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Merged
facebook-github-bot merged 1 commit into from
Dec 6, 2024
Merged

Check group size is divisible by 32 #6941

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17 changes: 10 additions & 7 deletions backends/xnnpack/operators/node_visitor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -309,27 +309,30 @@ def _check_per_channel_group_params(
num_groups = cast(torch.Tensor, quant_params.scale).shape[1]
assert (
quant_params.axis == 0
), "For per_channel_group quant, axis must be 0, but got {axis}"
), f"For per_channel_group quant, axis must be 0, but got {quant_params.axis}"
assert (
len(dims) == 2
), "For per_channel_group quant, expecting linear weights to be 2d, but got {len(dims)}"
), f"For per_channel_group quant, expecting linear weights to be 2d, but got {len(dims)}"
assert (
num_groups > 0 and quant_params.group_size > 0
), "For per_channel_group quant, num_groups and group_size must be > 0, but got num_groups: {num_groups}, group_size: {quant_params.group_size}"
), f"For per_channel_group quant, num_groups and group_size must be > 0, but got num_groups: {num_groups}, group_size: {quant_params.group_size}"
output_channels = dims[quant_params.axis]
input_channels = dims[quant_params.axis ^ 1]
assert (
quant_params.group_size % 32 == 0
), f"Delegation to XNNPACK requires group_size to be a multiple of 32, but got {quant_params.group_size}"
assert (
output_channels == cast(torch.Tensor, quant_params.scale).shape[0]
), "For per_channel_group quant, expecting output channels to match scale.shape[0], gut got: {output_channels}, scale.shape[0]: {quant_params.scale.shape[0]}"
), f"For per_channel_group quant, expecting output channels to match scale.shape[0], gut got: {output_channels}, scale.shape[0]: {quant_params.scale.shape[0]}"
assert (
input_channels % num_groups == 0
), "For per_channel_group quant, expecting input channels to be divisible by num_groups, but got ic: {input_channels}, num_groups: {num_groups}"
), f"For per_channel_group quant, expecting input channels to be divisible by num_groups, but got ic: {input_channels}, num_groups: {num_groups}"
assert (
input_channels % quant_params.group_size == 0
), "For per_channel_group quant, expecting input channels to be divisible by group_size, but got ic: {input_channels}, group_size: {quant_params.group_size}"
), f"For per_channel_group quant, expecting input channels to be divisible by group_size, but got ic: {input_channels}, group_size: {quant_params.group_size}"
assert (
input_channels / quant_params.group_size == num_groups
), "For per_channel_group quant, expecting input channels // group_size == num_groups, but got ic: {input_channels}, group_size: {quant_params.group_size}, num_groups: {num_groups}"
), f"For per_channel_group quant, expecting input channels // group_size == num_groups, but got ic: {input_channels}, group_size: {quant_params.group_size}, num_groups: {num_groups}"

# For now group quantization is only supported for 4b weights
assert quant_params.is_qc4w, "Only 4b group quantization is supported"
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22 changes: 22 additions & 0 deletions backends/xnnpack/test/ops/linear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -458,6 +458,28 @@ def test_qd8_fp16_per_token_weight_per_channel_group_int4(self):
lin_mod, inputs, group_size=bl, use_bias=use_bias, atol=1e-2
)

@unittest.skipIf(
not torchao_installed, "Per Channel Group Quantization Required TorchAO"
)
def test_qd8_fp32_per_token_groupwise_unsupported_groupsize(self):
# groupsize must be multiple of 32
lin_mod = BaseLinear(
in_size=1,
input_channels=60,
output_channels=60,
dtype=torch.float32,
use_bias=True,
)
inputs = lin_mod.get_inputs()

with self.assertRaisesRegex(
AssertionError,
"Delegation to XNNPACK requires group_size to be a multiple of 32, but got 30",
):
self._test_groupwise_dq_linear(
lin_mod, inputs, group_size=30, use_bias=False, atol=1e-2
)

def _test_linear(
self,
make_module,
Expand Down