[MLU]add mlu kernel for sqrt op (#43326)

paddle/fluid/operators/activation_op_mlu.cc

@@ -108,6 +108,43 @@ class ActivationGradMLUKernelV3 : public framework::OpKernel<T> {
   }
 };
 
+// For sqrt
+template <typename T>
+class SqrtMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* x = ctx.Input<Tensor>("X");
+    auto* out = ctx.Output<Tensor>("Out");
+    auto place = ctx.GetPlace();
+
+    out->mutable_data<T>(place);
+
+    MLUCnnlTensorDesc input_desc(*x);
+    MLUCnnlTensorDesc output_desc(*out);
+
+    cnnlComputationPreference_t prefer = CNNL_COMPUTATION_FAST;
+    MLUCnnl::Sqrt(ctx, prefer, input_desc.get(), GetBasePtr(x),
+                  output_desc.get(), GetBasePtr(out));
+  }
+};
+
+template <typename T>
+class SqrtGradMLUKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* out = ctx.Input<Tensor>("Out");
+    auto* dout = ctx.Input<Tensor>(framework::GradVarName("Out"));
+    auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
+    auto place = ctx.GetPlace();
+
+    dx->mutable_data<T>(place);
+
+    MLUCnnlTensorDesc data_desc(*out);
+    MLUCnnl::SqrtGrad(ctx, data_desc.get(), GetBasePtr(out), GetBasePtr(dout),
+                      GetBasePtr(dx));
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
@@ -170,3 +207,9 @@ REGISTER_OP_MLU_KERNEL(
     ops::ActivationGradMLUKernelV1<CNNL_ACTIVATION_LEAKYRELU, float>,
     ops::ActivationGradMLUKernelV1<CNNL_ACTIVATION_LEAKYRELU,
                                    paddle::platform::float16>);
+
+// sqrt
+REGISTER_OP_MLU_KERNEL(sqrt, ops::SqrtMLUKernel<float>,
+                       ops::SqrtMLUKernel<paddle::platform::float16>);
+REGISTER_OP_MLU_KERNEL(sqrt_grad, ops::SqrtGradMLUKernel<float>,
+                       ops::SqrtGradMLUKernel<paddle::platform::float16>);

python/paddle/fluid/tests/unittests/mlu/test_sqrt_op_mlu.py

+#   Copyright (c) 2022 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 unittest
+import numpy as np
+import sys
+
+sys.path.append('..')
+from op_test import OpTest
+import paddle.fluid.core as core
+import paddle.fluid as fluid
+from paddle.fluid import compiler, Program, program_guard
+import paddle
+import paddle.nn.functional as F
+
+paddle.enable_static()
+np.random.seed(10)
+
+
+class TestSqrt(OpTest):
+
+    def setUp(self):
+        self.op_type = "sqrt"
+        self.dtype = 'float32'
+        self.set_mlu()
+        self.python_api = paddle.sqrt
+
+        np.random.seed(1023)
+        x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
+        out = np.sqrt(x)
+
+        self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
+        self.outputs = {'Out': out}
+
+    def set_mlu(self):
+        self.__class__.use_mlu = True
+        self.place = paddle.device.MLUPlace(0)
+
+    def test_check_grad(self):
+        self.check_grad_with_place(self.place, ['X'], 'Out', check_eager=False)
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+class TestSqrtHalf(OpTest):
+
+    def setUp(self):
+        self.op_type = "sqrt"
+        self.dtype = 'float16'
+        self.set_mlu()
+        self.python_api = paddle.sqrt
+
+        np.random.seed(1023)
+        x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
+        out = np.sqrt(x)
+
+        self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
+        self.outputs = {'Out': out}
+
+    def set_mlu(self):
+        self.__class__.use_mlu = True
+        self.place = paddle.device.MLUPlace(0)
+
+    def test_check_grad(self):
+        self.check_grad_with_place(self.place, ['X'],
+                                   'Out',
+                                   check_eager=False,
+                                   max_relative_error=0.85)
+
+    def test_check_output(self):
+        self.check_output_with_place(self.place)
+
+
+if __name__ == "__main__":
+    unittest.main()