forked from huawei/mindspore2022
127 lines
4.4 KiB
Python
127 lines
4.4 KiB
Python
# Copyright 2022 Huawei Technologies Co., Ltd
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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 numpy as np
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import pytest
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from mindspore import Tensor, context
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from mindspore.common.api import _cell_graph_executor
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from mindspore.nn import Cell
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from mindspore.ops import operations as P
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from parallel.utils.utils import ParallelValidator
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POOLED_HEIGHT = 2
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POOLED_WIDTH = 2
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SPATIAL_SCALE = 0.5
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BATCH_SIZE = 32
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FEATURES_HEIGHT = 256
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FEATURES_WIDTH = 256
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CHANNELS = 3
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NUM_ROIS = 16
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_features = Tensor(np.random.normal(size=[BATCH_SIZE, CHANNELS, FEATURES_HEIGHT, FEATURES_WIDTH]).astype(np.float32))
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_rois = Tensor(
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np.hstack((np.random.randint(0, BATCH_SIZE, [NUM_ROIS, 1]).astype(np.float32),
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np.random.uniform(low=0, high=FEATURES_HEIGHT / SPATIAL_SCALE, size=[NUM_ROIS, 4]).astype(np.float32))))
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class Net(Cell):
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def __init__(self, pooled_h, pooled_w, spatial_scale, strategy=None):
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super(Net, self).__init__()
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self.roi_align = P.ROIAlign(pooled_h, pooled_w, spatial_scale).shard(strategy)
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def construct(self, features, rois):
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output = self.roi_align(features, rois)
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return output
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def compile_net(net: Cell, *inputs):
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net.set_auto_parallel()
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net.set_train()
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phase, _ = _cell_graph_executor.compile(net, *inputs, auto_parallel_mode=True)
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context.reset_auto_parallel_context()
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return phase
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def test_roi_align_auto_parallel():
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"""
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Feature: test ROIAlign auto parallel
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Description: auto parallel
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0)
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net = Net(POOLED_HEIGHT, POOLED_WIDTH, SPATIAL_SCALE)
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compile_net(net, _features, _rois)
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def test_roi_align_data_parallel():
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"""
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Feature: test ROIAlign data parallel
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Description: data parallel
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((4, 1, 1, 1), (2, 1))
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net = Net(POOLED_HEIGHT, POOLED_WIDTH, SPATIAL_SCALE, strategy)
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compile_net(net, _features, _rois)
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def test_roi_align_strategy_error():
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"""
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Feature: test invalid strategy for ROIAlign
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Description: illegal strategy
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Expectation: raise RuntimeError
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((2, 1, 2, 2), (1, 1))
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net = Net(POOLED_HEIGHT, POOLED_WIDTH, SPATIAL_SCALE, strategy)
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with pytest.raises(RuntimeError):
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compile_net(net, _features, _rois)
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context.reset_auto_parallel_context()
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def test_roi_align_layout():
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"""
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Features: ROIAlignInfo
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Description: validate layout and structure
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Expectation: No raise RuntimeError
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((4, 1, 1, 1), (2, 1))
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net = Net(POOLED_HEIGHT, POOLED_WIDTH, SPATIAL_SCALE, strategy)
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phase = compile_net(net, _features, _rois)
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validator = ParallelValidator(net, phase)
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# check layout
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features_expect_layout = ([8], [0, -1, -1, -1], [4, 3, 256, 256], 0, True, '')
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assert validator.check_parameter_layout('features', features_expect_layout)
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# check attrs
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roi_expect_attrs = {'pooled_height': POOLED_HEIGHT, 'pooled_width': POOLED_WIDTH, 'spatial_scale': SPATIAL_SCALE}
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assert validator.check_node_attrs('ROIAlign-0', roi_expect_attrs)
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# check inputs
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roi_expect_inputs = ['Reshape-1', 'TensorScatterUpdate-0']
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assert validator.check_node_inputs('ROIAlign-0', roi_expect_inputs)
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# check sub_graph
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sub_graph = {
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'TensorScatterUpdate-0': ['Reshape-3', 'Stack-0', 'Minimum-0'],
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'Equal-0': ['Sub-0', 'Minimum-0'],
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'ROIAlign-0': ['Reshape-1', 'TensorScatterUpdate-0'],
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'Mul-0': ['ROIAlign-0', 'ExpandDims-2'],
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'AllReduce-0': ['Mul-0']
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}
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assert validator.check_graph_structure(sub_graph)
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