Registry / ai-ml / mct-quantizers

mct-quantizers

library1.7.0pypypiunverified

MCT Quantizers is a Python library that provides infrastructure for supporting neural network compression through quantization-aware training and post-training quantization. It is part of the Model Compression Toolkit (MCT) ecosystem. Version 1.7.0 requires Python >=3.10. The library is actively maintained with regular releases.

ai-ml

pip install mct-quantizers

package ↗

INSTALL

IMPORT

SIG · MCT-QUANTIZERS

mct-quantizers

ai-mlpythonv1.7.0

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Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

QuantizationConfig

✓ from mct_quantizers import QuantizationConfig

✗ from mct.quantizers import QuantizationConfig

MCT Quantizers uses underscore in package name, not dot.

PostTrainingQuantization

✓ from mct_quantizers.pytorch import PostTrainingQuantization

✗ from mct_quantizers import PostTrainingQuantization

PostTrainingQuantization is under framework-specific submodule.

Logger

✓ from mct_quantizers.logger import Logger

✗ import mct_quantizers.logger

Logger is a class, must be imported explicitly.

Basic usage: quantize a PyTorch model with post-training quantization.

import torch from mct_quantizers.pytorch import QuantizationConfig, PostTrainingQuantization # Create a simple model model = torch.nn.Sequential(torch.nn.Linear(10, 5), torch.nn.ReLU()) # Define quantization configuration config = QuantizationConfig(n_bits=8, per_channel=True) # Apply post-training quantization ptq = PostTrainingQuantization(model, config) quantized_model = ptq.quantize() # Save the quantized model torch.save(quantized_model.state_dict(), 'quantized_model.pth')

Debug

Known issues

breakingIn version 1.5.0, the import path for QuantizationConfig changed from mct_quantizers.quantization to mct_quantizers. Old code will break.

fix

Update imports: replace 'from mct_quantizers.quantization import QuantizationConfig' with 'from mct_quantizers import QuantizationConfig'.

affects: <1.5.0

deprecatedPostTrainingQuantization for TensorFlow models is deprecated since version 1.6.0 and will be removed in future releases. Use PyTorch or ONNX variants instead.

fix

If using TensorFlow, migrate your pipeline to PyTorch or use mct-quantizers with ONNX backend.

affects: ≥1.6.0

gotchaWhen using multi-GPU, the quantization process may fail if the model is not properly wrapped with DataParallel. This is not automatically handled.

fix

Wrap your model with torch.nn.DataParallel before passing to PostTrainingQuantization.

affects: all

Upgrade

Version history

1.7.0latest on PyPI · released Mar 2, 2026

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Dependencies

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Resources

packagehttps://pypi.org/project/mct-quantizers/ ↗