!44877 Fix maxpool3d infer for dynamic shape input

Merge pull request !44877 from panzhihui/fix_maxpool3d_infer

mindspore/core/ops/max_pool3d.cc

@@ -165,9 +165,10 @@ abstract::ShapePtr MaxPool3DInferShape(const PrimitivePtr &primitive, const std:
     MS_EXCEPTION_IF_NULL(item);
   }
   auto in_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->GetShapeTrack())[kShape];
-  // ToSupport Dynamic rank
-  if (IsDynamicRank(in_shape)) {
-    return std::make_shared<abstract::Shape>(std::vector<int64_t>{abstract::Shape::kShapeRankAny});
+  if (IsDynamic(in_shape)) {
+    return std::make_shared<abstract::Shape>(
+      std::vector<int64_t>{abstract::Shape::kShapeDimAny, abstract::Shape::kShapeDimAny, abstract::Shape::kShapeDimAny,
+                           abstract::Shape::kShapeDimAny, abstract::Shape::kShapeDimAny});
   }
   (void)CheckAndConvertUtils::CheckInteger("x_rank", SizeToLong(in_shape.size()), kEqual, k5DInputDims, op_name);
 

tests/st/ops/dynamic_shape/test_maxpool3d_dyn.py

@@ -0,0 +1,54 @@
+# Copyright 2022 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 Maxpool3d dynamic shape"""
+
+import numpy as np
+import pytest
+
+import mindspore as ms
+from mindspore import ops
+from mindspore import nn
+
+
+class Net(nn.Cell):
+    def __init__(self):
+        super().__init__()
+        self.pool = ops.MaxPool3D(kernel_size=2, strides=1, pad_mode="valid")
+
+    def construct(self, x):
+        out = self.pool(x)
+        return out
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_maxpool3d_valid(mode):
+    """
+    Feature: MaxPool3d
+    Description: test dynamic shape of MaxPool3d
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    x = ms.Tensor(np.arange(1 * 2 * 2 * 2 * 3).reshape((1, 2, 2, 2, 3)), ms.float32)
+    expected_shape = (1, 2, 1, 1, 2)
+
+    net = Net()
+    x_dyn = ms.Tensor(shape=[None]*len(x.shape), dtype=x.dtype)
+    net.set_inputs(x_dyn)
+    output = net(x)
+    assert output.shape == expected_shape