未验证 提交 2900f3ee 编写于 作者: Z zhupengyang 提交者: GitHub

[NPU] add sqrt op bridge and unit test (#2515)

test=develop
上级 5fac0949
...@@ -20,6 +20,7 @@ lite_cc_library(npu_bridge_concat_op SRCS concat_op.cc DEPS ${npu_bridge_deps}) ...@@ -20,6 +20,7 @@ lite_cc_library(npu_bridge_concat_op SRCS concat_op.cc DEPS ${npu_bridge_deps})
lite_cc_library(npu_bridge_shuffle_channel_op SRCS shuffle_channel_op.cc DEPS ${npu_bridge_deps}) lite_cc_library(npu_bridge_shuffle_channel_op SRCS shuffle_channel_op.cc DEPS ${npu_bridge_deps})
lite_cc_library(npu_bridge_pad2d_op SRCS pad2d_op.cc DEPS ${npu_bridge_deps}) lite_cc_library(npu_bridge_pad2d_op SRCS pad2d_op.cc DEPS ${npu_bridge_deps})
lite_cc_library(npu_bridge_square_op SRCS square_op.cc DEPS ${npu_bridge_deps}) lite_cc_library(npu_bridge_square_op SRCS square_op.cc DEPS ${npu_bridge_deps})
lite_cc_library(npu_bridge_sqrt_op SRCS sqrt_op.cc DEPS ${npu_bridge_deps})
set(npu_bridges set(npu_bridges
npu_bridge_registry npu_bridge_registry
...@@ -41,6 +42,7 @@ set(npu_bridges ...@@ -41,6 +42,7 @@ set(npu_bridges
npu_bridge_shuffle_channel_op npu_bridge_shuffle_channel_op
npu_bridge_pad2d_op npu_bridge_pad2d_op
npu_bridge_square_op npu_bridge_square_op
npu_bridge_sqrt_op
CACHE INTERNAL "npu_bridges") CACHE INTERNAL "npu_bridges")
set(npu_bridge_test_deps ${npu_bridges} ${npu_kernels} ${ops}) set(npu_bridge_test_deps ${npu_bridges} ${npu_kernels} ${ops})
...@@ -63,5 +65,6 @@ lite_cc_test(test_npu_bridge_concat_op SRCS concat_op_test.cc test_helper.cc DEP ...@@ -63,5 +65,6 @@ lite_cc_test(test_npu_bridge_concat_op SRCS concat_op_test.cc test_helper.cc DEP
lite_cc_test(test_npu_bridge_shuffle_channel_op SRCS shuffle_channel_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps}) lite_cc_test(test_npu_bridge_shuffle_channel_op SRCS shuffle_channel_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps})
lite_cc_test(test_npu_bridge_pad2d_op SRCS pad2d_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps}) lite_cc_test(test_npu_bridge_pad2d_op SRCS pad2d_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps})
lite_cc_test(test_npu_bridge_square_op SRCS square_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps}) lite_cc_test(test_npu_bridge_square_op SRCS square_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps})
lite_cc_test(test_npu_bridge_sqrt_op SRCS sqrt_op_test.cc test_helper.cc DEPS ${npu_bridge_test_deps})
message(STATUS "+++++ npu_bridges: ${npu_bridges}") message(STATUS "+++++ npu_bridges: ${npu_bridges}")
// Copyright (c) 2019 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 "lite/backends/npu/builder.h"
#include "lite/kernels/npu/bridges/registry.h"
namespace paddle {
namespace lite {
namespace kernels {
namespace npu {
namespace bridges {
node_map_type SqrtConverter(const std::shared_ptr<lite::OpLite> sqrt_op,
const node_map_type& inputs_map) {
auto scope = sqrt_op->scope();
auto op_info = sqrt_op->op_info();
auto op_type = op_info->Type();
auto unique_op_type = lite::npu::UniqueName(op_type);
LOG(INFO) << "[NPU] Converting " + op_type + "...";
std::shared_ptr<ge::op::Sqrt> sqrt_node =
std::make_shared<ge::op::Sqrt>(unique_op_type);
auto x_var_name = op_info->Input("X").front();
CHECK(inputs_map.count(x_var_name));
sqrt_node->set_input_x(*inputs_map.at(x_var_name));
lite::npu::OpList::Global().add(inputs_map.at(x_var_name));
lite::npu::OpList::Global().add(sqrt_node);
node_map_type outputs_map;
outputs_map[op_info->Output("Out").front()] = sqrt_node;
return outputs_map;
}
} // namespace bridges
} // namespace npu
} // namespace kernels
} // namespace lite
} // namespace paddle
REGISTER_NPU_BRIDGE(sqrt, paddle::lite::kernels::npu::bridges::SqrtConverter);
// Copyright (c) 2019 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 <gtest/gtest.h>
#include <cmath>
#include "lite/core/op_registry.h"
#include "lite/kernels/npu/bridges/registry.h"
#include "lite/kernels/npu/bridges/test_helper.h"
#include "lite/operators/activation_ops.h"
namespace paddle {
namespace lite {
namespace kernels {
namespace npu {
namespace bridges {
template <typename dtype>
void sqrt_ref(const std::shared_ptr<operators::ActivationOp> op) {
Scope* scope = op->scope();
const OpInfo* op_info = op->op_info();
auto x = scope->FindTensor("x");
auto out = scope->FindMutableTensor("out_ref");
out->Resize(x->dims());
auto x_data = x->data<dtype>();
auto out_data = out->mutable_data<dtype>();
for (size_t i = 0; i < x->numel(); i++) {
out_data[i] = std::sqrtf(x_data[i]);
}
}
void test_sqrt(const std::vector<int64_t>& input_shape) {
// prepare input&output variables
Scope scope;
std::string x_var_name = "x";
std::string out_var_name = "out";
std::string out_ref_var_name = "out_ref";
auto* x = scope.NewTensor(x_var_name);
auto* out = scope.NewTensor(out_var_name);
auto* out_ref = scope.NewTensor(out_ref_var_name);
x->Resize(input_shape);
// initialize input&output data
FillTensor<float>(x, 0, 5);
// initialize op desc
cpp::OpDesc opdesc;
opdesc.SetType("sqrt");
opdesc.SetInput("X", {x_var_name});
opdesc.SetOutput("Out", {out_var_name});
// create and convert op to NPU model, then run it on NPU
auto op = CreateOp<operators::ActivationOp>(opdesc, &scope);
LauchOp(op, {x_var_name}, {out_var_name});
// execute reference implementation and save to output tensor
sqrt_ref<float>(op);
// compare results
auto* out_data = out->mutable_data<float>();
auto* out_ref_data = out_ref->mutable_data<float>();
for (int i = 0; i < out->dims().production(); i++) {
EXPECT_NEAR(out_data[i], out_ref_data[i], 1e-2);
}
}
TEST(NPUBridges, sqrt) {
test_sqrt({2});
test_sqrt({2, 3});
test_sqrt({1, 2, 3, 4});
test_sqrt({5, 6, 7, 8});
}
} // namespace bridges
} // namespace npu
} // namespace kernels
} // namespace lite
} // namespace paddle
USE_LITE_OP(sqrt);
USE_NPU_BRIDGE(sqrt);
...@@ -117,6 +117,7 @@ REGISTER_LITE_OP(log, paddle::lite::operators::ActivationOp); ...@@ -117,6 +117,7 @@ REGISTER_LITE_OP(log, paddle::lite::operators::ActivationOp);
REGISTER_LITE_OP(exp, paddle::lite::operators::ActivationOp); REGISTER_LITE_OP(exp, paddle::lite::operators::ActivationOp);
REGISTER_LITE_OP(floor, paddle::lite::operators::ActivationOp); REGISTER_LITE_OP(floor, paddle::lite::operators::ActivationOp);
REGISTER_LITE_OP(hard_sigmoid, paddle::lite::operators::ActivationOp); REGISTER_LITE_OP(hard_sigmoid, paddle::lite::operators::ActivationOp);
REGISTER_LITE_OP(sqrt, paddle::lite::operators::ActivationOp);
REGISTER_LITE_OP(rsqrt, paddle::lite::operators::ActivationOp); REGISTER_LITE_OP(rsqrt, paddle::lite::operators::ActivationOp);
REGISTER_LITE_OP(softsign, paddle::lite::operators::ActivationOp); REGISTER_LITE_OP(softsign, paddle::lite::operators::ActivationOp);
......
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