comaniac commented on a change in pull request #8172:
URL: https://github.com/apache/tvm/pull/8172#discussion_r643480880
##########
File path: src/runtime/contrib/tensorrt/tensorrt_runtime.cc
##########
@@ -64,7 +64,8 @@ class TensorRTRuntime : public JSONRuntimeBase {
const Array<String>& const_names)
: JSONRuntimeBase(symbol_name, graph_json, const_names),
use_implicit_batch_(true),
- max_workspace_size_(size_t(1) << 30) {}
+ max_workspace_size_(size_t(1) << 30),
+ highest_batch_size_(-1) {}
Review comment:
Better to make it consistent.
```suggestion
max_batch_size_(-1) {}
```
##########
File path: src/runtime/contrib/tensorrt/tensorrt_runtime.cc
##########
@@ -221,10 +248,15 @@ class TensorRTRuntime : public JSONRuntimeBase {
}
// Build engine.
- trt_engine_cache_[std::make_pair(symbol_name_, batch_size_)] =
builder.BuildEngine();
+ trt_engine_cache_[std::make_pair(symbol_name_, batch_size)] =
builder.BuildEngine();
DLOG(INFO) << "Finished building TensorRT engine for subgraph " <<
symbol_name_
- << " with batch size " << batch_size_;
+ << " with batch size " << batch_size;
+ // Update highest batch size.
+ if (batch_size > highest_batch_size_) {
+ highest_batch_size_ = batch_size;
+ }
Review comment:
nit
```suggestion
highest_batch_size_ = (batch_size > highest_batch_size_) ? batch_size :
highest_batch_size_;
```
##########
File path: src/runtime/contrib/tensorrt/tensorrt_runtime.cc
##########
@@ -174,25 +176,50 @@ class TensorRTRuntime : public JSONRuntimeBase {
int binding_index = engine->getBindingIndex(name.c_str());
ICHECK_NE(binding_index, -1);
if (data_entry_[eid]->device.device_type != kDLCUDA) {
-
device_buffers[binding_index].CopyTo(const_cast<DLTensor*>(data_entry_[eid]));
+ auto device_buffer = GetOrAllocateDeviceBuffer(eid, binding_index);
+ device_buffer.CopyTo(const_cast<DLTensor*>(data_entry_[eid]));
}
}
}
private:
+ /*! \brief Get batch size for engine from the runtime input shapes. */
+ int GetBatchSize() {
+ return data_entry_[input_var_eid_[0]]->ndim == 0 ? 1 :
data_entry_[input_var_eid_[0]]->shape[0];
+ }
+
+ /*! \brief TensorRT engines are built for a maximum batch size. If an engine
doesn't exist for a
+ * certain batch size already, see if we can reuse an engine built for a
higher batch size. */
+ bool FindCompatibleEngine(int batch_size, int* compatible_engine_batch_size)
{
+ // Check for exact match
+ if (trt_engine_cache_.count(std::make_pair(symbol_name_, batch_size))) {
+ *compatible_engine_batch_size = batch_size;
+ return true;
+ }
Review comment:
1. IIUC, seems like you don't need the exact match, so we can rely on
the following logic and remove this one. This can also reduce the number of
cached engines.
2. Accordingly, can we only keep one engine with the so far largest batch
size? i.e., after we build a new engine with larger batch size, can we throw
away the old one?
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