wehub-resource-sync
186 lines
7.3 KiB
Python
186 lines
7.3 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 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 TestRoiAlignSPMDRule(unittest.TestCase):
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def setUp(self):
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x_shape = [2, 4, 16, 16]
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boxes_shape = [6, 6]
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boxes_num_shape = [2]
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out_shape = [6, 2, 3, 3]
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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 = [0, 1, -1, -1]
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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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boxes_dist_attr = TensorDistAttr()
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boxes_dist_attr.dims_mapping = [-1, 1]
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boxes_dist_attr.process_mesh = process_mesh
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self.boxes_dist_tensor_spec = DistTensorSpec(
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boxes_shape, boxes_dist_attr
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)
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boxes_num_dist_attr = TensorDistAttr()
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boxes_num_dist_attr.dims_mapping = [-1]
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boxes_num_dist_attr.process_mesh = process_mesh
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self.boxes_num_dist_tensor_spec = DistTensorSpec(
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boxes_num_shape, boxes_num_dist_attr
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)
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out_grad_tensor_dist_attr = TensorDistAttr()
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out_grad_tensor_dist_attr.dims_mapping = [0, -1, -1, -1]
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out_grad_tensor_dist_attr.process_mesh = process_mesh
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self.out_grad_dist_tensor_spec = DistTensorSpec(
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out_shape, out_grad_tensor_dist_attr
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)
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self.rule = core.get_phi_spmd_rule("roi_align")
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self.attrs = OrderedDict()
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self.attrs['pooled_height'] = 3
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self.attrs['pooled_width'] = 3
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self.attrs['spatial_scale'] = 0.5
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self.attrs['sampling_ratio'] = -1
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self.attrs['aligned'] = True
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def test_roi_align_forward(self):
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# [0, 1, -1, -1], [-1, 1], [0] --> [-1, 1, -1, -1],[-1, -1],[-1],[-1,1,-1,-1]
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec,
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self.boxes_dist_tensor_spec,
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self.boxes_num_dist_tensor_spec,
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self.attrs['pooled_height'],
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self.attrs['pooled_width'],
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self.attrs['spatial_scale'],
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self.attrs['sampling_ratio'],
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self.attrs['aligned'],
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)
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self.assertEqual(len(result_dist_attrs), 2)
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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(inferred_input_dist_attrs), 3)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(
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inferred_input_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [-1, -1])
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self.assertEqual(inferred_input_dist_attrs[2].dims_mapping, [-1])
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self.assertEqual(
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inferred_output_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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# [0, 1, -1, -1], [-1, 1], Fake --> [-1, 1, -1, -1],[-1, -1], Fake ,[-1,1,-1,-1]
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result_dist_attrs = self.rule.infer_forward(
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self.x_dist_tensor_spec,
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self.boxes_dist_tensor_spec,
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DistTensorSpec(),
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self.attrs['pooled_height'],
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self.attrs['pooled_width'],
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self.attrs['spatial_scale'],
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self.attrs['sampling_ratio'],
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self.attrs['aligned'],
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)
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self.assertEqual(len(result_dist_attrs), 2)
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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(inferred_input_dist_attrs), 3)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(
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inferred_input_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [-1, -1])
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self.assertEqual(inferred_input_dist_attrs[2], TensorDistAttr())
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self.assertEqual(
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inferred_output_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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def test_roi_align_backward(self):
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# [0, 1, -1, -1], [-1, 1], [0], [0, -1, -1, -1] --> [-1, 1, -1, -1],[-1,-1],[-1],[-1,1,-1,-1],[-1, 1, -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.boxes_dist_tensor_spec,
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self.boxes_num_dist_tensor_spec,
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self.out_grad_dist_tensor_spec,
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self.attrs['pooled_height'],
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self.attrs['pooled_width'],
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self.attrs['spatial_scale'],
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self.attrs['sampling_ratio'],
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self.attrs['aligned'],
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)
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self.assertEqual(len(result_dist_attrs), 2)
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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(inferred_input_dist_attrs), 4)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(
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inferred_input_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [-1, -1])
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self.assertEqual(inferred_input_dist_attrs[2].dims_mapping, [-1])
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self.assertEqual(
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inferred_input_dist_attrs[3].dims_mapping, [-1, 1, -1, -1]
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)
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self.assertEqual(
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inferred_output_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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# [0, 1, -1, -1], [-1, 1], Fake, [0, -1, -1, -1] --> [-1, 1, -1, -1],[-1,-1],Fake,[-1,1,-1,-1],[-1, 1, -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.boxes_dist_tensor_spec,
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DistTensorSpec(),
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self.out_grad_dist_tensor_spec,
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self.attrs['pooled_height'],
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self.attrs['pooled_width'],
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self.attrs['spatial_scale'],
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self.attrs['sampling_ratio'],
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self.attrs['aligned'],
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)
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self.assertEqual(len(result_dist_attrs), 2)
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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(inferred_input_dist_attrs), 4)
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self.assertEqual(len(inferred_output_dist_attrs), 1)
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self.assertEqual(
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inferred_input_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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self.assertEqual(inferred_input_dist_attrs[1].dims_mapping, [-1, -1])
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self.assertEqual(inferred_input_dist_attrs[2], TensorDistAttr())
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self.assertEqual(
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inferred_input_dist_attrs[3].dims_mapping, [-1, 1, -1, -1]
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)
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self.assertEqual(
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inferred_output_dist_attrs[0].dims_mapping, [-1, 1, -1, -1]
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)
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if __name__ == "__main__":
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unittest.main()
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