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Allow empty shapes and do not validate them for inputs/outputs (#18442)

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### Description
Allow empty shapes and do not validate them for inputs/outputs at the
InferenceSession::ValidateInputsOutputs().

### Motivation and Context
https://github.com/microsoft/onnxruntime/pull/17301 disallowed empty
shapes.
However, many models depend on them as a way to pass shapes of different
ranks.
This commit is contained in:
Dmitri Smirnov 2023-11-16 13:15:48 -08:00 committed by GitHub
parent 3588fbac13
commit b6b9aff608
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1 changed files with 9 additions and 7 deletions
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16
onnxruntime/core/session/inference_session.cc
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@ -2025,9 +2025,10 @@ common::Status InferenceSession::ValidateInputsOutputs(gsl::span<const std::stri
expected_element_type, "tensor", input_output_moniker));
// check for shape
if (iter->second.tensor_shape.has_value()) {
const auto& opt_shape = iter->second.tensor_shape;
if (opt_shape.has_value() && !opt_shape->GetDims().empty()) {
ORT_RETURN_IF_ERROR_SESSIONID_(CheckShapes(name, input_output_tensor.Shape(),
*iter->second.tensor_shape, input_output_moniker));
*opt_shape, input_output_moniker));
}
} else if (input_output_ml_value.IsSparseTensor()) {
#if !defined(DISABLE_SPARSE_TENSORS)
@ -2038,9 +2039,10 @@ common::Status InferenceSession::ValidateInputsOutputs(gsl::span<const std::stri
ORT_RETURN_IF_ERROR_SESSIONID_(CheckTypes(sparse_tensor.DataType(), expected_element_type,
"sparse_tensor", input_output_moniker));
// Check shape
if (iter->second.tensor_shape.has_value()) {
const auto& opt_shape = iter->second.tensor_shape;
if (opt_shape.has_value() && !opt_shape->GetDims().empty()) {
ORT_RETURN_IF_ERROR_SESSIONID_(CheckShapes(name, sparse_tensor.DenseShape(),
*iter->second.tensor_shape, input_output_moniker));
*opt_shape, input_output_moniker));
}
} else if (is_sparse_initializer(name) &&
expected_type->IsTensorType()) {
@ -2049,9 +2051,10 @@ common::Status InferenceSession::ValidateInputsOutputs(gsl::span<const std::stri
ORT_RETURN_IF_ERROR_SESSIONID_(CheckTypes(sparse_tensor.DataType(), expected_element_type,
"sparse_tensor", input_output_moniker));
// Check shape
if (iter->second.tensor_shape.has_value()) {
const auto& opt_shape = iter->second.tensor_shape;
if (opt_shape.has_value() && !opt_shape->GetDims().empty()) {
ORT_RETURN_IF_ERROR_SESSIONID_(CheckShapes(name, sparse_tensor.DenseShape(),
*iter->second.tensor_shape, input_output_moniker));
*opt_shape, input_output_moniker));
}
} else {
return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, input_output_moniker, " with name: '", name,
@ -2061,7 +2064,6 @@ common::Status InferenceSession::ValidateInputsOutputs(gsl::span<const std::stri
return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, input_output_moniker, " with name ", name,
" is a sparse tensor, which is not supported in this build.");
#endif
} else if (input_output_ml_value.IsTensorSequence()) {
if (!expected_type->IsTensorSequenceType()
#if !defined(DISABLE_OPTIONAL_TYPE)