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pin nightly to 2.5.0.dev20240709+cu121 (#505)
* pin nightly to 2.5.0.dev20240711+cu121 * push * Update regression_test.yml * Update regression_test.yml
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.github/workflows/regression_test.yml

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@@ -33,7 +33,7 @@ jobs:
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gpu-arch-version: "12.1"
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- name: CUDA Nightly
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runs-on: linux.g5.12xlarge.nvidia.gpu
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torch-spec: '--pre torch --index-url https://download.pytorch.org/whl/nightly/cu121'
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torch-spec: '--pre torch==2.5.0.dev20240709+cu121 --index-url https://download.pytorch.org/whl/nightly/cu121'
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gpu-arch-type: "cuda"
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gpu-arch-version: "12.1"
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- name: CPU 2.2.2
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gpu-arch-version: ""
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- name: CPU Nightly
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runs-on: linux.4xlarge
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torch-spec: '--pre torch --index-url https://download.pytorch.org/whl/nightly/cpu'
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torch-spec: '--pre torch==2.5.0.dev20240709+cpu --index-url https://download.pytorch.org/whl/nightly/cpu'
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gpu-arch-type: "cpu"
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gpu-arch-version: ""
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test/dtypes/test_uint4.py

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@@ -4,19 +4,14 @@
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PerChannelSymmetricWeightUInt4Tensor,
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)
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import unittest
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from unittest import TestCase, main
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from torch.ao.quantization.quantize_pt2e import prepare_pt2e, convert_pt2e
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from torch.ao.quantization.quantizer import QuantizationSpec, Quantizer
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from torch._export import capture_pre_autograd_graph
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from torch._export import dynamic_dim
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from torch.testing._internal.common_quantization import (
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NodeSpec as ns,
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QuantizationTestCase,
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)
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from torchao.quantization.utils import (
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compute_error,
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)
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from torchao.quantization.quant_api import (
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_replace_with_custom_fn_if_matches_filter,
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)
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QuantizationAnnotation,
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)
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import copy
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from packaging import version
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def _apply_weight_only_uint4_quant(model):
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)
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if __name__ == "__main__":
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main()
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unittest.main()

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