wehub-resource-sync
82 lines
3.0 KiB
Python
82 lines
3.0 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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import test_collective_api_base as test_base
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import paddle
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import paddle.distributed as dist
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from paddle import base
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class TestCollectiveAllToAllAPIUnequalSplit(
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test_base.TestCollectiveAPIRunnerBase
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):
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def __init__(self):
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self.global_ring_id = 0
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def get_model(self, main_prog, startup_program, rank, indata=None):
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with base.program_guard(main_prog, startup_program):
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dim0 = indata.shape[0]
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dim1 = indata.shape[1]
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half_dim0 = dim0 // 2
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half_dim1 = dim1 // 2
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if rank == 0:
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in_data_list = [
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indata[: half_dim0 - 1, : half_dim1 - 1],
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indata[: half_dim0 - 1, half_dim1 - 1 :],
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]
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out_data_shape_list = [
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(half_dim0 - 1, half_dim1 - 1),
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(half_dim0 + 1, half_dim1 - 2),
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]
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elif rank == 1:
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in_data_list = [
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indata[half_dim0 - 1 :, : half_dim1 - 2],
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indata[half_dim0 - 1 :, half_dim1 - 2 :],
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]
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out_data_shape_list = [
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(half_dim0 - 1, half_dim1 + 1),
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(half_dim0 + 1, half_dim1 + 2),
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]
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else:
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raise ValueError(f"only support nranks==2, but got rank {rank}")
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# NOTE: this is a hack relying on an undocumented behavior that `to_tensor` uses uint16 to replace bfloat16
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if indata.dtype == "bfloat16":
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tindata = [
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paddle.to_tensor(data, "float32").cast("uint16")
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for data in in_data_list
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]
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toutdata = [
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paddle.empty(shape, dtype="uint16")
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for shape in out_data_shape_list
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]
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dist.alltoall(toutdata, tindata)
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return [data.cast("float32").numpy() for data in toutdata]
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else:
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tindata = [paddle.to_tensor(data) for data in in_data_list]
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toutdata = [
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paddle.empty(shape, dtype=tindata[0].dtype)
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for shape in out_data_shape_list
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]
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dist.alltoall(toutdata, tindata)
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return [data.numpy() for data in toutdata]
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if __name__ == "__main__":
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test_base.runtime_main(
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TestCollectiveAllToAllAPIUnequalSplit, "alltoall_unequal_split"
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)
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