wehub-resource-sync
487 lines
21 KiB
Python
487 lines
21 KiB
Python
# Copyright (c) 2023 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 collections import OrderedDict
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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 TestReductionSPMDRule(unittest.TestCase):
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"""
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Unit tests for reduction spmd rule.
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"""
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def config(self):
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self.kernel = "max"
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def setUp(self):
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self.config()
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self.rule = core.get_phi_spmd_rule(self.kernel)
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x_shape = [64, 32]
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process_mesh = auto.ProcessMesh(mesh=[0, 1, 2, 3])
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x_tensor_dist_attr = TensorDistAttr()
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x_tensor_dist_attr.dims_mapping = [1, 0]
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x_tensor_dist_attr.process_mesh = process_mesh
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self.x_dist_tensor_spec = DistTensorSpec(x_shape, x_tensor_dist_attr)
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self.out_dist_tensor_spec = DistTensorSpec(self.x_dist_tensor_spec)
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self.attrs = OrderedDict([('axis', [0]), ('keep_dim', False)])
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def test_single_mesh_dim(self):
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# reduce on dim 0, keep_dim = false
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# [0, -1] --> [0, -1], [-1], partial_on_dim:[0]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [0]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(len(result_dist_attrs), 2)
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self.assertEqual(len(inferred_input_dist_attrs), 1)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {0})
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# reduce on dim 0, keep_dim = true
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# [0, -1] --> [0, -1], [-1, -1], partial_on_dim:[0]
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [0]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1, -1])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {0})
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# reduce on dim 1, keep_dim = false
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# [0, -1] --> [0, -1], [0], partial_on_dim:[]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), False)
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# reduce on dim 1, keep_dim = true
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# [0, -1] --> [0, -1], [0, -1], partial_on_dim:[]
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [1]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), False)
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# reduce on dim 0 and 1, keep_dim = false
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# [0, -1] --> [0, -1], [], partial_on_dim:[0]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [0, 1]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {0})
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# reduce on dim 0 and 1, keep_dim = true
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# [0, -1] --> [0, -1], [-1, -1], partial_on_dim:[0]
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [0, 1]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1, -1])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {0})
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def test_multi_mesh_dim(self):
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process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2], [3, 4, 5]])
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self.x_dist_tensor_spec.set_process_mesh(process_mesh)
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self.x_dist_tensor_spec.shape = [96, 24, 48]
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# reduce on dim 1, 2, keep_dim = false
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# [0, -1, -1] --> [0, -1, -1], [0], partial_on_dim:[]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1, 2]
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self.x_dist_tensor_spec.set_dims_mapping([0, -1, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(len(result_dist_attrs), 2)
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self.assertEqual(len(inferred_input_dist_attrs), 1)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), False)
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# reduce on dim 1, 2, keep_dim = false
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# [-1, 0, 1] --> [-1, 0, 1], [-1], partial_on_dim:[0, 1]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1, 2]
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self.x_dist_tensor_spec.set_dims_mapping([-1, 0, 1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [-1, 0, 1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {0, 1})
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inferred_output_dist_attrs[0]._clean_partial_status()
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), False)
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# reduction on dim 1, 2, keep_dim = false
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# [1, -1, -1] --> [1, -1, -1], [1], partial_on_dim:[]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1, 2]
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self.x_dist_tensor_spec.set_dims_mapping([1, -1, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [1, -1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [1])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), False)
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# reduction on dim 1, 2, keep_dim = false
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# [0, 1, -1] --> [0, 1, -1], [0], partial_on_dim:[1]
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1, 2]
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self.x_dist_tensor_spec.set_dims_mapping([0, 1, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, 1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0])
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {1})
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inferred_output_dist_attrs[0]._clean_partial_status()
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), False)
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# reduction on dim 1, 2, keep_dim = true
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# [0, 1, -1] --> [0, 1, -1], [0, -1, -1], partial_on_dim:[1]
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [1, 2]
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self.x_dist_tensor_spec.set_dims_mapping([0, 1, -1])
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec, self.attrs['axis'], self.attrs['keep_dim']
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, 1, -1])
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self.assertEqual(
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inferred_output_dist_attrs[0].dims_mapping, [0, -1, -1]
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)
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self.assertEqual(inferred_output_dist_attrs[0]._is_partial(), True)
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self.assertEqual(inferred_output_dist_attrs[0]._partial_dims(), {1})
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def test_backward_single_mesh_dim(self):
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# reduce on dim 0, keep_dim = false
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# [-1] --> [-1, -1], [-1] (output --> input, output)
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [0]
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self.out_dist_tensor_spec.shape = [32]
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self.out_dist_tensor_spec.set_dims_mapping([-1])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(len(result_dist_attrs), 2)
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self.assertEqual(len(inferred_input_dist_attrs), 1)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [-1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1])
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# reduce on dim 0, keep_dim = true
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# [-1, -1] --> [-1, -1], [-1, -1] (output --> input, output)
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [0]
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self.out_dist_tensor_spec.shape = [1, 32]
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self.out_dist_tensor_spec.set_dims_mapping([-1, -1])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [-1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1, -1])
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# reduce on dim 1, keep_dim = false
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# [0] --> [0, -1], [0] (output --> input, output)
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1]
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self.out_dist_tensor_spec.shape = [64]
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self.out_dist_tensor_spec.set_dims_mapping([0])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0])
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# reduce on dim 1, keep_dim = true
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# [0, -1] --> [0, -1], [0, -1] (output --> input, output)
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [1]
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self.out_dist_tensor_spec.shape = [64, 1]
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self.out_dist_tensor_spec.set_dims_mapping([0, -1])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0, -1])
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# reduce on dim 0 and 1, keep_dim = false
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# [] --> [-1, -1], [] (output --> input, output)
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [0, 1]
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self.out_dist_tensor_spec.shape = []
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self.out_dist_tensor_spec.set_dims_mapping([])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [-1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [])
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# reduce on dim 0 and 1, keep_dim = true
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# [-1, -1] --> [-1, -1], [-1, -1] (output --> input, output)
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self.attrs['keep_dim'] = True
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self.attrs['axis'] = [0, 1]
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self.out_dist_tensor_spec.shape = [1, 1]
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self.out_dist_tensor_spec.set_dims_mapping([-1, -1])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [-1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1, -1])
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def test_backward_multi_mesh_dim(self):
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process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2], [3, 4, 5]])
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self.x_dist_tensor_spec.set_process_mesh(process_mesh)
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self.x_dist_tensor_spec.shape = [96, 24, 48]
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self.out_dist_tensor_spec.set_process_mesh(process_mesh)
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# reduce on dim 1, 2, keep_dim = false
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# [0] --> [0, -1, -1], [0] (output --> input, output)
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self.attrs['keep_dim'] = False
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self.attrs['axis'] = [1, 2]
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self.out_dist_tensor_spec.shape = [96]
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self.out_dist_tensor_spec.set_dims_mapping([0])
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result_dist_attrs = self.rule.infer_backward(
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self.x_dist_tensor_spec,
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self.out_dist_tensor_spec,
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self.attrs['axis'],
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self.attrs['keep_dim'],
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)
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inferred_input_dist_attrs = result_dist_attrs[0]
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inferred_output_dist_attrs = result_dist_attrs[1]
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self.assertEqual(len(result_dist_attrs), 2)
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self.assertEqual(len(inferred_input_dist_attrs), 1)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1, -1])
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self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [0])
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# reduce on dim 1, 2, keep_dim = false
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# [-1] --> [-1, -1, -1], [-1] (output --> input, output)
|
|
self.attrs['keep_dim'] = False
|
|
self.attrs['axis'] = [1, 2]
|
|
self.out_dist_tensor_spec.shape = [96]
|
|
self.out_dist_tensor_spec.set_dims_mapping([-1])
|
|
result_dist_attrs = self.rule.infer_backward(
|
|
self.x_dist_tensor_spec,
|
|
self.out_dist_tensor_spec,
|
|
self.attrs['axis'],
|
|
self.attrs['keep_dim'],
|
|
)
|
|
inferred_input_dist_attrs = result_dist_attrs[0]
|
|
inferred_output_dist_attrs = result_dist_attrs[1]
|
|
|
|
self.assertEqual(
|
|
inferred_input_dist_attrs[0].dims_mapping, [-1, -1, -1]
|
|
)
|
|
self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [-1])
|
|
|
|
# reduction on dim 1, 2, keep_dim = false
|
|
# [1] --> [1, -1, -1], [1] (output --> input, output)
|
|
self.attrs['keep_dim'] = False
|
|
self.attrs['axis'] = [1, 2]
|
|
self.out_dist_tensor_spec.shape = [96]
|
|
self.out_dist_tensor_spec.set_dims_mapping([1])
|
|
result_dist_attrs = self.rule.infer_backward(
|
|
self.x_dist_tensor_spec,
|
|
self.out_dist_tensor_spec,
|
|
self.attrs['axis'],
|
|
self.attrs['keep_dim'],
|
|
)
|
|
inferred_input_dist_attrs = result_dist_attrs[0]
|
|
inferred_output_dist_attrs = result_dist_attrs[1]
|
|
|
|
self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [1, -1, -1])
|
|
self.assertEqual(inferred_output_dist_attrs[0].dims_mapping, [1])
|
|
|
|
# reduction on dim 1, 2, keep_dim = true
|
|
# [0, -1, -1] --> [0, -1, -1], [0, -1, -1] (output --> input, output)
|
|
self.attrs['keep_dim'] = True
|
|
self.attrs['axis'] = [1, 2]
|
|
self.out_dist_tensor_spec.shape = [96, 1, 1]
|
|
self.out_dist_tensor_spec.set_dims_mapping([0, -1, -1])
|
|
result_dist_attrs = self.rule.infer_backward(
|
|
self.x_dist_tensor_spec,
|
|
self.out_dist_tensor_spec,
|
|
self.attrs['axis'],
|
|
self.attrs['keep_dim'],
|
|
)
|
|
inferred_input_dist_attrs = result_dist_attrs[0]
|
|
inferred_output_dist_attrs = result_dist_attrs[1]
|
|
|
|
self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1, -1])
|
|
self.assertEqual(
|
|
inferred_output_dist_attrs[0].dims_mapping, [0, -1, -1]
|
|
)
|
|
|
|
def test_backward_multi_mesh_dim_partial(self):
|
|
# reduction on dim 1, 2, keep_dim = true, partial_dim=[1]
|
|
# [0, -1, -1] --> [0, -1, -1], [0, -1, -1] (output --> input, output)
|
|
# output partial_dim: [1], input partial_dim: []
|
|
out_shape = [96, 1, 1]
|
|
process_mesh = auto.ProcessMesh(mesh=[[0, 1, 2], [3, 4, 5]])
|
|
|
|
self.x_dist_tensor_spec.set_process_mesh(process_mesh)
|
|
self.x_dist_tensor_spec.shape = [96, 24, 48]
|
|
out_tensor_dist_attr = TensorDistAttr()
|
|
out_tensor_dist_attr.dims_mapping = [0, -1, -1]
|
|
out_tensor_dist_attr.process_mesh = process_mesh
|
|
out_tensor_dist_attr._set_partial_dims([1])
|
|
self.out_dist_tensor_spec = DistTensorSpec(
|
|
out_shape, out_tensor_dist_attr
|
|
)
|
|
|
|
self.attrs['keep_dim'] = True
|
|
self.attrs['axis'] = [1, 2]
|
|
result_dist_attrs = self.rule.infer_backward(
|
|
self.x_dist_tensor_spec,
|
|
self.out_dist_tensor_spec,
|
|
self.attrs['axis'],
|
|
self.attrs['keep_dim'],
|
|
)
|
|
inferred_input_dist_attrs = result_dist_attrs[0]
|
|
inferred_output_dist_attrs = result_dist_attrs[1]
|
|
|
|
self.assertEqual(inferred_input_dist_attrs[0].dims_mapping, [0, -1, -1])
|
|
self.assertEqual(
|
|
inferred_output_dist_attrs[0].dims_mapping, [0, -1, -1]
|
|
)
|
|
self.assertEqual(inferred_input_dist_attrs[0]._is_partial(), False)
|
|
|
|
|
|
class TestSquaredL2NormSPMDRule(TestReductionSPMDRule):
|
|
"""
|
|
Unit tests for squared_l2_norm spmd rule.
|
|
"""
|
|
|
|
def config(self):
|
|
self.kernel = "squared_l2_norm"
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|