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Commit 3d53e58a authored by fenglei.tian's avatar fenglei.tian
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merge and resolve conflict with origin master

parents 39dc384d b5467550
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Showing with 407 additions and 194 deletions
src/ngraph/runtime/cpu/cpu_emitter.cpp
View file @ 3d53e58a
......@@ -3279,6 +3279,45 @@ namespace ngraph
<< to_string(sigmoid_index) << ");\n";
}
template <>
void CPU_Emitter::EMITTER_DECL(ngraph::op::SigmoidBackprop)
{
auto input_shape = args[0].get_shape();
auto delta_shape = args[1].get_shape();
auto result_shape = out[0].get_shape();
int input_1d_size = static_cast<int>(shape_size(input_shape));
int delta_1d_size = static_cast<int>(shape_size(delta_shape));
int result_1d_size = static_cast<int>(shape_size(result_shape));
auto& mkldnn_emitter = external_function->get_mkldnn_emitter();
auto input_desc = mkldnn::memory::desc(
{input_1d_size},
mkldnn_utils::get_mkldnn_data_type(args[0].get_element_type()),
mkldnn::memory::format::x);
auto delta_desc = mkldnn::memory::desc(
{delta_1d_size},
mkldnn_utils::get_mkldnn_data_type(args[1].get_element_type()),
mkldnn::memory::format::x);
auto result_desc = mkldnn::memory::desc(
{result_1d_size},
mkldnn_utils::get_mkldnn_data_type(out[0].get_element_type()),
mkldnn::memory::format::x);
size_t sigmoid_index =
mkldnn_emitter->build_sigmoid_backward(input_desc, delta_desc, result_desc);
auto& deps = mkldnn_emitter->get_primitive_deps(sigmoid_index);
writer << "cpu::mkldnn_utils::set_memory_ptr(ctx, " << to_string(deps[0]) << ", "
<< args[0].get_name() << ");\n";
writer << "cpu::mkldnn_utils::set_memory_ptr(ctx, " << to_string(deps[1]) << ", "
<< args[1].get_name() << ");\n";
writer << "cpu::mkldnn_utils::set_memory_ptr(ctx, " << to_string(deps[2]) << ", "
<< out[0].get_name() << ");\n";
writer << "cpu::mkldnn_utils::mkldnn_invoke_primitive(ctx, "
<< to_string(sigmoid_index) << ");\n";
}
template <>
void CPU_Emitter::EMITTER_DECL(ngraph::op::Softmax)
{
......
src/ngraph/runtime/cpu/cpu_external_function.cpp
View file @ 3d53e58a
......@@ -252,6 +252,7 @@ static const runtime::cpu::OpMap dispatcher{
{TI(ngraph::op::ReluBackprop), &runtime::cpu::CPU_Emitter::emit<op::ReluBackprop>},
{TI(ngraph::op::Sigmoid), &runtime::cpu::CPU_Emitter::emit<op::Sigmoid>},
{TI(ngraph::op::Softmax), &runtime::cpu::CPU_Emitter::emit<op::Softmax>},
{TI(ngraph::op::SigmoidBackprop), &runtime::cpu::CPU_Emitter::emit<op::SigmoidBackprop>},
};
runtime::cpu::CPU_ExternalFunction::CPU_ExternalFunction(
......
src/ngraph/runtime/cpu/mkldnn_emitter.cpp
View file @ 3d53e58a
......@@ -513,6 +513,32 @@ size_t MKLDNNEmitter::build_sigmoid_forward(const mkldnn::memory::desc& input_de
return primitive_index;
}
size_t MKLDNNEmitter::build_sigmoid_backward(const mkldnn::memory::desc& input_desc,
const mkldnn::memory::desc& delta_desc,
const mkldnn::memory::desc& result_desc)
{
size_t input_index = build_memory_primitive(input_desc);
size_t delta_index = build_memory_primitive(delta_desc);
size_t result_index = build_memory_primitive(result_desc);
// sigmoid forward primitive desc
mkldnn::eltwise_forward::primitive_desc sigmoid_fwd_pd =
mkldnn::eltwise_forward::primitive_desc(
{mkldnn::prop_kind::forward, mkldnn::algorithm::eltwise_logistic, input_desc, 0, 0},
mkldnn_utils::global_cpu_engine);
size_t primitive_index = insert_primitive(new mkldnn::eltwise_backward(
{{mkldnn::algorithm::eltwise_logistic, delta_desc, input_desc, 0, 0},
mkldnn_utils::global_cpu_engine,
sigmoid_fwd_pd},
*m_mkldnn_primitives[input_index],
*m_mkldnn_primitives[delta_index],
*m_mkldnn_primitives[result_index]));
m_primitive_deps[primitive_index] = {input_index, delta_index, result_index};
return primitive_index;
}
size_t MKLDNNEmitter::build_elementwise_add(
const mkldnn::memory::desc& input0_data_desc,
const mkldnn::memory::desc& input1_data_desc,
......
src/ngraph/runtime/cpu/mkldnn_emitter.hpp
View file @ 3d53e58a
......@@ -153,6 +153,10 @@ namespace ngraph
size_t build_sigmoid_forward(const mkldnn::memory::desc& input_desc,
const mkldnn::memory::desc& result_desc);
size_t build_sigmoid_backward(const mkldnn::memory::desc& input_desc,
const mkldnn::memory::desc& delta_desc,
const mkldnn::memory::desc& result_desc);
size_t build_elementwise_add(
const mkldnn::memory::desc& input0_data_desc,
const mkldnn::memory::desc& input1_data_desc,
......
src/ngraph/runtime/cpu/ops/sigmoid.cpp
View file @ 3d53e58a
......@@ -35,3 +35,24 @@ ngraph::op::Sigmoid::Sigmoid(std::shared_ptr<ngraph::Node> input)
{
add_output(input->get_element_type(), m_shape_input);
}
ngraph::op::SigmoidBackprop::SigmoidBackprop(std::shared_ptr<Node> arg, std::shared_ptr<Node> delta)
: RequiresTensorViewArgs("SigmoidBackprop", {arg, delta})
{
if (arg->get_element_type() != delta->get_element_type())
{
throw ngraph_error("Argument and delta element types for Sigmoid backprop do not match");
}
if (arg->get_shape() != delta->get_shape())
{
throw ngraph_error("Argument and delta shape for Sigmoid backprop do not match");
}
set_value_type_checked(delta->get_element_type(), delta->get_shape());
}
void ngraph::op::Sigmoid::generate_adjoints(ngraph::autodiff::Adjoints& adjoints,
const std::shared_ptr<Node>& delta)
{
auto backprop = std::make_shared<op::SigmoidBackprop>(get_input_op(0), delta);
adjoints.add_delta(get_input_op(0), backprop);
}
src/ngraph/runtime/cpu/ops/sigmoid.hpp
View file @ 3d53e58a
......@@ -17,6 +17,7 @@
#pragma once
#include "ngraph/ops/util/requires_tensor_view_args.hpp"
#include "ngraph/util.hpp"
namespace ngraph
{
......@@ -29,9 +30,32 @@ namespace ngraph
Shape get_input_shape() const { return m_shape_input; }
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override;
virtual void generate_adjoints(autodiff::Adjoints& adjoints,
const std::shared_ptr<Node>& delta) override;
private:
Shape m_shape_input;
};
/// \brief Elementwise SigmoidBackprop operation.
///
class SigmoidBackprop : public util::RequiresTensorViewArgs
{
public:
/// \brief Constructs a SigmoidBackprop operation.
///
/// \param arg Node that produces the Sigmoid forward input tensor.
SigmoidBackprop(std::shared_ptr<ngraph::Node> arg, std::shared_ptr<ngraph::Node> delta);
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override
{
if (new_args.size() != 2)
{
throw ngraph_error("Incorrect number of new arguments");
}
return std::make_shared<SigmoidBackprop>(new_args.at(0), new_args.at(1));
}
};
}
}
src/ngraph/runtime/cpu/pass/cpu_assignment.cpp
View file @ 3d53e58a
......@@ -316,6 +316,19 @@ namespace ngraph
}
}
template <>
void CPUAssignment::ASSIGN_DECL(ngraph::op::SigmoidBackprop)
{
auto sigmoid = static_cast<op::SigmoidBackprop*>(node);
if (node->get_input_element_type(0) == element::f32)
{
auto op_annotations =
std::make_shared<ngraph::runtime::cpu::CPUOpAnnotations>();
op_annotations->set_mkldnn_op(true);
sigmoid->set_op_annotations(op_annotations);
}
}
template <>
void CPUAssignment::ASSIGN_DECL(ngraph::op::ReluBackprop)
{
......@@ -386,6 +399,8 @@ static const runtime::cpu::pass::AssignOpMap s_dispatcher{
{TI(ngraph::op::ReluBackprop),
&runtime::cpu::pass::CPUAssignment::assign<ngraph::op::ReluBackprop>},
{TI(ngraph::op::Sigmoid), &runtime::cpu::pass::CPUAssignment::assign<ngraph::op::Sigmoid>},
{TI(ngraph::op::SigmoidBackprop),
&runtime::cpu::pass::CPUAssignment::assign<ngraph::op::SigmoidBackprop>},
};
bool runtime::cpu::pass::CPUAssignment::run_on_call_graph(
......
src/ngraph/runtime/cpu/pass/cpu_fusion.cpp
View file @ 3d53e58a
......@@ -568,6 +568,57 @@ void ngraph::runtime::cpu::pass::CPUFusion::construct_sigmoid()
this->add_matcher(m);
}
void ngraph::runtime::cpu::pass::CPUFusion::construct_sigmoid_bprop()
{
//construct variance
auto input = std::make_shared<pattern::op::Label>(element::f32, Shape{3, 4});
auto neg_input = std::make_shared<op::Negative>(input);
auto exp_neg_input = std::make_shared<op::Exp>(neg_input);
// broadcast input
auto constant = std::make_shared<pattern::op::Label>(element::f32, Shape{});
auto broadcast_constant = std::make_shared<op::Broadcast>(constant, Shape{3, 4}, AxisSet{0, 1});
auto add_exp = std::make_shared<op::Add>(exp_neg_input, broadcast_constant);
// //auto divide_1_over_exp = std::make_shared<op::Divide>(broadcast_constant, add_exp);
auto sigmoid_fwd = std::make_shared<pattern::op::Label>(element::f32, Shape{3, 4});
auto delta = std::make_shared<pattern::op::Label>(element::f32, Shape{3, 4});
auto neg_delta = std::make_shared<op::Negative>(delta);
auto multiply_sigmoid_delta = std::make_shared<op::Multiply>(sigmoid_fwd, neg_delta);
auto divide_2 = std::make_shared<op::Divide>(multiply_sigmoid_delta, add_exp);
auto multiply_2 = std::make_shared<op::Multiply>(divide_2, exp_neg_input);
auto negtive_2 = std::make_shared<op::Negative>(multiply_2);
//Define a call back that needs to called once the DFG matches the pattern
ngraph::pattern::gr_callback_fn callback =
[input, delta](pattern::Matcher& m) -> std::shared_ptr<Node> {
NGRAPH_DEBUG << "In a callback for construct_fprop_sigmoid pattern against "
<< m.match_root()->get_name();
auto pattern_map = m.get_pattern_map();
if (m.match_root()->get_element_type() != element::f32)
{
NGRAPH_DEBUG << "mpattern = " << m.match_root()->get_name() << " type is not float!";
return nullptr;
}
if (m.match_root()->get_shape().size() != pattern_map[input]->get_shape().size())
{
NGRAPH_DEBUG << "mpattern = " << m.match_root()->get_name()
<< "input= " << pattern_map[input]->get_name() << "size dont match!";
return nullptr;
}
auto dsigmoid =
std::make_shared<op::SigmoidBackprop>(pattern_map[input], pattern_map[delta]);
return dsigmoid;
};
auto m = std::make_shared<ngraph::pattern::Matcher>(negtive_2, callback);
this->add_matcher(m);
}
void ngraph::runtime::cpu::pass::CPUFusion::construct_conv_bias()
{
Shape shape{2, 2, 1, 1};
......
src/ngraph/runtime/cpu/pass/cpu_fusion.hpp
View file @ 3d53e58a
......@@ -44,6 +44,7 @@ public:
construct_zero_padded_reshaped_conv();
construct_zero_padded_conv();
construct_sigmoid();
construct_sigmoid_bprop();
construct_conv_bias();
}
......@@ -53,6 +54,7 @@ private:
void construct_conv_bias();
void construct_fprop_bn();
void construct_sigmoid();
void construct_sigmoid_bprop();
void construct_zero_padded_reshaped_conv();
void construct_zero_padded_conv();
};
src/ngraph/runtime/cpu/pass/cpu_layout.cpp
View file @ 3d53e58a
......@@ -960,6 +960,29 @@ namespace ngraph
}
}
template <>
void CPULayout::LAYOUT_DECL(ngraph::op::SigmoidBackprop)
{
if (runtime::cpu::mkldnn_utils::use_mkldnn_kernel(node.get()))
{
auto input_layout =
runtime::cpu::mkldnn_utils::get_input_mkldnn_format(node.get(), 0);
vector<memory::format> prim_input_formats;
vector<memory::format> prim_output_formats;
//ensure delta and input have same layout
prim_input_formats.push_back(input_layout);
prim_input_formats.push_back(input_layout);
prim_output_formats.push_back(input_layout);
node =
insert_input_conversions(external_function, node, prim_input_formats);
set_output_layouts(node, prim_output_formats);
}
else
{
set_default_layouts(external_function, node);
}
}
template <>
void CPULayout::LAYOUT_DECL(ngraph::op::ReluBackprop)
{
......@@ -1095,6 +1118,8 @@ static const runtime::cpu::pass::LayoutOpMap s_dispatcher{
{TI(ngraph::op::ReluBackprop),
&runtime::cpu::pass::CPULayout::layout<ngraph::op::ReluBackprop>},
{TI(ngraph::op::Sigmoid), &runtime::cpu::pass::CPULayout::layout<ngraph::op::Sigmoid>},
{TI(ngraph::op::SigmoidBackprop),
&runtime::cpu::pass::CPULayout::layout<ngraph::op::SigmoidBackprop>},
};
bool runtime::cpu::pass::CPULayout::run_on_call_graph(const std::list<std::shared_ptr<Node>>& nodes)
......
src/ngraph/runtime/gpu/gpu_cuda_context_manager.cpp
View file @ 3d53e58a
......@@ -19,25 +19,18 @@
#include "ngraph/runtime/gpu/gpu_cuda_context_manager.hpp"
namespace ngraph
using namespace ngraph;
runtime::gpu::CudaContextManager& runtime::gpu::CudaContextManager::instance()
{
namespace runtime
{
namespace gpu
{
CudaContextManager& CudaContextManager::instance()
{
static CudaContextManager manager;
return manager;
}
static CudaContextManager manager;
return manager;
}
CudaContextManager::CudaContextManager()
{
CUDA_SAFE_CALL(cuInit(0));
CUDA_SAFE_CALL(cuDeviceGet(&m_device, 0));
CUDA_SAFE_CALL(cuCtxCreate(&m_context, 0, m_device));
m_context_ptr = std::make_shared<CUcontext>(m_context);
}
}
}
runtime::gpu::CudaContextManager::CudaContextManager()
{
CUDA_SAFE_CALL(cuInit(0));
CUDA_SAFE_CALL(cuDeviceGet(&m_device, 0));
CUDA_SAFE_CALL(cuCtxCreate(&m_context, 0, m_device));
m_context_ptr = std::make_shared<CUcontext>(m_context);
}
src/ngraph/runtime/gpu/gpu_cuda_function_builder.cpp
View file @ 3d53e58a
......@@ -20,46 +20,39 @@
#include "ngraph/runtime/gpu/gpu_cuda_function_builder.hpp"
#include "ngraph/runtime/gpu/gpu_util.hpp"
namespace ngraph
using namespace ngraph;
std::shared_ptr<CUfunction> runtime::gpu::CudaFunctionBuilder::get(const std::string& name,
const std::string& kernel,
int number_of_options,
const char** options)
{
namespace runtime
{
namespace gpu
{
std::shared_ptr<CUfunction> CudaFunctionBuilder::get(const std::string& name,
const std::string& kernel,
int number_of_options,
const char** options)
{
nvrtcProgram prog;
NVRTC_SAFE_CALL(nvrtcCreateProgram(&prog,
kernel.c_str(),
"op.cu",
0, // numHeaders
NULL, // headers
NULL)); // includeNames
nvrtcProgram prog;
NVRTC_SAFE_CALL(nvrtcCreateProgram(&prog,
kernel.c_str(),
"op.cu",
0, // numHeaders
NULL, // headers
NULL)); // includeNames
nvrtcResult compile_result = nvrtcCompileProgram(prog, number_of_options, options);
nvrtcResult compile_result = nvrtcCompileProgram(prog, number_of_options, options);
if (compile_result != NVRTC_SUCCESS)
{
throw std::runtime_error("compile error: \n" + kernel + "\n options");
}
if (compile_result != NVRTC_SUCCESS)
{
throw std::runtime_error("compile error: \n" + kernel + "\n options");
}
size_t ptx_size;
NVRTC_SAFE_CALL(nvrtcGetPTXSize(prog, &ptx_size));
char* ptx = new char[ptx_size];
NVRTC_SAFE_CALL(nvrtcGetPTX(
prog,
size_t ptx_size;
NVRTC_SAFE_CALL(nvrtcGetPTXSize(prog, &ptx_size));
char* ptx = new char[ptx_size];
NVRTC_SAFE_CALL(
nvrtcGetPTX(prog,
ptx)); // Load the generated PTX and get a handle to the parent kernel.
NVRTC_SAFE_CALL(nvrtcDestroyProgram(&prog)); // Destroy the program.
NVRTC_SAFE_CALL(nvrtcDestroyProgram(&prog)); // Destroy the program.
CUmodule module;
CUfunction function;
CUDA_SAFE_CALL(cuModuleLoadDataEx(&module, ptx, 0, 0, 0));
CUDA_SAFE_CALL(cuModuleGetFunction(&function, module, name.c_str()));
return std::make_shared<CUfunction>(function);
}
}
}
CUmodule module;
CUfunction function;
CUDA_SAFE_CALL(cuModuleLoadDataEx(&module, ptx, 0, 0, 0));
CUDA_SAFE_CALL(cuModuleGetFunction(&function, module, name.c_str()));
return std::make_shared<CUfunction>(function);
}
src/ngraph/runtime/gpu/gpu_cuda_function_pool.cpp
View file @ 3d53e58a
......@@ -26,40 +26,31 @@
static const std::string s_output_dir = "gpu_codegen";
namespace ngraph
using namespace ngraph;
runtime::gpu::CudaFunctionPool& runtime::gpu::CudaFunctionPool::instance()
{
namespace runtime
{
namespace gpu
{
CudaFunctionPool& CudaFunctionPool::instance()
{
static CudaFunctionPool pool;
return pool;
}
static CudaFunctionPool pool;
return pool;
}
void CudaFunctionPool::set(const std::string& name, const std::string& kernel)
{
const char* opts[] = {"--gpu-architecture=compute_35",
"--relocatable-device-code=true"};
std::string filename =
file_util::path_join(s_output_dir, "cuda_kernel_" + name + "_codegen.cu");
std::ofstream out(filename);
out << kernel;
out.close();
m_function_map.insert(
{name, CudaFunctionBuilder::get("cuda_" + name, kernel, 2, opts)});
}
void runtime::gpu::CudaFunctionPool::set(const std::string& name, const std::string& kernel)
{
const char* opts[] = {"--gpu-architecture=compute_35", "--relocatable-device-code=true"};
std::string filename =
file_util::path_join(s_output_dir, "cuda_kernel_" + name + "_codegen.cu");
std::ofstream out(filename);
out << kernel;
out.close();
m_function_map.insert({name, CudaFunctionBuilder::get("cuda_" + name, kernel, 2, opts)});
}
std::shared_ptr<CUfunction> CudaFunctionPool::get(const std::string& name)
{
auto it = m_function_map.find(name);
if (it != m_function_map.end())
{
return (*it).second;
}
return nullptr;
}
}
std::shared_ptr<CUfunction> runtime::gpu::CudaFunctionPool::get(const std::string& name)
{
auto it = m_function_map.find(name);
if (it != m_function_map.end())
{
return (*it).second;
}
return nullptr;
}
src/ngraph/runtime/gpu/gpu_cuda_kernel_builder.cpp
View file @ 3d53e58a
......@@ -16,74 +16,67 @@
#include "ngraph/runtime/gpu/gpu_cuda_kernel_builder.hpp"
#include "ngraph/codegen/code_writer.hpp"
namespace ngraph
using namespace ngraph;
void runtime::gpu::CudaKernelBuilder::get_elementwise_op(codegen::CodeWriter& writer,
const std::string& name,
const std::string& data_type,
const std::string& op,
const size_t& num_inputs)
{
namespace runtime
writer << "extern \"C\" __global__ void cuda_" << name << "(";
for (size_t i = 0; i < num_inputs; i++)
{
writer << data_type << "* in" << i << ", ";
}
writer << data_type << "* out,"
<< "size_t n)\n";
writer << "{\n";
writer.indent++;
{
namespace gpu
writer << "size_t tid = blockIdx.x * blockDim.x + threadIdx.x; \n";
writer << "if (tid < n)\n";
writer << "{\n";
writer.indent++;
{
void CudaKernelBuilder::get_elementwise_op(codegen::CodeWriter& writer,
const std::string& name,
const std::string& data_type,
const std::string& op,
const size_t& num_inputs)
writer << "out[tid] = " << op << "(";
for (size_t i = 0; i < num_inputs - 1; i++)
{
writer << "extern \"C\" __global__ void cuda_" << name << "(";
for (size_t i = 0; i < num_inputs; i++)
{
writer << data_type << "* in" << i << ", ";
}
writer << data_type << "* out,"
<< "size_t n)\n";
writer << "{\n";
writer.indent++;
{
writer << "size_t tid = blockIdx.x * blockDim.x + threadIdx.x; \n";
writer << "if (tid < n)\n";
writer << "{\n";
writer.indent++;
{
writer << "out[tid] = " << op << "(";
for (size_t i = 0; i < num_inputs - 1; i++)
{
writer << "in" << i << "[tid], ";
}
writer << "in" << num_inputs - 1 << "[tid]);\n";
}
writer.indent--;
writer << "}\n";
}
writer.indent--;
writer << "}\n";
return;
writer << "in" << i << "[tid], ";
}
writer << "in" << num_inputs - 1 << "[tid]);\n";
}
writer.indent--;
writer << "}\n";
}
writer.indent--;
writer << "}\n";
void CudaKernelBuilder::get_device_helper(codegen::CodeWriter& writer,
const std::string& name,
const std::string& data_type,
const std::string& math_kernel,
const size_t& num_inputs)
{
if (math_kernel.size())
{
writer << "__device__ " << data_type << " " << name << "(";
for (size_t i = 0; i < num_inputs - 1; i++)
{
writer << data_type << " x" << i << ", ";
}
writer << data_type << " x" << num_inputs - 1;
writer << ")\n";
writer << "{\n";
writer.indent++;
{
writer << "return " + math_kernel << ";\n";
}
writer.indent--;
writer << "}\n";
}
return;
}
return;
}
void runtime::gpu::CudaKernelBuilder::get_device_helper(codegen::CodeWriter& writer,
const std::string& name,
const std::string& data_type,
const std::string& math_kernel,
const size_t& num_inputs)
{
if (math_kernel.size())
{
writer << "__device__ " << data_type << " " << name << "(";
for (size_t i = 0; i < num_inputs - 1; i++)
{
writer << data_type << " x" << i << ", ";
}
writer << data_type << " x" << num_inputs - 1;
writer << ")\n";
writer << "{\n";
writer.indent++;
{
writer << "return " + math_kernel << ";\n";
}
writer.indent--;
writer << "}\n";
}
return;
}
src/ngraph/runtime/gpu/gpu_cuda_kernel_emitters.cpp
View file @ 3d53e58a
......@@ -20,26 +20,22 @@
#include "ngraph/runtime/gpu/gpu_cuda_kernel_emitters.hpp"
#include "ngraph/runtime/gpu/gpu_cuda_kernel_ops.hpp"
namespace ngraph
using namespace ngraph;
void runtime::gpu::emit_broadcast(
void* in, void* out, size_t repeat_size, size_t repeat_times, size_t count)
{
namespace runtime
std::string name = "broadcast";
// Create an instance of nvrtcProgram with the code string.
if (CudaFunctionPool::instance().get(name) == nullptr)
{
namespace gpu
{
void emit_broadcast(
void* in, void* out, size_t repeat_size, size_t repeat_times, size_t count)
{
std::string name = "broadcast";
// Create an instance of nvrtcProgram with the code string.
if (CudaFunctionPool::instance().get(name) == nullptr)
{
std::string kernel;
std::string data_type("float");
std::string kernel;
std::string data_type("float");
kernel = R"(
kernel = R"(
extern "C" __global__
void cuda_)" + name + "(" + data_type +
"* in, " + data_type + "* out, size_t m, size_t k, size_t n)\n" + R"(
void cuda_)" + name +
"(" + data_type + "* in, " + data_type + "* out, size_t m, size_t k, size_t n)\n" +
R"(
{
size_t tid = blockIdx.x * blockDim.x + threadIdx.x;
if(tid < n)
......@@ -48,28 +44,25 @@ void cuda_)" + name + "(" + data_type +
out[tid] = in[idx];
}
})";
CudaFunctionPool::instance().set(name, kernel);
}
CudaFunctionPool::instance().set(name, kernel);
}
//convert runtime ptr to driver api ptr
CUdeviceptr d_ptr_in, d_ptr_out;
d_ptr_in = (CUdeviceptr)in;
d_ptr_out = (CUdeviceptr)out;
//convert runtime ptr to driver api ptr
CUdeviceptr d_ptr_in, d_ptr_out;
d_ptr_in = CUdeviceptr(in);
d_ptr_out = CUdeviceptr(out);
void* args_list[] = {&d_ptr_in, &d_ptr_out, &repeat_size, &repeat_times, &count};
CUDA_SAFE_CALL(cuLaunchKernel(*CudaFunctionPool::instance().get(name).get(),
count,
1,
1, // grid dim
1,
1,
1, // block dim
0,
NULL, // shared mem and stream
args_list,
0)); // arguments
CUDA_SAFE_CALL(cuCtxSynchronize()); // Retrieve and print output.
}
}
}
void* args_list[] = {&d_ptr_in, &d_ptr_out, &repeat_size, &repeat_times, &count};
CUDA_SAFE_CALL(cuLaunchKernel(*CudaFunctionPool::instance().get(name).get(),
static_cast<unsigned int>(count),
1,
1, // grid dim
1,
1,
1, // block dim
0,
NULL, // shared mem and stream
args_list,
0)); // arguments
CUDA_SAFE_CALL(cuCtxSynchronize()); // Retrieve and print output.
}
src/ngraph/runtime/gpu/gpu_emitter.cpp
View file @ 3d53e58a
......@@ -518,15 +518,11 @@ cudnnSetOpTensorDescriptor(opTensorDesc,
writer.indent++;
auto arg_shape = args[0].get_shape();
auto arg_rank = arg_shape.size();
auto result_shape = out[0].get_shape();
auto& result_element_type = out[0].get_element_type();
auto input_order = reshape->get_input_order();
bool same_layout = is_sorted(input_order.begin(), input_order.end());
size_t result_shape_product = 1;
for (auto i : result_shape)
{
result_shape_product *= i;
......
src/ngraph/runtime/gpu/gpu_tensor_view.cpp
View file @ 3d53e58a
......@@ -41,7 +41,7 @@ runtime::gpu::GPU_TensorView::GPU_TensorView(const ngraph::element::Type& elemen
m_buffer_size = shape_size(shape) * element_type.size();
if (m_buffer_size > 0)
{
cudaMalloc((void**)&m_allocated_buffer_pool, m_buffer_size);
cudaMalloc(static_cast<void**>(&m_allocated_buffer_pool), m_buffer_size);
}
}
......
src/ngraph/runtime/gpu/gpu_util.cpp
View file @ 3d53e58a
......@@ -50,7 +50,7 @@ void runtime::gpu::check_cuda_errors(CUresult err)
void* runtime::gpu::create_gpu_buffer(size_t buffer_size)
{
void* allocated_buffer_pool;
cudaMalloc((void**)&allocated_buffer_pool, buffer_size);
cudaMalloc(static_cast<void**>(&allocated_buffer_pool), buffer_size);
return allocated_buffer_pool;
}
......
test/cpu_fusion.cpp
View file @ 3d53e58a
......@@ -48,6 +48,8 @@
#include "ngraph/util.hpp"
#include "nlohmann/json.hpp"
#include "util/all_close.hpp"
#include "util/autodiff/backprop_function.hpp"
#include "util/autodiff/numeric_compare.hpp"
#include "util/matcher.hpp"
#include "util/test_tools.hpp"
......@@ -914,3 +916,47 @@ TEST(cpu_fusion, sigmoid_n1c1h4)
vector<float> expected{0.73105858f, 0.98201379f, 0.73105858f, 0.98201379f};
ASSERT_TRUE(read_vector<float>(result) == expected);
}
TEST(cpu_fusion, sigmoid_bprop_fusion)
{
const string json_path = file_util::path_join(SERIALIZED_ZOO, "mxnet/Graph_fprop_sigmoid.json");
const string json_string = file_util::read_file_to_string(json_path);
stringstream ss(json_string);
shared_ptr<Function> func = ngraph::deserialize(ss);
auto df = autodiff::backprop_function(func);
auto manager = runtime::Manager::get("CPU");
auto external = manager->compile(df);
auto backend = manager->allocate_backend();
auto cf = backend->make_call_frame(external);
size_t ccg = count_ops_of_type<op::SigmoidBackprop>(df);
ASSERT_EQ(ccg, 1);
}
TEST(cpu_fusion, sigmoid_bprop_n1c1h4)
{
auto input = make_shared<op::Parameter>(element::f32, Shape{1, 1, 4});
auto delta = make_shared<op::Parameter>(element::f32, Shape{1, 1, 4});
auto sigmoid_node = make_shared<op::SigmoidBackprop>(input, delta);
auto func = make_shared<Function>(sigmoid_node, op::ParameterVector{input, delta});
auto manager = runtime::Manager::get("CPU");
auto external = manager->compile(func);
auto backend = manager->allocate_backend();
auto cf = backend->make_call_frame(external);
shared_ptr<runtime::TensorView> a =
backend->make_primary_tensor_view(element::f32, input->get_shape());
shared_ptr<runtime::TensorView> b =
backend->make_primary_tensor_view(element::f32, delta->get_shape());
shared_ptr<runtime::TensorView> result =
backend->make_primary_tensor_view(element::f32, input->get_shape());
vector<float> dataA{1.0f, 4.0f, 1.0f, 4.0f};
vector<float> dataB{1.0f, 1.0f, 1.0f, 1.0f};
copy_data(a, dataA);
copy_data(b, dataB);
cf->call({a, b}, {result});
vector<float> expected{0.196612f, 0.0176627f, 0.196612f, 0.0176627f};
EXPECT_TRUE(test::all_close(expected, read_vector<float>(result)));
}
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