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!2292 gpu fix all nop node graph execute 

Merge pull request !2292 from limingqi107/master
This commit is contained in:
mindspore-ci-bot 2020-06-18 17:17:06 +08:00 committed by Gitee
parent 9b90d89f6b 0f4397cece
commit 2e002ab64c
5 changed files with 126 additions and 22 deletions
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17
mindspore/ccsrc/device/gpu/gpu_kernel_runtime.cc
View File

@ -228,7 +228,7 @@ void GPUKernelRuntime::ClearKernelOutputAddress(const session::KernelGraph *grap
continue;
}
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i);
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i, false);
if (device_address->ptr_) {
mem_manager_->FreeMemFromMemPool(device_address);
}
@ -289,7 +289,7 @@ bool GPUKernelRuntime::AddMemSwapTask(const AnfNodePtr &kernel) {
for (auto &mem_swap_info : mem_swap_info_list) {
auto &kernel_exec_info = mem_swap_manager_->SearchKernelExecutionInfo(mem_swap_info.kernel_);
const HostAddress &host_address = kernel_exec_info.host_addrs_[mem_swap_info.output_idx_];
auto device_address = AnfAlgo::GetMutableOutputAddr(mem_swap_info.kernel_, mem_swap_info.output_idx_);
auto device_address = AnfAlgo::GetMutableOutputAddr(mem_swap_info.kernel_, mem_swap_info.output_idx_, false);
if (mem_swap_info.swap_kind_ == SwapKind::kDeviceToHost) {
mem_swap_manager_->AddMemSwapTask(SwapKind::kDeviceToHost, device_address, host_address);
@ -379,7 +379,8 @@ bool GPUKernelRuntime::AllocKernelInputDynamicRes(const mindspore::AnfNodePtr &k
MS_EXCEPTION_IF_NULL(kernel_inputs);
MS_EXCEPTION_IF_NULL(mem_swap_manager_);
for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(kernel); ++i) {
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i);
// Graph may be all nop nodes and not remove nop node, so this can not skip nop node.
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i, false);
MS_EXCEPTION_IF_NULL(device_address);
if (mem_swap_manager_->trigger_swap()) {
while (auto device_address_swap_in = mem_swap_manager_->UpdateSwapQueue(SwapKind::kHostToDevice)) {
@ -437,7 +438,7 @@ bool GPUKernelRuntime::AllocKernelOutputDynamicRes(const mindspore::kernel::Kern
}
auto output_sizes = kernel_mod.GetOutputSizeList();
for (size_t i = 0; i < output_sizes.size(); ++i) {
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i);
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i, false);
MS_EXCEPTION_IF_NULL(device_address);
if (device_address->ptr_ == nullptr && !AttemptMallocMem(device_address, output_sizes[i])) {
return false;
@ -495,7 +496,7 @@ void GPUKernelRuntime::AllocCommunicationOpInputDynamicRes(const mindspore::AnfN
std::vector<size_t> size_list;
DeviceAddressPtrList addr_list;
for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(kernel); ++i) {
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i);
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i, false);
MS_EXCEPTION_IF_NULL(device_address);
if (device_address->ptr_ == nullptr) {
is_need_alloc_memory = true;
@ -520,7 +521,7 @@ void GPUKernelRuntime::AllocCommunicationOpOutputDynamicRes(const mindspore::Anf
MS_EXCEPTION_IF_NULL(kernel_mod);
auto output_sizes = kernel_mod->GetOutputSizeList();
for (size_t i = 0; i < output_sizes.size(); ++i) {
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i);
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i, false);
MS_EXCEPTION_IF_NULL(device_address);
if (device_address->ptr_ == nullptr) {
is_need_alloc_memory = true;
@ -578,7 +579,7 @@ void GPUKernelRuntime::FreeKernelDynamicRes(const mindspore::AnfNodePtr &kernel,
MS_LOG(EXCEPTION) << "Check dynamic reference count failed.";
}
if (kernel_ref_count_ptr->ref_count_dynamic_use_ == 0) {
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i);
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i, false);
mem_manager_->FreeMemFromMemPool(device_address);
device_address->set_status(DeviceAddressStatus::kInDevice);
}
@ -590,7 +591,7 @@ void GPUKernelRuntime::FreeKernelDynamicRes(const mindspore::AnfNodePtr &kernel,
continue;
}
if (kernel_ref_count_ptr->ref_count_dynamic_use_ == 0) {
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i);
auto device_address = AnfAlgo::GetMutableOutputAddr(kernel, i, false);
mem_manager_->FreeMemFromMemPool(device_address);
device_address->set_status(DeviceAddressStatus::kInDevice);
}

6
mindspore/ccsrc/pre_activate/mem_reuse/mem_reuse.cc
View File

@ -228,7 +228,8 @@ KernelRefCountPtr MemReuseUtil::GetKernelInputRef(const CNodePtr &kernel, size_t
<< AnfAlgo::GetInputTensorNum(kernel);
}
auto input_node = kernel->input(input_idx + 1);
auto kernel_input = AnfAlgo::VisitKernelWithReturnType(input_node, 0, true);
// Graph may be all nop nodes and not remove nop node, so this can not skip nop node.
auto kernel_input = AnfAlgo::VisitKernelWithReturnType(input_node, 0, false);
if (IsPrimitive(kernel_input.first, prim::kPrimMakeTuple)) {
MS_LOG(EXCEPTION) << "Input node [" << input_node->DebugString() << "]'s input " << input_idx << " is MakeTuple";
}
@ -269,7 +270,8 @@ void MemReuseUtil::SetKernelDefInputs() {
if (ref_ptr != nullptr) {
// set the inputs of this kernel_def
auto input_node = AnfAlgo::GetInputNode(kernel, i);
auto input = AnfAlgo::VisitKernelWithReturnType(input_node, 0, true);
// Graph may be all nop nodes and not remove nop node, so this can not skip nop node.
auto input = AnfAlgo::VisitKernelWithReturnType(input_node, 0, false);
if (IsPrimitive(input.first, prim::kPrimMakeTuple)) {
MS_LOG(EXCEPTION) << "Input node [" << input_node->DebugString() << "]'s input " << i << " is MakeTuple";
}

20
mindspore/ccsrc/session/anf_runtime_algorithm.cc
View File

@ -544,9 +544,10 @@ TypeId AnfRuntimeAlgorithm::GetPrevNodeOutputDeviceDataType(const AnfNodePtr &an
}
// get output device addr of anf_node
const DeviceAddress *AnfRuntimeAlgorithm::GetOutputAddr(const AnfNodePtr &node, size_t output_idx) {
const DeviceAddress *AnfRuntimeAlgorithm::GetOutputAddr(const AnfNodePtr &node, size_t output_idx,
bool visit_nop_node) {
MS_EXCEPTION_IF_NULL(node);
if (opt::IsNopNode(node)) {
if (opt::IsNopNode(node) && visit_nop_node) {
auto cnode = node->cast<CNodePtr>();
MS_EXCEPTION_IF_NULL(cnode);
if (cnode->inputs().size() == 2) {
@ -565,9 +566,10 @@ const DeviceAddress *AnfRuntimeAlgorithm::GetOutputAddr(const AnfNodePtr &node,
return addr;
}
DeviceAddressPtr AnfRuntimeAlgorithm::GetMutableOutputAddr(const AnfNodePtr &node, size_t output_idx) {
DeviceAddressPtr AnfRuntimeAlgorithm::GetMutableOutputAddr(const AnfNodePtr &node, size_t output_idx,
bool visit_nop_node) {
MS_EXCEPTION_IF_NULL(node);
if (opt::IsNopNode(node)) {
if (opt::IsNopNode(node) && visit_nop_node) {
auto cnode = node->cast<CNodePtr>();
MS_EXCEPTION_IF_NULL(cnode);
if (cnode->inputs().size() == 2) {
@ -598,14 +600,16 @@ bool AnfRuntimeAlgorithm::OutputAddrExist(const AnfNodePtr &node, size_t output_
return kernel_info->OutputAddrExist(output_idx);
}
const DeviceAddress *AnfRuntimeAlgorithm::GetPrevNodeOutputAddr(const AnfNodePtr &anf_node, size_t input_idx) {
const DeviceAddress *AnfRuntimeAlgorithm::GetPrevNodeOutputAddr(const AnfNodePtr &anf_node, size_t input_idx,
bool visit_nop_node) {
KernelWithIndex kernel_with_index = AnfAlgo::GetPrevNodeOutput(anf_node, input_idx);
return AnfRuntimeAlgorithm::GetOutputAddr(kernel_with_index.first, kernel_with_index.second);
return AnfRuntimeAlgorithm::GetOutputAddr(kernel_with_index.first, kernel_with_index.second, visit_nop_node);
}
DeviceAddressPtr AnfRuntimeAlgorithm::GetPrevNodeMutableOutputAddr(const AnfNodePtr &anf_node, size_t input_idx) {
DeviceAddressPtr AnfRuntimeAlgorithm::GetPrevNodeMutableOutputAddr(const AnfNodePtr &anf_node, size_t input_idx,
bool visit_nop_node) {
KernelWithIndex kernel_with_index = AnfAlgo::GetPrevNodeOutput(anf_node, input_idx);
return AnfRuntimeAlgorithm::GetMutableOutputAddr(kernel_with_index.first, kernel_with_index.second);
return AnfRuntimeAlgorithm::GetMutableOutputAddr(kernel_with_index.first, kernel_with_index.second, visit_nop_node);
}
// set output device addr of anf_node

10
mindspore/ccsrc/session/anf_runtime_algorithm.h
View File

@ -121,14 +121,16 @@ class AnfRuntimeAlgorithm {
// get output select data type from prev node,input_index is the input index of current node related to prev node
static TypeId GetPrevNodeOutputDeviceDataType(const AnfNodePtr &node, size_t input_idx);
// get output device addr of anf_node
static const DeviceAddress *GetOutputAddr(const AnfNodePtr &node, size_t output_idx);
static const DeviceAddress *GetOutputAddr(const AnfNodePtr &node, size_t output_idx, bool visit_nop_node = true);
// get mutable output device addr of anf_node
static DeviceAddressPtr GetMutableOutputAddr(const AnfNodePtr &node, size_t output_idx);
static DeviceAddressPtr GetMutableOutputAddr(const AnfNodePtr &node, size_t output_idx, bool visit_nop_node = true);
// check whether output addr is exist or not
static bool OutputAddrExist(const AnfNodePtr &node, size_t output_idx);
// get address from prev node,input_index is the input index of current node related to prev node
static const DeviceAddress *GetPrevNodeOutputAddr(const AnfNodePtr &node, size_t input_idx);
static DeviceAddressPtr GetPrevNodeMutableOutputAddr(const AnfNodePtr &anf_node, size_t input_idx);
static const DeviceAddress *GetPrevNodeOutputAddr(const AnfNodePtr &node, size_t input_idx,
bool visit_nop_node = true);
static DeviceAddressPtr GetPrevNodeMutableOutputAddr(const AnfNodePtr &anf_node, size_t input_idx,
bool visit_nop_node = true);
// set output device addr of anf_node
static void SetOutputAddr(const DeviceAddressPtr &addr, size_t output_idx, AnfNode *node);
// set workspace device addr of anf_node

95
tests/st/ops/gpu/test_flatten_op.py
View File

@ -31,6 +31,49 @@ class NetFlatten(nn.Cell):
return self.flatten(x)
class NetAllFlatten(nn.Cell):
def __init__(self):
super(NetAllFlatten, self).__init__()
self.flatten = P.Flatten()
def construct(self, x):
loop_count = 4
while loop_count > 0:
x = self.flatten(x)
loop_count = loop_count - 1
return x
class NetFirstFlatten(nn.Cell):
def __init__(self):
super(NetFirstFlatten, self).__init__()
self.flatten = P.Flatten()
self.relu = P.ReLU()
def construct(self, x):
loop_count = 4
while loop_count > 0:
x = self.flatten(x)
loop_count = loop_count - 1
x = self.relu(x)
return x
class NetLastFlatten(nn.Cell):
def __init__(self):
super(NetLastFlatten, self).__init__()
self.flatten = P.Flatten()
self.relu = P.ReLU()
def construct(self, x):
loop_count = 4
x = self.relu(x)
while loop_count > 0:
x = self.flatten(x)
loop_count = loop_count - 1
return x
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
@ -46,3 +89,55 @@ def test_flatten():
flatten = NetFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_all_flatten():
x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype(np.float32))
expect = np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype(np.float32)
context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
flatten = NetAllFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()
context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
flatten = NetAllFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_first_flatten():
x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype(np.float32))
expect = np.array([[0, 0.3, 3.6], [0.4, 0.5, 0]]).astype(np.float32)
context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
flatten = NetFirstFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()
context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
flatten = NetFirstFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_last_flatten():
x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype(np.float32))
expect = np.array([[0, 0.3, 3.6], [0.4, 0.5, 0]]).astype(np.float32)
context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
flatten = NetLastFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()
context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
flatten = NetLastFlatten()
output = flatten(x)
assert (output.asnumpy() == expect).all()