trevor-m commented on a change in pull request #8172:
URL: https://github.com/apache/tvm/pull/8172#discussion_r643553887
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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:
Thanks for the review! Yes, I suppose we could do that instead.
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