_kwargs,
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)
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self.gate_size = self.intermediate_size // tp_size
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self.down_proj = tensor_parallel.RowParallelLinear(input_size=self.intermediate_size,
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output_size=self.hidden_size,
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bias=False,
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input_is_parallel=True,
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skip_bias_add=False,
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**row_kwargs)
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self.act_fn = ACT2FN[config.hidden_act]
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def forward(self, x):
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gate_up = self.gate_up_proj(x)[0]
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gate, up = gate_up.split(self.gate_size, dim=-1)
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return self.down_proj(self.act_fn(gate) * up)[0]
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