[npu]add unsqueeze2_grad,test=develop (#34733)

paddle/fluid/operators/unsqueeze_op_npu.cc

@@ -38,4 +38,20 @@ REGISTER_OP_NPU_KERNEL(
     ops::UnsqueezeKernel<plat::NPUDeviceContext, int>,
     ops::UnsqueezeKernel<plat::NPUDeviceContext, int8_t>,
     ops::UnsqueezeKernel<plat::NPUDeviceContext, int64_t>);
+REGISTER_OP_NPU_KERNEL(
+    unsqueeze_grad, ops::UnsqueezeGradKernel<plat::NPUDeviceContext, float>,
+    ops::UnsqueezeGradKernel<plat::NPUDeviceContext, double>,
+    ops::UnsqueezeGradKernel<plat::NPUDeviceContext, plat::float16>,
+    ops::UnsqueezeGradKernel<plat::NPUDeviceContext, bool>,
+    ops::UnsqueezeGradKernel<plat::NPUDeviceContext, int>,
+    ops::UnsqueezeGradKernel<plat::NPUDeviceContext, int8_t>,
+    ops::UnsqueezeGradKernel<plat::NPUDeviceContext, int64_t>);
+REGISTER_OP_NPU_KERNEL(
+    unsqueeze2_grad, ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, float>,
+    ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, double>,
+    ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, plat::float16>,
+    ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, bool>,
+    ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, int>,
+    ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, int8_t>,
+    ops::Unsqueeze2GradKernel<plat::NPUDeviceContext, int64_t>);
 #endif

python/paddle/fluid/tests/unittests/npu/test_unsqueeze_op_npu.py

+#   Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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.
+
+from __future__ import print_function
+
+import numpy as np
+import unittest
+import sys
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+from paddle.fluid import Program, program_guard
+
+paddle.enable_static()
+
+
+# unsqueeze
+class TestUnsqueezeOp(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "unsqueeze"
+        self.place = paddle.NPUPlace(0)
+        self.init_test_case()
+        self.x = np.random.random(self.ori_shape).astype("float32")
+        self.inputs = {"X": OpTest.np_dtype_to_fluid_dtype(self.x)}
+        self.init_attrs()
+        self.outputs = {"Out": self.x.reshape(self.new_shape), }
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+    def test_check_grad(self):
+        self.check_grad_with_place(self.place, ["X"], "Out")
+
+    def init_test_case(self):
+        self.ori_shape = (3, 40)
+        self.axes = (0, 2)
+        self.new_shape = (1, 3, 1, 40)
+
+    def init_attrs(self):
+        self.attrs = {"axes": self.axes}
+
+
+class TestUnsqueezeOp1(TestUnsqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (3, 40)
+        self.axes = (0, -2)
+        self.new_shape = (1, 3, 1, 40)
+
+
+# No axes input.
+class TestUnsqueezeOp2(TestUnsqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (20, 5)
+        self.axes = ()
+        self.new_shape = (1, 20, 5)
+
+
+# Just part of axes be squeezed. 
+class TestUnsqueezeOp3(TestUnsqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (6, 5, 1, 4)
+        self.axes = (1, -1)
+        self.new_shape = (6, 1, 5, 1, 4, 1)
+
+
+# unsqueeze 2        
+class TestUnsqueeze2Op(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "unsqueeze2"
+        self.place = paddle.NPUPlace(0)
+        self.init_test_case()
+        self.x = np.random.random(self.ori_shape).astype("float32")
+        self.inputs = {"X": OpTest.np_dtype_to_fluid_dtype(self.x)}
+        self.init_attrs()
+        self.outputs = {
+            "Out": self.x.reshape(self.new_shape),
+            "XShape": np.random.random(self.ori_shape).astype("float32")
+        }
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place, no_check_set=['XShape'])
+
+    def test_check_grad(self):
+        self.check_grad_with_place(self.place, ["X"], "Out")
+
+    def init_test_case(self):
+        self.ori_shape = (3, 40)
+        self.axes = (0, 2)
+        self.new_shape = (1, 3, 1, 40)
+
+    def init_attrs(self):
+        self.attrs = {"axes": self.axes}
+
+
+# Correct: There is mins axis.
+class TestUnsqueeze2Op1(TestUnsqueeze2Op):
+    def init_test_case(self):
+        self.ori_shape = (20, 5)
+        self.axes = (0, -2)
+        self.new_shape = (1, 20, 1, 5)
+
+
+# Correct: No axes input.
+class TestUnsqueeze2Op2(TestUnsqueeze2Op):
+    def init_test_case(self):
+        self.ori_shape = (20, 5)
+        self.axes = ()
+        self.new_shape = (1, 20, 5)
+
+
+# Correct: Just part of axes be squeezed. 
+class TestUnsqueeze2Op3(TestUnsqueeze2Op):
+    def init_test_case(self):
+        self.ori_shape = (6, 5, 1, 4)
+        self.axes = (1, -1)
+        self.new_shape = (6, 1, 5, 1, 4, 1)
+
+
+if __name__ == "__main__":
+    unittest.main()