!17239 add parallel gathernd test case

From: @hanyang001
Reviewed-by: @stsuteng,@yangzhenzhang
Signed-off-by: @stsuteng

tests/ut/python/parallel/test_gathernd_further.py

@@ -0,0 +1,376 @@
+# Copyright 2021 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.
+# ============================================================================
+import numpy as np
+import pytest
+
+import mindspore as ms
+from mindspore import context, Tensor, Parameter
+from mindspore.nn import Cell, Momentum
+from mindspore.ops import operations as P
+from mindspore.train import Model
+from tests.dataset_mock import MindData
+
+
+class Dataset(MindData):
+    def __init__(self, predict, label, length=3):
+        super(Dataset, self).__init__(size=length)
+        self.predict = predict
+        self.label = label
+        self.index = 0
+        self.length = length
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        if self.index >= self.length:
+            raise StopIteration
+        self.index += 1
+        return self.predict, self.label
+
+    def reset(self):
+        self.index = 0
+
+
+class Net(Cell):
+    def __init__(self, w1_shape, indices_shape, strategy1=None, strategy2=None, strategy3=None):
+        super().__init__()
+        self.mul = P.Mul().shard(strategy1)
+        self.w1 = Parameter(Tensor(np.ones(w1_shape), dtype=ms.float32), "w1")
+        self.indices = Tensor(np.ones(indices_shape), dtype=ms.int32)
+        self.gathernd = P.GatherNd().shard(strategy2)
+        self.relu = P.ReLU().shard(strategy3)
+
+    def construct(self, x, b):
+        out = self.mul(x, self.w1)
+        out = self.gathernd(out, self.indices)
+        out = self.relu(out)
+        return out
+
+
+class Net2(Cell):
+    def __init__(self, w1_shape, indices_shape, strategy1=None, strategy2=None, strategy3=None):
+        super().__init__()
+        self.mul = P.Mul().shard(strategy1)
+        self.w1 = Parameter(Tensor(np.ones(w1_shape), dtype=ms.float32), "w1")
+        self.indices = Tensor(np.ones(indices_shape), dtype=ms.int32)
+        self.gathernd = P.GatherNd().shard(strategy2)
+        self.relu = P.ReLU().shard(strategy3)
+
+    def construct(self, x, b):
+        out = self.mul(x, self.w1)
+        out = self.gathernd(out, self.indices)
+        return out
+
+
+class Net3(Cell):
+    def __init__(self, w1_shape, indices_shape, strategy1=None, strategy2=None, strategy3=None):
+        super().__init__()
+        self.mul = P.Mul().shard(strategy1)
+        self.w1 = Parameter(Tensor(np.ones(w1_shape), dtype=ms.float32), "w1")
+        self.indices = Tensor(np.ones(indices_shape), dtype=ms.int32)
+        self.gathernd = P.GatherNd().shard(strategy2)
+        self.relu = P.ReLU().shard(strategy3)
+
+    def construct(self, x, b):
+        out = self.gathernd(x, self.indices)
+        out = self.relu(out)
+        out = self.mul(out, self.w1)
+        return out
+
+
+# full_batch = false
+_x = Tensor(np.ones([1, 16, 32]), dtype=ms.float32)
+_b = Tensor(np.ones([1, 16, 32]), dtype=ms.float32)
+
+
+def compile_net(net):
+    context.set_context(save_graphs=True)
+    learning_rate = 0.1
+    momentum = 0.9
+    epoch_size = 2
+    dataset = Dataset(_x, _b)
+    opt = Momentum(net.trainable_params(), learning_rate, momentum)
+    model = Model(net, optimizer=opt)
+    model.train(epoch_size, dataset, dataset_sink_mode=False)
+    context.reset_auto_parallel_context()
+
+
+def test_gathernd_data_parallel():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel2():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 2]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel3():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel4():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1, 1, 1),)
+    net = Net2(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel5():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 2]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1, 1),)
+    net = Net2(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel6():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net2(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel7():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 4, 2, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    strategy1 = ((8, 1, 1, 1, 1), (8, 1, 1, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1, 1, 1),)
+    net = Net3(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel8():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 4, 2, 32]
+    indices_shape = [8, 4, 2, 2]
+    strategy1 = ((8, 1, 1, 1), (8, 1, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1, 1),)
+    net = Net3(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_data_parallel9():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 4, 2]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (8, 1, 1, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net3(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel2():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 2]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel3():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel4():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1, 1, 1),)
+    net = Net2(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel5():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 2]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1, 1),)
+    net = Net2(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel6():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net2(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel7():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 4, 2, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    strategy1 = ((8, 1, 1, 1, 1), (8, 1, 1, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1, 1, 1),)
+    net = Net3(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel8():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 4, 2, 32]
+    indices_shape = [8, 4, 2, 2]
+    strategy1 = ((8, 1, 1, 1), (8, 1, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1, 1),)
+    net = Net3(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+
+def test_gathernd_model_parallel9():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 4, 2]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (2, 2, 2, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net3(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    compile_net(net)
+
+def test_gathernd_auto_parallel():
+    context.set_auto_parallel_context(
+        parallel_mode="auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 1]
+    net = Net(w1_shape, indices_shape)
+    compile_net(net)
+
+
+def test_gathernd_auto_parallel2():
+    context.set_auto_parallel_context(
+        parallel_mode="auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 2]
+    net = Net(w1_shape, indices_shape)
+    compile_net(net)
+
+
+def test_gathernd_auto_parallel3():
+    context.set_auto_parallel_context(
+        parallel_mode="auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    net = Net(w1_shape, indices_shape)
+    compile_net(net)
+
+
+def test_gathernd_strategy_error():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((2, 1, 1), (1, 2, 2, 1))
+    strategy3 = ((8, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    with pytest.raises(RuntimeError):
+        compile_net(net)
+
+
+def test_gathernd_strategy_error2():
+    context.set_auto_parallel_context(
+        parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
+    w1_shape = [8, 16, 32]
+    indices_shape = [8, 4, 2, 3]
+    strategy1 = ((8, 1, 1), (8, 1, 1))
+    strategy2 = ((1, 1, 1), (1, 2, 2, 2))
+    strategy3 = ((8, 1, 1),)
+    net = Net(w1_shape, indices_shape, strategy1, strategy2, strategy3)
+    with pytest.raises(RuntimeError):
+        compile_net(net)