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Fix torchao quantization for deployment targets under iOS18 #13896

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Merged
merged 2 commits into from
Sep 5, 2025
Merged

Fix torchao quantization for deployment targets under iOS18 #13896

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7e76b69
Fix CoreML torchao-quant for iOS16
metascroy Sep 3, 2025
fc4e8fe
up
metascroy Sep 3, 2025
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1 change: 0 additions & 1 deletion backends/apple/coreml/compiler/torch_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -175,7 +175,6 @@ def dequantize_affine(context, node):
int_data.astype(quantized_np_dtype),
zero_point,
scale,
axis=-1,
name=node.name,
)
context.add(output, node.name)
Expand Down
32 changes: 30 additions & 2 deletions backends/apple/coreml/test/test_torch_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,9 +27,9 @@
class TestTorchOps(unittest.TestCase):
edge_compile_config = executorch.exir.EdgeCompileConfig()

def _coreml_partitioner(self):
def _coreml_partitioner(self, *, minimum_deployment_target=ct.target.iOS18):
compile_specs = CoreMLBackend.generate_compile_specs(
minimum_deployment_target=ct.target.iOS18
minimum_deployment_target=minimum_deployment_target
)
return CoreMLPartitioner(compile_specs=compile_specs)

Expand Down Expand Up @@ -158,6 +158,33 @@ def test_dequantize_affine_c8w_embedding_b4w_linear(self):
et_prog = delegated_program.to_executorch()
self._compare_outputs(et_prog, model, example_inputs)

def test_dequantize_affine_c8w_embedding_c8w_linear_ios16(self):
model, example_inputs = self._get_test_model()
quantize_(
model,
IntxWeightOnlyConfig(weight_dtype=torch.int8, granularity=PerAxis(0)),
lambda m, fqn: isinstance(m, torch.nn.Embedding),
)
quantize_(
model,
IntxWeightOnlyConfig(weight_dtype=torch.int8, granularity=PerAxis(0)),
)
ep = torch.export.export(model, example_inputs)
delegated_program = executorch.exir.to_edge_transform_and_lower(
ep,
partitioner=[
self._coreml_partitioner(minimum_deployment_target=ct.target.iOS16)
],
)
for node in delegated_program.exported_program().graph.nodes:
if node.op == "call_function":
assert node.target.__name__ in [
"executorch_call_delegate",
"getitem",
], f"Got unexpected node target after delegation: {node.target.__name__}"
et_prog = delegated_program.to_executorch()
self._compare_outputs(et_prog, model, example_inputs)

def test_dequantize_codebook_linear_per_grouped_col(self):
model, example_inputs = self._get_test_model()
quantize_(
Expand Down Expand Up @@ -298,6 +325,7 @@ def forward(self, x):
test_runner.test_dequantize_affine_c4w_embedding()
test_runner.test_dequantize_affine_c4w_linear()
test_runner.test_dequantize_affine_c8w_embedding_b4w_linear()
test_runner.test_dequantize_affine_c8w_embedding_c8w_linear_ios16()
test_runner.test_dequantize_codebook_linear_per_grouped_col()
test_runner.test_dequantize_codebook_linear_per_grouped_row()
test_runner.test_dequantize_codebook_embedding_per_grouped_col()
Expand Down
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