wehub-resource-sync
165 lines
6.3 KiB
Python
165 lines
6.3 KiB
Python
# Copyright (c) 2024 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 unittest
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from paddle.distributed.auto_parallel.static.dist_attribute import (
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DistTensorSpec,
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TensorDistAttr,
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)
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from paddle.distributed.fleet import auto
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from paddle.framework import core
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class TestAddNSPMDRule(unittest.TestCase):
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"""
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Unit tests for add_n spmd rule.
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"""
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def setUp(self):
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self.rule1 = core.get_phi_spmd_rule("add_n")
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process_mesh = auto.ProcessMesh(mesh=[[0, 1], [2, 3]])
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self.x_shape = [16, 16, 16]
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self.x_tensor_dist_attr = TensorDistAttr()
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self.x_tensor_dist_attr.process_mesh = process_mesh
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self.y_shape = [16, 16, 16]
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self.y_tensor_dist_attr = TensorDistAttr()
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self.y_tensor_dist_attr.process_mesh = process_mesh
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self.output_shape = [16, 16, 16]
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self.output_tensor_dist_attr = TensorDistAttr()
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self.output_tensor_dist_attr.process_mesh = process_mesh
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def test_infer_forward(self):
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# [0, -1, -1], [-1, -1, -1] (x,y) -->
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# [0, -1, -1], [0, -1, -1] (x, y)
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# [0, -1, -1] (output)
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self.x_dist_tensor_spec = DistTensorSpec(
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self.x_shape, self.x_tensor_dist_attr
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)
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self.x_dist_tensor_spec.set_dims_mapping([0, -1, -1])
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self.y_dist_tensor_spec = DistTensorSpec(
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self.y_shape, self.y_tensor_dist_attr
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)
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self.y_dist_tensor_spec.set_dims_mapping([0, -1, -1])
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inferred_dist_attr = self.rule1.infer_forward(
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[self.x_dist_tensor_spec, self.y_dist_tensor_spec]
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)
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self.assertEqual(len(inferred_dist_attr), 2)
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inferred_input_dist_attr = inferred_dist_attr[0]
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inferred_output_dist_attr = inferred_dist_attr[1]
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self.assertEqual(len(inferred_input_dist_attr), 1)
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self.assertEqual(len(inferred_input_dist_attr[0]), 2)
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self.assertEqual(len(inferred_output_dist_attr), 1)
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self.assertEqual(
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inferred_input_dist_attr[0][0].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(
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inferred_input_dist_attr[0][1].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(inferred_output_dist_attr[0].dims_mapping, [0, -1, -1])
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# [0, -1, -1], [-1, -1, -1] (x, y) partial_dim=[1] -->
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# [0, -1, -1], [0, -1, -1] (x, y) partial_dim=[1]
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# [0, -1, -1] (output) partial_dim=[1]
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self.x_tensor_dist_attr._set_partial_dims([1])
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self.x_dist_tensor_spec = DistTensorSpec(
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self.x_shape, self.x_tensor_dist_attr
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)
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self.x_dist_tensor_spec.set_dims_mapping([0, -1, -1])
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self.y_tensor_dist_attr._set_partial_dims([1])
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self.y_dist_tensor_spec = DistTensorSpec(
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self.y_shape, self.y_tensor_dist_attr
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)
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self.y_dist_tensor_spec.set_dims_mapping([-1, -1, -1])
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inferred_dist_attr = self.rule1.infer_forward(
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[self.x_dist_tensor_spec, self.y_dist_tensor_spec]
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)
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self.assertEqual(len(inferred_dist_attr), 2)
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inferred_input_dist_attr = inferred_dist_attr[0]
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inferred_output_dist_attr = inferred_dist_attr[1]
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self.assertEqual(len(inferred_input_dist_attr), 1)
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self.assertEqual(len(inferred_input_dist_attr[0]), 2)
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self.assertEqual(len(inferred_output_dist_attr), 1)
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self.assertEqual(
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inferred_input_dist_attr[0][0].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attr[0][0]._is_partial(), True)
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self.assertEqual(inferred_input_dist_attr[0][0]._partial_dims(), {1})
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self.assertEqual(
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inferred_input_dist_attr[0][1].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attr[0][1]._is_partial(), True)
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self.assertEqual(inferred_input_dist_attr[0][1]._partial_dims(), {1})
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self.assertEqual(inferred_output_dist_attr[0].dims_mapping, [0, -1, -1])
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self.assertEqual(inferred_output_dist_attr[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attr[0]._partial_dims(), {1})
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# [0, -1, -1] partial_dim=[0], [-1, -1, -1]partial_dim=[1] (x,y) -->
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# [0, -1, -1], [0, -1, -1] (x, y)
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# [0, -1, -1] (output)
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self.x_tensor_dist_attr._clean_partial_dims([1])
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self.x_tensor_dist_attr._set_partial_dims([0])
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self.x_dist_tensor_spec = DistTensorSpec(
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self.x_shape, self.x_tensor_dist_attr
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)
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self.x_dist_tensor_spec.set_dims_mapping([0, -1, -1])
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self.y_tensor_dist_attr._clean_partial_dims([1])
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self.y_tensor_dist_attr._set_partial_dims([1])
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self.y_dist_tensor_spec = DistTensorSpec(
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self.y_shape, self.y_tensor_dist_attr
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)
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self.y_dist_tensor_spec.set_dims_mapping([-1, -1, -1])
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inferred_dist_attr = self.rule1.infer_forward(
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[self.x_dist_tensor_spec, self.y_dist_tensor_spec]
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)
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self.assertEqual(len(inferred_dist_attr), 2)
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inferred_input_dist_attr = inferred_dist_attr[0]
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inferred_output_dist_attr = inferred_dist_attr[1]
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self.assertEqual(len(inferred_input_dist_attr), 1)
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self.assertEqual(len(inferred_input_dist_attr[0]), 2)
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self.assertEqual(len(inferred_output_dist_attr), 1)
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self.assertEqual(
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inferred_input_dist_attr[0][0].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attr[0][0]._is_partial(), False)
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self.assertEqual(
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inferred_input_dist_attr[0][1].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attr[0][1]._is_partial(), False)
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self.assertEqual(inferred_output_dist_attr[0].dims_mapping, [0, -1, -1])
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self.assertEqual(inferred_output_dist_attr[0]._is_partial(), False)
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if __name__ == "__main__":
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unittest.main()
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