Skip to content

[ET] enabling half dtype input for quantization #11479

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 9 commits into from
Jun 14, 2025
4 changes: 2 additions & 2 deletions kernels/quantized/cpu/op_quantize.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -150,7 +150,7 @@ Tensor& quantize_per_tensor_out(
break;

switch (input.scalar_type()) {
ET_FORALL_FLOAT_TYPES(CALCULATE_FLOAT_TYPE);
ET_FORALL_FLOATH_TYPES(CALCULATE_FLOAT_TYPE);
default:
ET_CHECK_MSG(
false,
Expand Down Expand Up @@ -346,7 +346,7 @@ Tensor& quantize_per_channel_out(
break;

switch (input.scalar_type()) {
ET_FORALL_FLOAT_TYPES(CALCULATE_FLOAT_TYPE);
ET_FORALL_FLOATH_TYPES(CALCULATE_FLOAT_TYPE);
default:
ET_CHECK_MSG(
false,
Expand Down
65 changes: 65 additions & 0 deletions kernels/quantized/test/op_quantize_test.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -49,6 +49,32 @@ void test_dtype() {
EXPECT_TENSOR_EQ(out, expected);
}

template <ScalarType INPUT_DTYPE>
void test_input_dtype() {
TensorFactory<INPUT_DTYPE> tf_input;

Tensor input = tf_input.full({3, 5}, 4);
double scale = 0.5;
int64_t zero_point = 108;
int64_t quant_min = 0;
int64_t quant_max = 127;

TensorFactory<ScalarType::Char> tfo;
Tensor out = tfo.zeros({3, 5});
// 4 / 0.5 + 108 = 116
Tensor expected = tfo.full({3, 5}, 116);
quantize_per_tensor_out(
input, scale, zero_point, quant_min, quant_max, ScalarType::Char, out);

EXPECT_TENSOR_EQ(out, expected);
}

TEST(OpQuantizeOutTest, AllInputDtypesSupported) {
test_input_dtype<ScalarType::Float>();
test_input_dtype<ScalarType::Half>();
test_input_dtype<ScalarType::Double>();
}

TEST(OpQuantizeOutTest, AllDtypesSupported) {
test_dtype<ScalarType::Byte>();
test_dtype<ScalarType::Char>();
Expand All @@ -58,6 +84,45 @@ TEST(OpQuantizeOutTest, AllDtypesSupported) {
test_dtype<ScalarType::Int>();
}

TEST(OpQuantizeOutTest, DoubleInputTest) {
TensorFactory<ScalarType::Double> tf_double;

// Test with a more complex value that might have precision differences
Tensor input = tf_double.full({2, 3}, 3.14159265359);
double scale = 0.01;
int64_t zero_point = -100;
int64_t quant_min = 0;
int64_t quant_max = 255;

TensorFactory<ScalarType::Byte> tfo;
Tensor out = tfo.zeros({2, 3});
// 3.14159265359 / 0.01 - 100 = 214.159265359
Tensor expected = tfo.full({2, 3}, 214);
quantize_per_tensor_out(
input, scale, zero_point, quant_min, quant_max, ScalarType::Byte, out);

EXPECT_TENSOR_EQ(out, expected);
}

TEST(OpQuantizeOutTest, HalfInputTest) {
TensorFactory<ScalarType::Half> tf_half;

Tensor input = tf_half.full({2, 3}, 2.5);
double scale = 0.5;
int64_t zero_point = 10;
int64_t quant_min = -128;
int64_t quant_max = 127;

TensorFactory<ScalarType::Char> tfo;
Tensor out = tfo.zeros({2, 3});
// 2.5 / 0.5 + 10 = 15
Tensor expected = tfo.full({2, 3}, 15);
quantize_per_tensor_out(
input, scale, zero_point, quant_min, quant_max, ScalarType::Char, out);

EXPECT_TENSOR_EQ(out, expected);
}

TEST(OpQuantizeOutTest, TensorArgOverload) {
TensorFactory<ScalarType::Float> tf_float;
TensorFactory<ScalarType::Double> tf_double;
Expand Down
Loading