sum op (#39165)

Author: joeqiao12

paddle/fluid/operators/sum_op_mlu.cc

@@ -0,0 +1,74 @@
+/* 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. */
+
+#include "paddle/fluid/operators/sum_op.h"
+#include "paddle/fluid/operators/mlu/mlu_baseop.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+
+template <typename DeviceContext, typename T>
+class SumMLUKernel : public framework::OpKernel<T> {
+ public:
+ void Compute(const framework::ExecutionContext &ctx) const override {
+ auto out_var = ctx.OutputVar("Out");
+ if (out_var->IsType<framework::LoDTensor>()) {
+ // init
+ auto *out = out_var->GetMutable<framework::LoDTensor>();
+ auto ins = ctx.MultiInput<Tensor>("X");
+ out->mutable_data<T>(ctx.GetPlace());
+ auto place = ctx.GetPlace();
+ int ins_size = static_cast<int>(ins.size());
+ if (ins_size == 1) {
+ TensorCopy(*ins[0], place, out);
+ return;
+ }
+
+ // MLU shoul do sth
+ std::vector<const void *> inputs;
+ std::vector<MLUCnnlTensorDesc> input_descs;
+ std::vector<cnnlTensorDescriptor_t> desc_vector;
+ for (int i = 0; i < ins_size; i++) {
+ input_descs.emplace_back(MLUCnnlTensorDesc(
+ *ins[i], CNNL_LAYOUT_ARRAY, ToCnnlDataType(ins[i]->type())));
+ desc_vector.push_back(input_descs.back().get());
+ inputs.push_back(GetBasePtr(ins[i]));
+ }
+ // init out tensors
+ MLUCnnlTensorDesc output_desc(*out, CNNL_LAYOUT_ARRAY,
+ ToCnnlDataType(out->type()));
+ uint32_t ins_size_t = static_cast<uint32_t>(ins_size);
+ MLUCnnl::AddN(ctx, ins_size_t, desc_vector.data(), inputs.data(),
+ output_desc.get(), GetBasePtr(out));
+
+ } else {
+ PADDLE_THROW(platform::errors::InvalidArgument(
+ "Expected type of Output(out) must be Tensor or But got "
+ "unsupport type: %s.",
+ framework::ToTypeName(out_var->Type())));
+ }
+ }
+};
+
+} // namespace operators
+} // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OP_MLU_KERNEL(
+ sum, ops::SumMLUKernel<paddle::platform::MLUDeviceContext, float>,
+ ops::SumMLUKernel<paddle::platform::MLUDeviceContext,
+ paddle::platform::float16>);

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

@@ -0,0 +1,116 @@
+# 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 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
+
+paddle.enable_static()
+SEED = 2021
+
+
+class TestSum1(OpTest):
+ def setUp(self):
+ self.set_mlu()
+ self.init_dtype()
+ self.op_type = "sum"
+ self.place = paddle.MLUPlace(0)
+
+ x0 = np.random.random((3, 40)).astype(self.dtype)
+ x1 = np.random.random((3, 40)).astype(self.dtype)
+ x2 = np.random.random((3, 40)).astype(self.dtype)
+ self.inputs = {'X': [("x0", x0), ("x1", x1), ("x2", x2)]}
+ y = x0 + x1 + x2
+ self.outputs = {'Out': y}
+
+ self.attrs = {'use_mkldnn': False}
+
+ def init_dtype(self):
+ self.dtype = np.float32
+
+ def set_mlu(self):
+ self.__class__.use_mlu = True
+
+ def test_check_output(self):
+ self.check_output_with_place(self.place)
+
+
+class TestSum2(OpTest):
+ def setUp(self):
+ self.set_mlu()
+ self.init_dtype()
+ self.op_type = "sum"
+ self.place = paddle.MLUPlace(0)
+
+ x0 = np.random.random((3, 3)).astype(self.dtype)
+ x1 = np.random.random((3, 3)).astype(self.dtype)
+ x2 = np.random.random((3, 3)).astype(self.dtype)
+ x3 = np.random.random((3, 3)).astype(self.dtype)
+ self.inputs = {'X': [("x0", x0), ("x1", x1), ("x2", x2), ("x3", x3)]}
+ # There will be a problem if just using `y=x0+x1+x2+x3` to calculate the
+ # summation result as the reference standard result. The reason is that 
+ # numpy's fp16 data has precision loss when doing `add` operation.
+ # For example, the results of `x0+x1+x2+x3` is different from that of
+ # `x3+x2+x1+x0` if the dtype is fp16.
+ # Therefore, converting the input to fp32 for calculation.
+ y = (x0.astype(np.float32) + x1.astype(np.float32) +
+ x2.astype(np.float32) + x3.astype(np.float32)).astype(self.dtype)
+ self.outputs = {'Out': y}
+
+ self.attrs = {'use_mkldnn': False}
+
+ def init_dtype(self):
+ self.dtype = np.float16
+
+ def set_mlu(self):
+ self.__class__.use_mlu = True
+
+ def test_check_output(self):
+ self.check_output_with_place(self.place)
+
+
+class TestSum3(OpTest):
+ def setUp(self):
+ self.set_mlu()
+ self.init_dtype()
+ self.op_type = "sum"
+ self.place = paddle.MLUPlace(0)
+
+ x0 = np.random.random((3, 3)).astype(self.dtype)
+
+ self.inputs = {'X': [("x0", x0)]}
+ y = x0
+ self.outputs = {'Out': y}
+
+ self.attrs = {'use_mkldnn': False}
+
+ def init_dtype(self):
+ self.dtype = np.float16
+
+ def set_mlu(self):
+ self.__class__.use_mlu = True
+
+ def test_check_output(self):
+ self.check_output_with_place(self.place)
+
+
+if __name__ == '__main__':
+ unittest.main()