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Fix clamp operation in PyTorch frontend to use Clamp op for constants #33041

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Fix clamp operation in PyTorch frontend to use Clamp op for constants #33041

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3488d26
Fix clamp operation in PyTorch frontend to use Clamp op for constants
vishalharkal15 Nov 26, 2025
afb33fa
Merge branch 'master' into fix-clamp-cpp-inference
vishalharkal15 Nov 26, 2025
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39 changes: 29 additions & 10 deletions src/frontends/pytorch/src/op/clamp.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -3,11 +3,15 @@
//

#include "openvino/frontend/pytorch/node_context.hpp"
#include "openvino/op/clamp.hpp"
#include "openvino/op/constant.hpp"
#include "openvino/op/convert_like.hpp"
#include "openvino/op/maximum.hpp"
#include "openvino/op/minimum.hpp"
#include "utils.hpp"

#include <limits>

namespace ov {
namespace frontend {
namespace pytorch {
Expand All @@ -18,17 +22,32 @@ using namespace ov::op;
OutputVector translate_clamp(const NodeContext& context) {
num_inputs_check(context, 1, 3);
auto x = context.get_input(0);
if (!context.input_is_none(1)) {
auto min_clip = context.get_input(1);
min_clip = context.mark_node(std::make_shared<v1::ConvertLike>(min_clip, x));
x = context.mark_node(std::make_shared<v1::Maximum>(x, min_clip));
}
if (!context.input_is_none(2)) {
auto max_clip = context.get_input(2);
max_clip = context.mark_node(std::make_shared<v1::ConvertLike>(max_clip, x));
x = context.mark_node(std::make_shared<v1::Minimum>(x, max_clip));

// Check if min and max are constants
bool min_is_const = !context.input_is_none(1) && ov::as_type_ptr<ov::op::v0::Constant>(context.get_input(1).get_node_shared_ptr());
bool max_is_const = !context.input_is_none(2) && ov::as_type_ptr<ov::op::v0::Constant>(context.get_input(2).get_node_shared_ptr());

if (min_is_const && max_is_const) {
// Both min and max are constants, use Clamp op
auto min_const = ov::as_type_ptr<ov::op::v0::Constant>(context.get_input(1).get_node_shared_ptr());
double min_val = min_const->cast_vector<double>()[0];
auto max_const = ov::as_type_ptr<ov::op::v0::Constant>(context.get_input(2).get_node_shared_ptr());
double max_val = max_const->cast_vector<double>()[0];
return {context.mark_node(std::make_shared<v0::Clamp>(x, min_val, max_val))};
} else {
// Fallback to Maximum/Minimum for tensor min/max or missing min/max
if (!context.input_is_none(1)) {
auto min_clip = context.get_input(1);
min_clip = context.mark_node(std::make_shared<v1::ConvertLike>(min_clip, x));
x = context.mark_node(std::make_shared<v1::Maximum>(x, min_clip));
}
if (!context.input_is_none(2)) {
auto max_clip = context.get_input(2);
max_clip = context.mark_node(std::make_shared<v1::ConvertLike>(max_clip, x));
x = context.mark_node(std::make_shared<v1::Minimum>(x, max_clip));
}
return {std::move(x)};
}
return {std::move(x)};
};

} // namespace op
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