mindspore/tests/st/gnn/test_gnn_aggregator.py

54 lines
1.9 KiB
Python
Raw Normal View History

2020-04-27 16:34:00 +08:00
# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""test gnn aggregator."""
import numpy as np
import mindspore.nn as nn
import mindspore.context as context
from mindspore import Tensor
from mindspore.common.api import _executor
import mindspore.ops.composite as C
from aggregator import MeanAggregator
context.set_context(mode=context.GRAPH_MODE)
class MeanAggregatorGrad(nn.Cell):
"""Backward of MeanAggregator"""
def __init__(self, network):
super(MeanAggregatorGrad, self).__init__()
self.grad_op = C.grad_all_with_sens
self.network = network
def construct(self, x, sens):
grad_op = self.grad_op(self.network)(x, sens)
return grad_op
def test_MeanAggregator():
"""Compile MeanAggregator forward graph"""
aggregator = MeanAggregator(32, 64, activation="relu", dropout_ratio=0.5)
input_data = Tensor(np.array(np.random.rand(32, 3, 32), dtype=np.float32))
_executor.compile(aggregator, input_data)
def test_MeanAggregator_grad():
"""Compile MeanAggregator backward graph"""
aggregator = MeanAggregator(32, 64, activation="relu", dropout_ratio=0.5)
input_data = Tensor(np.array(np.random.rand(32, 3, 32), dtype=np.float32))
sens = Tensor(np.ones([32, 64]).astype(np.float32))
grad_op = MeanAggregatorGrad(aggregator)
_executor.compile(grad_op, input_data, sens)