trevor-m commented on a change in pull request #8172:
URL: https://github.com/apache/tvm/pull/8172#discussion_r644228764
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File path: src/runtime/contrib/tensorrt/tensorrt_runtime.cc
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@@ -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:
I see. Having it configurable makes the most sense to me also. We can
have two modes, "best fit" which was the previous behavior, or "single engine"
which would be built for the highest batch size. I will update the PR when done.
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