NicolaLancellotti commented on a change in pull request #10060:
URL: https://github.com/apache/tvm/pull/10060#discussion_r799553892
##########
File path: src/relay/op/contrib/ethosu/common.cc
##########
@@ -75,6 +78,56 @@ Array<IndexExpr> EthosuInferKernelOutput(Array<IndexExpr>
ifm_shape, String ifm_
return output_shape;
}
+DataType DataTypeFromString(const String& dtype) {
+ DLDataType dl_dtype = tvm::runtime::String2DLDataType(dtype);
+ return DataType(dl_dtype);
+}
+
+void CheckDataType(const TypeReporter& reporter, const DataType& data_type,
+ const std::unordered_set<DataType>& allowed_data_types,
Review comment:
I would have used `std::initializer_list` instead of
`std::unordered_set`. It should be more efficient in this case,
it doesn't require allocation in the free store, and the number of elements
is small to benefit the fast retrieval of `std::unordered_set`.
##########
File path: src/relay/op/contrib/ethosu/common.cc
##########
@@ -75,6 +78,56 @@ Array<IndexExpr> EthosuInferKernelOutput(Array<IndexExpr>
ifm_shape, String ifm_
return output_shape;
}
+DataType DataTypeFromString(const String& dtype) {
+ DLDataType dl_dtype = tvm::runtime::String2DLDataType(dtype);
+ return DataType(dl_dtype);
+}
+
+void CheckDataType(const TypeReporter& reporter, const DataType& data_type,
+ const std::unordered_set<DataType>& allowed_data_types,
+ const String& operator_name, const String& tensor_name,
+ const String& operator_type) {
+ if (allowed_data_types.find(data_type) != allowed_data_types.end()) {
Review comment:
```suggestion
if (allowed_data_types.count(data_type)) {
```
If you use `std::unordered_set`.
##########
File path: src/relay/op/contrib/ethosu/common.cc
##########
@@ -75,6 +78,56 @@ Array<IndexExpr> EthosuInferKernelOutput(Array<IndexExpr>
ifm_shape, String ifm_
return output_shape;
}
+DataType DataTypeFromString(const String& dtype) {
+ DLDataType dl_dtype = tvm::runtime::String2DLDataType(dtype);
+ return DataType(dl_dtype);
+}
+
+void CheckDataType(const TypeReporter& reporter, const DataType& data_type,
+ const std::unordered_set<DataType>& allowed_data_types,
+ const String& operator_name, const String& tensor_name,
+ const String& operator_type) {
+ if (allowed_data_types.find(data_type) != allowed_data_types.end()) {
+ return;
+ }
+
+ std::ostringstream message;
+ message << "Invalid operator: expected " << operator_name << " ";
+ if (operator_type != "") {
+ message << operator_type << " ";
+ }
+ message << "to have type in {";
+ for (auto it = allowed_data_types.begin(); it != allowed_data_types.end();
++it) {
+ message << *it;
+ if (std::next(it) != allowed_data_types.end()) {
+ message << ", ";
+ }
+ }
+ message << "}";
+ message << " for " << tensor_name << " but was " << data_type << ".";
+
+ reporter->GetDiagCtx().EmitFatal(Diagnostic::Error(reporter->GetSpan()) <<
message.str());
+}
+
+void CheckDataTypeMatch(const TypeReporter& reporter, const DataType&
data_type,
+ const DataType& data_type2, const String&
operator_name,
+ const String& tensor_name, const String& tensor_name2,
+ const String& operator_type) {
+ if (data_type == data_type2) {
+ return;
+ }
+
+ std::ostringstream message;
+ message << "Invalid operator: expected " << operator_name << " ";
+ if (operator_type != " ") {
Review comment:
```suggestion
if (operator_type != "") {
```
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