55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
# Copyright 2024 Bytedance Ltd. and/or its affiliates
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# Copyright (c) 2024, NVIDIA CORPORATION. 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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import torch
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import torch.nn.functional as F
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from megatron.core import parallel_state as mpu
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def mark_parameter_as_sequence_parallel(parameter):
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setattr(parameter, 'sequence_parallel', True)
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def is_sequence_parallel_param(param):
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return hasattr(param, 'sequence_parallel') and param.sequence_parallel
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def pad_to_sequence_parallel(unpad_tokens: torch.Tensor):
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"""pad the tokens such that the total length is a multiple of sp world size
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Args:
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unpad_tokens: (total_nnz, ...). Tokens after removing padding
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Returns:
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"""
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total_nnz = unpad_tokens.shape[0]
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sp_world_size = mpu.get_tensor_model_parallel_world_size()
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if total_nnz % sp_world_size == 0:
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pad_size = 0
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else:
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pad_size = sp_world_size - total_nnz % sp_world_size
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if pad_size > 0:
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if unpad_tokens.ndim == 1:
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unpad_tokens = F.pad(unpad_tokens, (0, pad_size))
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elif unpad_tokens.ndim == 2:
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unpad_tokens = F.pad(unpad_tokens, (0, 0, 0, pad_size))
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else:
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raise NotImplementedError(f'Padding dim {unpad_tokens.ndim()} is not supported')
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return unpad_tokens
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