Fix GPTQ for inputs with batch size != 1 and with seq len == 1 #3002
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This PR resolves 155538 |
andreyanufr
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Oct 22, 2024
ljaljushkin
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ljaljushkin
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Oct 23, 2024
| @@ -264,7 +264,7 @@ def _quantize_weights( | |||
| scales.append(scale) | |||
| else: | |||
| if self._scale_estimation and block_compression_config.num_bits == 4: | |||
| activations = [inp.squeeze()[:, (i1 + i) : (i1 + i + group_size)] for inp in inputs] | |||
| activations = [inp[..., (i1 + i) : (i1 + i + group_size)] for inp in inputs] | |||
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Slice by last dimension, which is supposed to be hidden one.
It's aligned with processing statistics in activations_to_wc_statistics when reduction axes are all dimensions except the last one @nikita-savelyevv
| [ | ||
| LMLinearModel.INPUT_SHAPE, | ||
| [3, 5, 16], | ||
| [1, 1, 16], |
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Added test case for the bug 155538 with tiny-llama example. The root cause is not filtered data with sequence length == 1.
@kshpv
| "input_shape", | ||
| [ | ||
| LMLinearModel.INPUT_SHAPE, | ||
| [3, 5, 16], |
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test case to cover SD case with batch size != 1
nikita-savelyevv
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Oct 23, 2024
alexsu52
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Oct 24, 2024
andreyanufr
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Oct 24, 2024
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Changes
GPTQ correctly processes inputs with batch size != 1 and with batch size and sequence length equal 1.
Also changed the errors we are raising in NNCF from built-in Python errors to NNCF-specific ones.
Reason for changes
Stable-diffusion models, e.g.
runwayml/stable-diffusion-v1-5has as an input for linear layers with the following shapes:[2*num_images_in_prompt, text_embedding_size, hidden_dimension].https://github.com/openvinotoolkit/nncf/blob/develop/examples/llm_compression/openvino/tiny_llama/main.py
uses not filtered data from
wikitextthat leads to the corner case with sequence length == 1.Related tickets
150851, 155538
Tests
CI