Initial commit

verl/utils/megatron/sequence_parallel.py

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+# Copyright 2024 Bytedance Ltd. and/or its affiliates
+# Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+import torch.nn.functional as F
+from megatron.core import parallel_state as mpu
+
+
+def mark_parameter_as_sequence_parallel(parameter):
+    setattr(parameter, 'sequence_parallel', True)
+
+
+def is_sequence_parallel_param(param):
+    return hasattr(param, 'sequence_parallel') and param.sequence_parallel
+
+
+def pad_to_sequence_parallel(unpad_tokens: torch.Tensor):
+    """pad the tokens such that the total length is a multiple of sp world size
+
+    Args:
+        unpad_tokens: (total_nnz, ...). Tokens after removing padding
+
+    Returns:
+
+    """
+    total_nnz = unpad_tokens.shape[0]
+    sp_world_size = mpu.get_tensor_model_parallel_world_size()
+
+    if total_nnz % sp_world_size == 0:
+        pad_size = 0
+    else:
+        pad_size = sp_world_size - total_nnz % sp_world_size
+
+    if pad_size > 0:
+        if unpad_tokens.ndim == 1:
+            unpad_tokens = F.pad(unpad_tokens, (0, pad_size))
+        elif unpad_tokens.ndim == 2:
+            unpad_tokens = F.pad(unpad_tokens, (0, 0, 0, pad_size))
+        else:
+            raise NotImplementedError(f'Padding dim {unpad_tokens.ndim()} is not supported')
+
+    return unpad_tokens