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fix: Automatically send truncated long ints to cuda at shape analysis time #1541

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Merged
merged 1 commit into from
Dec 12, 2022
Merged

fix: Automatically send truncated long ints to cuda at shape analysis time #1541

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2 changes: 1 addition & 1 deletion core/lowering/lowering.h
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ struct LowerInfo {
std::vector<std::string> forced_fallback_modules;
friend std::ostream& operator<<(std::ostream& os, const LowerInfo& l);

std::string getGPUDeviceString() {
std::string getGPUDeviceString() const {
return "cuda:" + std::to_string(target_device.gpu_id);
};
};
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5 changes: 5 additions & 0 deletions core/partitioning/partitioninginfo/PartitioningInfo.h
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Expand Up @@ -16,6 +16,11 @@ struct PartitioningInfo {
uint64_t min_block_size = 1;
std::vector<std::string> forced_fallback_operators;
bool truncate_long_and_double;
ir::Device target_device;

std::string getGPUDeviceString() const {
return "cuda:" + std::to_string(target_device.gpu_id);
};
};

std::ostream& operator<<(std::ostream& os, const PartitioningInfo& s);
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13 changes: 9 additions & 4 deletions core/partitioning/shape_analysis.cpp
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Expand Up @@ -99,7 +99,7 @@ torch::jit::Node* getUpstreamCastNode(torch::jit::Value* val) {
return nullptr;
}

torch::jit::Node* createCastNode(SegmentedBlock& seg_block, size_t index, bool is_input) {
torch::jit::Node* createCastNode(SegmentedBlock& seg_block, size_t index, bool is_input, std::string device) {
auto cast_raw_value = is_input ? seg_block.raw_inputs()[index] : seg_block.raw_outputs()[index];
auto cast_subgraph_value = is_input ? seg_block.inputs()[index] : seg_block.outputs()[index];
torch::jit::Node* cast_node = getUpstreamCastNode(cast_raw_value);
Expand All @@ -125,8 +125,11 @@ torch::jit::Node* createCastNode(SegmentedBlock& seg_block, size_t index, bool i
auto const_type = is_input ? g->insertConstant(4) : g->insertConstant(3);
auto const_zero = g->insertConstant(0);
const_zero->setType(torch::jit::BoolType::get());
auto cuda = g->insertConstant(device);
cuda->setType(torch::jit::DeviceObjType::get());
auto none_val = g->insertNode(g->createNone())->output();
cast_node = g->create(torch::jit::aten::to, {cast_subgraph_value, const_type, const_zero, const_zero, none_val});
cast_node =
g->create(torch::jit::aten::to, {cast_subgraph_value, cuda, const_type, const_zero, const_zero, none_val});
}
return cast_node;
}
Expand Down Expand Up @@ -217,6 +220,8 @@ void getSegmentsOutputByRunning(
ivalues_maps[output] = jit_results[idx++];
}

auto target_device = partitioning_info.getGPUDeviceString();

// auto int64 <=> int32 conversion
if (seg_block.target() == SegmentedBlock::kTorch && partitioning_info.truncate_long_and_double) {
// First, check if there is Int64 input
Expand All @@ -226,7 +231,7 @@ void getSegmentsOutputByRunning(
at::ScalarType t = cur_ivalue.toTensor().scalar_type();
if (t == at::kLong) {
// we add a cast operation to cast the type to Int64
auto cast_node = createCastNode(seg_block, i, true);
auto cast_node = createCastNode(seg_block, i, true, target_device);
seg_block.g()->prependNode(cast_node);
seg_block.inputs()[i]->replaceAllUsesAfterNodeWith(cast_node, cast_node->outputs()[0]);
}
Expand All @@ -237,7 +242,7 @@ void getSegmentsOutputByRunning(
auto cur_ivalue = ivalues_maps[seg_block.raw_outputs()[i]];
at::ScalarType t = cur_ivalue.toTensor().scalar_type();
if (t == at::kLong) {
auto cast_node = createCastNode(seg_block, i, false);
auto cast_node = createCastNode(seg_block, i, false, target_device);
seg_block.g()->appendNode(cast_node);
seg_block.g()->block()->replaceOutput(i, cast_node->outputs()[0]);
}
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6 changes: 6 additions & 0 deletions cpp/src/compile_spec.cpp
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Expand Up @@ -111,6 +111,7 @@ torchtrt::core::CompileSpec to_internal_compile_spec(CompileSpec external) {
internal.convert_info.engine_settings.truncate_long_and_double = external.truncate_long_and_double;
internal.convert_info.engine_settings.device.allow_gpu_fallback = external.device.allow_gpu_fallback;
internal.lower_info.target_device.allow_gpu_fallback = external.device.allow_gpu_fallback;
internal.partitioning_info.target_device.allow_gpu_fallback = external.device.allow_gpu_fallback;

TORCHTRT_CHECK(
!(external.require_full_compilation && (external.torch_executed_ops.size() > 0)),
Expand All @@ -132,11 +133,13 @@ torchtrt::core::CompileSpec to_internal_compile_spec(CompileSpec external) {
case Device::DeviceType::kDLA:
internal.convert_info.engine_settings.device.device_type = nvinfer1::DeviceType::kDLA;
internal.lower_info.target_device.device_type = nvinfer1::DeviceType::kDLA;
internal.partitioning_info.target_device.device_type = nvinfer1::DeviceType::kDLA;
break;
case Device::DeviceType::kGPU:
default:
internal.convert_info.engine_settings.device.device_type = nvinfer1::DeviceType::kGPU;
internal.lower_info.target_device.device_type = nvinfer1::DeviceType::kGPU;
internal.partitioning_info.target_device.device_type = nvinfer1::DeviceType::kGPU;
}

switch (external.capability) {
Expand All @@ -155,6 +158,9 @@ torchtrt::core::CompileSpec to_internal_compile_spec(CompileSpec external) {
internal.convert_info.engine_settings.device.dla_core = external.device.dla_core;
internal.lower_info.target_device.gpu_id = external.device.gpu_id;
internal.lower_info.target_device.dla_core = external.device.dla_core;
internal.partitioning_info.target_device.gpu_id = external.device.gpu_id;
internal.partitioning_info.target_device.dla_core = external.device.dla_core;

internal.convert_info.engine_settings.num_avg_timing_iters = external.num_avg_timing_iters;
internal.convert_info.engine_settings.workspace_size = external.workspace_size;
internal.convert_info.engine_settings.dla_sram_size = external.dla_sram_size;
Expand Down