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[XNNPACK] torchao is installed by default #10336

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[XNNPACK] torchao is installed by default #10336

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22 changes: 4 additions & 18 deletions backends/xnnpack/partition/config/quant_affine_configs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
from typing import List, Optional

import torch
import torchao.quantization.quant_primitives # noqa
from executorch.backends.xnnpack.partition.config.xnnpack_config import (
ConfigPrecisionType,
XNNPartitionerConfig,
Expand All @@ -33,33 +34,18 @@ class QuantizeAffineConfig(QDQAffineConfigs):
target_name = "quantize_affine.default"

def get_original_aten(self) -> Optional[torch._ops.OpOverload]:
try:
import torchao.quantization.quant_primitives # noqa

return torch.ops.torchao.quantize_affine.default
except:
return None
return torch.ops.torchao.quantize_affine.default


class DeQuantizeAffineConfig(QDQAffineConfigs):
target_name = "dequantize_affine.default"

def get_original_aten(self) -> Optional[torch._ops.OpOverload]:
try:
import torchao.quantization.quant_primitives # noqa

return torch.ops.torchao.dequantize_affine.default
except:
return None
return torch.ops.torchao.dequantize_affine.default


class ChooseQParamsAffineConfig(QDQAffineConfigs):
target_name = "choose_qparams_affine.default"

def get_original_aten(self) -> Optional[torch._ops.OpOverload]:
try:
import torchao.quantization.quant_primitives # noqa

return torch.ops.torchao.choose_qparams_affine.default
except:
return None
return torch.ops.torchao.choose_qparams_affine.default
24 changes: 5 additions & 19 deletions backends/xnnpack/test/ops/test_linear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,16 +33,11 @@

from torch.export.graph_signature import ExportGraphSignature, InputKind

try:
from torchao.quantization.quant_api import (
int8_dynamic_activation_int4_weight,
quantize_,
)
from torchao.utils import unwrap_tensor_subclass

torchao_installed = True
except:
torchao_installed = False
from torchao.quantization.quant_api import (
int8_dynamic_activation_int4_weight,
quantize_,
)
from torchao.utils import unwrap_tensor_subclass


# Pytorch Modules Used for Testing
Expand Down Expand Up @@ -818,22 +813,13 @@ def test_linear_qd8_f32_per_channel_int4(self):
self._test_qd8_per_channel_4w_linear(dtype=torch.float)

# Tests for q[dp]8-f16-qb4w
@unittest.skipIf(
not torchao_installed, "Per Channel Group Quantization Required TorchAO"
)
def test_linear_qd8_f16_per_token_weight_per_channel_group_int4(self):
self._test_qd8_per_token_weight_per_channel_group_int4(dtype=torch.half)

# Tests for q[dp]8-f32-qb4w
@unittest.skipIf(
not torchao_installed, "Per Channel Group Quantization Required TorchAO"
)
def test_linear_qd8_f32_per_token_weight_per_channel_group_int4(self):
self._test_qd8_per_token_weight_per_channel_group_int4(dtype=torch.float)

@unittest.skipIf(
not torchao_installed, "Per Channel Group Quantization Required TorchAO"
)
def test_linear_qd8_per_token_groupwise_unsupported_groupsize(self):
# groupsize must be multiple of 32
for dtype in [torch.float, torch.half]:
Expand Down
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