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Using generic implemntation for 16-bit activations and 8 bit weights for Conv2D in Backends #16007

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Using generic implementation for 16-bit activations and 8 bit weights…
RahulC7 Nov 28, 2025
a8e37d4
Using generic implemntation for 16-bit activations and 8 bit weights …
RahulC7 Nov 28, 2025
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14 changes: 14 additions & 0 deletions backends/cadence/aot/quantizer/quantizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -372,3 +372,17 @@ def __init__(self, quantizers: Optional[list[Quantizer]] = None) -> None:
# Add 16-bit quantizers for LinearPattern
quantizers.append(CadenceAtenQuantizer(LinearPattern(), qconfig_A16))
super().__init__(quantizers)


class CadenceWith16BitConvActivationsQuantizer(CadenceQuantizer):
"""
Quantizer including A16 conv
"""

def __init__(self, quantizers: Optional[list[Quantizer]] = None) -> None:
if quantizers is None:
quantizers = []
# Add 16-bit quantizers for Conv patterns
quantizers.append(CadenceAtenQuantizer(Conv1dPattern(), qconfig_A16))
quantizers.append(CadenceAtenQuantizer(Conv2dPattern(), qconfig_A16))
super().__init__(quantizers)
49 changes: 49 additions & 0 deletions backends/cadence/hifi/operators/op_quantized_conv2d_nchw_out.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
#include <executorch/backends/cadence/hifi/kernels/kernels.h>
#include <executorch/backends/cadence/hifi/operators/operators.h>
#include <executorch/runtime/kernel/kernel_includes.h>
#include <on_device_ai/Assistant/Jarvis/min_runtime/operators/generic/op_quantized_conv2d.h>

#define ALIGN_PTR(x, bytes) ((((unsigned)(x)) + (bytes - 1)) & (~(bytes - 1)))

Expand Down Expand Up @@ -532,6 +533,30 @@ void quantized_conv2d_nchw_out(
__ET_UNUSED const Tensor& out_multiplier,
__ET_UNUSED const Tensor& out_shift,
Tensor& out) {
// Handle W8A16 heterogeneous type (int16_t activations, int8_t weights)
if (out.scalar_type() == ::executorch::aten::ScalarType::Short &&
input.scalar_type() == ::executorch::aten::ScalarType::Short &&
weight.scalar_type() == ::executorch::aten::ScalarType::Char) {
::impl::generic::native::quantized_conv2d_nchw_out(
ctx,
input,
weight,
bias,
stride,
padding,
dilation,
groups,
in_zero_point,
weight_zero_point,
bias_scale,
output_scale,
output_zero_point,
out_multiplier,
out_shift,
out);
return;
}

const float bias_scale_float = bias_scale.const_data_ptr<float>()[0];
const int32_t weight_zero_point_int =
weight_zero_point.const_data_ptr<int32_t>()[0];
Expand Down Expand Up @@ -596,6 +621,30 @@ void quantized_conv2d_nchw_per_tensor_out(
__ET_UNUSED int64_t out_multiplier,
__ET_UNUSED int64_t out_shift,
Tensor& out) {
// Handle W8A16 heterogeneous type (int16_t activations, int8_t weights)
if (out.scalar_type() == ::executorch::aten::ScalarType::Short &&
input.scalar_type() == ::executorch::aten::ScalarType::Short &&
weight.scalar_type() == ::executorch::aten::ScalarType::Char) {
::impl::generic::native::quantized_conv2d_nchw_per_tensor_out(
ctx,
input,
weight,
bias,
stride,
padding,
dilation,
groups,
in_zero_point,
weight_zero_point,
bias_scale,
output_scale,
output_zero_point,
out_multiplier,
out_shift,
out);
return;
}

bool optimized = 0;

if ((input.scalar_type() == ScalarType::Char) ||
Expand Down
49 changes: 48 additions & 1 deletion backends/cadence/hifi/operators/op_quantized_conv2d_nhwc_out.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
#include <executorch/backends/cadence/hifi/kernels/kernels.h>
#include <executorch/backends/cadence/hifi/operators/operators.h>
#include <executorch/runtime/kernel/kernel_includes.h>
#include <on_device_ai/Assistant/Jarvis/min_runtime/operators/generic/op_quantized_conv2d.h>

#define ALIGN_PTR(x, bytes) ((((unsigned)(x)) + (bytes - 1)) & (~(bytes - 1)))

Expand Down Expand Up @@ -438,6 +439,29 @@ void quantized_conv2d_nhwc_out(
__ET_UNUSED const Tensor& out_multiplier,
__ET_UNUSED const Tensor& out_shift,
Tensor& out) {
// Handle W8A16 heterogeneous type (int16_t activations, int8_t weights)
if (out.scalar_type() == ::executorch::aten::ScalarType::Short &&
input.scalar_type() == ::executorch::aten::ScalarType::Short &&
weight.scalar_type() == ::executorch::aten::ScalarType::Char) {
::impl::generic::native::quantized_conv2d_nhwc_out(
ctx,
input,
weight,
bias,
stride,
padding,
dilation,
groups,
in_zero_point,
weight_zero_point,
bias_scale,
output_scale,
output_zero_point,
out_multiplier,
out_shift,
out);
return;
}
const float bias_scale_float = bias_scale.const_data_ptr<float>()[0];
const int32_t weight_zero_point_int =
weight_zero_point.const_data_ptr<int32_t>()[0];
Expand Down Expand Up @@ -502,8 +526,31 @@ void quantized_conv2d_nhwc_per_tensor_out(
__ET_UNUSED int64_t out_multiplier,
__ET_UNUSED int64_t out_shift,
Tensor& out) {
bool optimized = 0;
// Handle W8A16 heterogeneous type (int16_t activations, int8_t weights)
if (out.scalar_type() == ::executorch::aten::ScalarType::Short &&
input.scalar_type() == ::executorch::aten::ScalarType::Short &&
weight.scalar_type() == ::executorch::aten::ScalarType::Char) {
::impl::generic::native::quantized_conv2d_nhwc_per_tensor_out(
ctx,
input,
weight,
bias,
stride,
padding,
dilation,
groups,
in_zero_point,
weight_zero_point,
bias_scale,
output_scale,
output_zero_point,
out_multiplier,
out_shift,
out);
return;
}

bool optimized = 0;
if ((input.scalar_type() == ScalarType::Char) ||
(input.scalar_type() == ScalarType::Byte))
optimized = 1;
Expand Down
38 changes: 36 additions & 2 deletions backends/cadence/hifi/operators/op_quantized_linear_out.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
#include <executorch/backends/cadence/hifi/operators/operators.h>
#include <executorch/runtime/kernel/kernel_includes.h>
#include <xa_nnlib_kernels_api.h>
#include <on_device_ai/Assistant/Jarvis/min_runtime/operators/generic/op_quantized_linear.h>
#include <xtensa/tie/xt_datacache.h>
#include <algorithm>
#include <cmath>
Expand Down Expand Up @@ -218,7 +219,24 @@ void quantized_linear_out(
int64_t out_zero_point,
__ET_UNUSED const optional<Tensor>& offset,
Tensor& out) {
if (out.scalar_type() == executorch::aten::ScalarType::Byte) {

if (out.scalar_type() == ::executorch::aten::ScalarType::Short &&
in.scalar_type() == ::executorch::aten::ScalarType::Short &&
weight.scalar_type() == ::executorch::aten::ScalarType::Char) {
::impl::generic::native::quantized_linear_out(
ctx,
in,
weight,
bias,
in_zero_point,
weight_zero_point,
out_multiplier,
out_shift,
out_zero_point,
offset,
out);
}
else if (out.scalar_type() == executorch::aten::ScalarType::Byte) {
Comment on lines +238 to +239
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Copilot AI Nov 28, 2025

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[nitpick] The else if should be on the same line as the closing brace according to standard C++ formatting conventions. Change to } else if for consistency with typical C++ style.

Suggested change
}
else if (out.scalar_type() == executorch::aten::ScalarType::Byte) {
} else if (out.scalar_type() == executorch::aten::ScalarType::Byte) {

Copilot uses AI. Check for mistakes.
_quantized_linear_asym8u(
in,
weight,
Expand Down Expand Up @@ -260,7 +278,23 @@ void quantized_linear_per_tensor_out(
int64_t out_zero_point,
__ET_UNUSED const optional<Tensor>& offset,
Tensor& out) {
if (out.scalar_type() == executorch::aten::ScalarType::Byte) {
if (out.scalar_type() == ::executorch::aten::ScalarType::Short &&
in.scalar_type() == ::executorch::aten::ScalarType::Short &&
weight.scalar_type() == ::executorch::aten::ScalarType::Char) {
::impl::generic::native::quantized_linear_per_tensor_out(
ctx,
in,
weight,
bias,
in_zero_point,
weight_zero_point,
out_multiplier,
out_shift,
out_zero_point,
offset,
out);
}
else if (out.scalar_type() == executorch::aten::ScalarType::Byte) {
Comment on lines +296 to +297
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Copilot AI Nov 28, 2025

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The reason will be displayed to describe this comment to others. Learn more.

[nitpick] The else if should be on the same line as the closing brace according to standard C++ formatting conventions. Change to } else if for consistency with typical C++ style.

Suggested change
}
else if (out.scalar_type() == executorch::aten::ScalarType::Byte) {
} else if (out.scalar_type() == executorch::aten::ScalarType::Byte) {

Copilot uses AI. Check for mistakes.
_quantized_linear_per_tensor_asym8u(
in,
weight,
Expand Down
11 changes: 8 additions & 3 deletions backends/cadence/hifi/operators/targets.bzl
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,6 @@ OPERATORS = [
"ne",
"permute_copy",
"pow",
"quantized_conv2d_nchw_out",
"quantized_conv2d_nchw_asym8sxsym8s_asym8s_per_tensor_out",
"quantized_conv2d_nchw_asym8uxsym8u_asym8u_per_tensor_out",
"quantized_conv1d_ncl_asym8sxsym8s_asym8s_per_tensor_out",
Expand All @@ -74,7 +73,6 @@ OPERATORS = [
"quantized_conv2d_nchw_depthwise_asym8uxsym8u_asym8u_per_tensor_out",
"quantized_conv2d_nchw_dilated_asym8sxsym8s_asym8s_per_tensor_out",
"quantized_conv2d_nchw_dilated_asym8uxsym8u_asym8u_per_tensor_out",
"quantized_conv2d_nhwc_out",
"quantized_conv2d_nhwc_asym8sxsym8s_asym8s_per_tensor_out",
"quantized_conv2d_nhwc_asym8uxsym8u_asym8u_per_tensor_out",
"quantized_conv1d_nlc_asym8sxsym8s_asym8s_per_tensor_out",
Expand All @@ -87,7 +85,6 @@ OPERATORS = [
"quantized_fully_connected_asym8sxasym8s_asym8s_per_tensor_out",
"quantized_fully_connected_asym8uxasym8u_asym8u_per_tensor_out",
"quantized_layer_norm",
"quantized_linear_out",
"quantized_linear_asym8sxasym8s_asym8s_per_tensor_out",
"quantized_linear_asym8uxasym8u_asym8u_per_tensor_out",
"quantized_matmul_out",
Expand Down Expand Up @@ -122,3 +119,11 @@ def define_common_targets():
# Define build targets for all operators registered in the tables above.
for op in OPERATORS:
define_operator(op)

# quantized_linear_out and quantized_linear_per_tensor_out needs additional dependency for int16 support
define_operator("quantized_linear_out", deps=["fbcode//on_device_ai/Assistant/Jarvis/min_runtime/operators/generic:op_quantized_linear"])
define_operator("quantized_linear_per_tensor_out", deps=["fbcode//on_device_ai/Assistant/Jarvis/min_runtime/operators/generic:op_quantized_linear"])

# quantized_conv2d_nchw_out and quantized_conv2d_nhwc_out need additional dependency for int16 support
define_operator("quantized_conv2d_nchw_out", deps=["fbcode//on_device_ai/Assistant/Jarvis/min_runtime/operators/generic:op_quantized_conv2d"])
define_operator("quantized_conv2d_nhwc_out", deps=["fbcode//on_device_ai/Assistant/Jarvis/min_runtime/operators/generic:op_quantized_conv2d"])
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