fix range op crash in dygraph xpu place (#30469)
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18ecd433f5
commit
5e5c2827a3
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifdef PADDLE_WITH_XPU
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#include "paddle/fluid/operators/range_op.h"
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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class XPURangeKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* start_t = context.Input<framework::Tensor>("Start");
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auto* end_t = context.Input<framework::Tensor>("End");
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auto* step_t = context.Input<framework::Tensor>("Step");
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auto* out = context.Output<framework::Tensor>("Out");
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framework::Tensor n;
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framework::TensorCopy(*start_t, platform::CPUPlace(), &n);
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T start = n.data<T>()[0];
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framework::TensorCopy(*end_t, platform::CPUPlace(), &n);
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T end = n.data<T>()[0];
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framework::TensorCopy(*step_t, platform::CPUPlace(), &n);
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T step = n.data<T>()[0];
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int64_t size = 0;
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GetSize(start, end, step, &size);
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out->Resize(framework::make_ddim({size}));
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T* out_data = out->mutable_data<T>(context.GetPlace());
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framework::Tensor out_cpu;
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T* out_cpu_data_ptr =
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out_cpu.mutable_data<T>(platform::CPUPlace(), out->numel() * sizeof(T));
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T value = start;
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for (int64_t i = 0; i < size; ++i) {
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out_cpu_data_ptr[i] = value;
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value += step;
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}
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int ret = xpu_memcpy(out_data, out_cpu_data_ptr, out->numel() * sizeof(T),
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XPUMemcpyKind::XPU_HOST_TO_DEVICE);
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PADDLE_ENFORCE_EQ(ret, XPU_SUCCESS,
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platform::errors::External("XPU xpu_memcpy return wrong "
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"value[%d %s]",
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ret, XPUAPIErrorMsg[ret]));
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_XPU_KERNEL(range, ops::XPURangeKernel<int>,
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ops::XPURangeKernel<int64_t>, ops::XPURangeKernel<float>,
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ops::XPURangeKernel<double>);
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#endif // PADDLE_WITH_XPU
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@ -0,0 +1,76 @@
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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import paddle
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import numpy as np
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import sys
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sys.path.append("..")
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from op_test_xpu import XPUOpTest
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paddle.enable_static()
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class TestRangeOp(XPUOpTest):
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def setUp(self):
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self.op_type = "range"
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self.init_config()
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self.inputs = {
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'Start': np.array([self.case[0]]).astype(self.dtype),
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'End': np.array([self.case[1]]).astype(self.dtype),
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'Step': np.array([self.case[2]]).astype(self.dtype)
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}
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self.outputs = {
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'Out': np.arange(self.case[0], self.case[1],
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self.case[2]).astype(self.dtype)
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}
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def init_config(self):
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self.dtype = np.float32
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self.case = (0, 1, 0.2)
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def test_check_output(self):
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place = paddle.XPUPlace(0)
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self.check_output_with_place(place, check_dygraph=False)
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class TestFloatRangeOpCase0(TestRangeOp):
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def init_config(self):
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self.dtype = np.float32
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self.case = (0, 5, 1)
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class TestInt32RangeOpCase0(TestRangeOp):
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def init_config(self):
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self.dtype = np.int32
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self.case = (0, 5, 2)
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class TestInt32RangeOpCase1(TestRangeOp):
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def init_config(self):
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self.dtype = np.int32
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self.case = (10, 1, -2)
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class TestInt32RangeOpCase2(TestRangeOp):
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def init_config(self):
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self.dtype = np.int32
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self.case = (-1, -10, -2)
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if __name__ == "__main__":
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unittest.main()
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