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[WebNN EP] Make some types clearer (#16705)

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It's a follow-up to address comments in
https://github.com/microsoft/onnxruntime/pull/16671#discussion_r1261761828
and
https://github.com/microsoft/onnxruntime/pull/16671#discussion_r1261763873
This commit is contained in:
Wanming Lin 2023-07-15 08:39:36 +08:00 committed by GitHub
parent 2ae041f390
commit 2b7a94e65b
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1 changed files with 10 additions and 10 deletions
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20
onnxruntime/core/providers/webnn/builders/impl/split_op_builder.cc
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@ -37,11 +37,11 @@ Status SplitOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
emscripten::val output_array;
std::vector<int64_t> input_shape;
ORT_RETURN_IF_NOT(GetShape(*input_defs[0], input_shape, logger), "Cannot get shape");
const auto rank = input_shape.size();
const size_t rank = input_shape.size();
emscripten::val options = emscripten::val::object();
NodeAttrHelper helper(node);
auto axis = helper.Get("axis", 0);
int32_t axis = helper.Get("axis", 0);
axis = SafeInt<int32_t>(HandleNegativeAxis(axis, rank));
options.set("axis", axis);
@ -59,13 +59,13 @@ Status SplitOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
"The size of outputs must be equal to the size of 'split' input.");
} else {
if (helper.HasAttr("num_outputs")) {
const auto num_outputs = helper.Get("num_outputs", 1);
const int32_t num_outputs = helper.Get("num_outputs", 1);
ORT_RETURN_IF_NOT(num_outputs > 0, "The 'num_outputs' must be a positive integer.");
if (input_shape[axis] % num_outputs == 0) {
// The 'num_outputs' evenly divide the dim value at 'axis' specified.
output_array = model_builder.GetBuilder().call<emscripten::val>("split",
input,
static_cast<int32_t>(num_outputs),
num_outputs,
options);
} else {
std::vector<int64_t> mapping_split;
@ -80,22 +80,22 @@ Status SplitOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
emscripten::val::array(converted_splits),
options);
}
ORT_RETURN_IF_NOT(output_array["length"].as<int32_t>() == static_cast<int32_t>(num_outputs),
ORT_RETURN_IF_NOT(output_array["length"].as<int32_t>() == num_outputs,
"The size of outputs must be equal to 'num_outputs'.");
} else {
// w/o 'split' input for opset 13
// Refer to https://github.com/microsoft/onnxruntime/blob/a7ad859e3ab60bddfcf2fefa96bfcb550f0fc04c/onnxruntime/core/providers/dml/OperatorAuthorHelper/OperatorHelper.cpp#L984-L989
// split input stream equally across output streams.
const auto& output_defs = node.OutputDefs();
auto output_count = output_defs.size();
const size_t output_count = output_defs.size();
output_array = model_builder.GetBuilder().call<emscripten::val>("split",
input, static_cast<int32_t>(output_count),
options);
ORT_RETURN_IF_NOT(output_array["length"].as<int32_t>() == static_cast<int32_t>(output_count),
ORT_RETURN_IF_NOT(output_array["length"].as<size_t>() == output_count,
"The size of outputs must be equal to the count of output nodes.");
}
}
for (size_t i = 0, count = output_array["length"].as<int32_t>(); i < count; i++) {
for (size_t i = 0, count = output_array["length"].as<size_t>(); i < count; i++) {
model_builder.AddOperand(node.OutputDefs()[i]->Name(), std::move(output_array[i]));
}
return Status::OK();
@ -118,10 +118,10 @@ bool SplitOpBuilder::IsOpSupportedImpl(const InitializedTensorSet& initializers,
LOGS(logger, VERBOSE) << "Cannot get input's shape.";
return false;
}
const auto rank = input_shape.size();
const size_t rank = input_shape.size();
NodeAttrHelper helper(node);
auto axis = helper.Get("axis", 0);
int32_t axis = helper.Get("axis", 0);
axis = SafeInt<int32_t>(HandleNegativeAxis(axis, rank));
if (input_defs.size() == 2) {