frozenleaves/pytorch
1
0
Fork 0
mirror of https://github.com/pytorch/pytorch.git synced 2025-10-21 05:34:18 +08:00
Code Issues Packages Projects Releases Wiki Activity
Files
22ae059d32809f9bdcacf2d60f12c473ded5d451
pytorch/docs/source/quantization.rst
Angel Li 70ec464c16 [BE] document some quantization public apis (#165160) 
This PR documents some apis in `torch.ao.quantization.utils`

<img width="885" height="296" alt="Screenshot 2025-10-10 at 4 38 10 PM" src="https://github.com/user-attachments/assets/4323a6f5-ac3a-4f2e-ba00-35f3b208bef4" />
<img width="876" height="319" alt="Screenshot 2025-10-10 at 4 38 14 PM" src="https://github.com/user-attachments/assets/164822c3-9740-46f9-953d-bb20c77bcf69" />

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165160
Approved by: https://github.com/janeyx99
2025-10-13 17:24:42 +00:00

216 lines
11 KiB
ReStructuredText
Raw Blame History

.. _quantization-doc:
Quantization
============
.. automodule:: torch.ao.quantization
.. automodule:: torch.ao.quantization.fx
We are cetralizing all quantization related development to `torchao <https://github.com/pytorch/ao>`__, please checkout our new doc page: https://docs.pytorch.org/ao/stable/index.html
Plan for the existing quantization flows:
1. Eager mode quantization (torch.ao.quantization.quantize,
torch.ao.quantization.quantize_dynamic), please migrate to use torchao eager mode
`quantize_ <https://docs.pytorch.org/ao/main/generated/torchao.quantization.quantize_.html#torchao.quantization.quantize_>`__ API instead
2. FX graph mode quantization (torch.ao.quantization.quantize_fx.prepare_fx
torch.ao.quantization.quantize_fx.convert_fx, please migrate to use torchao pt2e quantization
API instead (`torchao.quantization.pt2e.quantize_pt2e.prepare_pt2e`, `torchao.quantization.pt2e.quantize_pt2e.convert_pt2e`)
3. pt2e quantization has been migrated to torchao (https://github.com/pytorch/ao/tree/main/torchao/quantization/pt2e)
see https://github.com/pytorch/ao/issues/2259 for more details
We plan to delete `torch.ao.quantization` in 2.10 if there are no blockers, or in the earliest PyTorch version until all the blockers are cleared.
Quantization API Reference (Kept since APIs are still public)
-----------------------------------------------------------------
The :doc:`Quantization API Reference <quantization-support>` contains documentation
of quantization APIs, such as quantization passes, quantized tensor operations,
and supported quantized modules and functions.
.. toctree::
:hidden:
quantization-support
.. torch.ao is missing documentation. Since part of it is mentioned here, adding them here for now.
.. They are here for tracking purposes until they are more permanently fixed.
.. py:module:: torch.ao
.. py:module:: torch.ao.nn
.. py:module:: torch.ao.nn.quantizable
.. py:module:: torch.ao.nn.quantizable.modules
.. py:module:: torch.ao.nn.quantized
.. py:module:: torch.ao.nn.quantized.reference
.. py:module:: torch.ao.nn.quantized.reference.modules
.. py:module:: torch.ao.nn.sparse
.. py:module:: torch.ao.nn.sparse.quantized
.. py:module:: torch.ao.nn.sparse.quantized.dynamic
.. py:module:: torch.ao.ns
.. py:module:: torch.ao.ns.fx
.. py:module:: torch.ao.quantization.backend_config
.. py:module:: torch.ao.pruning
.. py:module:: torch.ao.pruning.scheduler
.. py:module:: torch.ao.pruning.sparsifier
.. py:module:: torch.ao.nn.intrinsic.modules.fused
.. py:module:: torch.ao.nn.intrinsic.qat.modules.conv_fused
.. py:module:: torch.ao.nn.intrinsic.qat.modules.linear_fused
.. py:module:: torch.ao.nn.intrinsic.qat.modules.linear_relu
.. py:module:: torch.ao.nn.intrinsic.quantized.dynamic.modules.linear_relu
.. py:module:: torch.ao.nn.intrinsic.quantized.modules.bn_relu
.. py:module:: torch.ao.nn.intrinsic.quantized.modules.conv_add
.. py:module:: torch.ao.nn.intrinsic.quantized.modules.conv_relu
.. py:module:: torch.ao.nn.intrinsic.quantized.modules.linear_relu
.. py:module:: torch.ao.nn.qat.dynamic.modules.linear
.. py:module:: torch.ao.nn.qat.modules.conv
.. py:module:: torch.ao.nn.qat.modules.embedding_ops
.. py:module:: torch.ao.nn.qat.modules.linear
.. py:module:: torch.ao.nn.quantizable.modules.activation
.. py:module:: torch.ao.nn.quantizable.modules.rnn
.. py:module:: torch.ao.nn.quantized.dynamic.modules.conv
.. py:module:: torch.ao.nn.quantized.dynamic.modules.linear
.. py:module:: torch.ao.nn.quantized.dynamic.modules.rnn
.. py:module:: torch.ao.nn.quantized.modules.activation
.. py:module:: torch.ao.nn.quantized.modules.batchnorm
.. py:module:: torch.ao.nn.quantized.modules.conv
.. py:module:: torch.ao.nn.quantized.modules.dropout
.. py:module:: torch.ao.nn.quantized.modules.embedding_ops
.. py:module:: torch.ao.nn.quantized.modules.functional_modules
.. py:module:: torch.ao.nn.quantized.modules.linear
.. py:module:: torch.ao.nn.quantized.modules.normalization
.. py:module:: torch.ao.nn.quantized.modules.rnn
.. py:module:: torch.ao.nn.quantized.modules.utils
.. py:module:: torch.ao.nn.quantized.reference.modules.conv
.. py:module:: torch.ao.nn.quantized.reference.modules.linear
.. py:module:: torch.ao.nn.quantized.reference.modules.rnn
.. py:module:: torch.ao.nn.quantized.reference.modules.sparse
.. py:module:: torch.ao.nn.quantized.reference.modules.utils
.. py:module:: torch.ao.nn.sparse.quantized.dynamic.linear
.. py:module:: torch.ao.nn.sparse.quantized.linear
.. py:module:: torch.ao.nn.sparse.quantized.utils
.. py:module:: torch.ao.ns.fx.graph_matcher
.. py:module:: torch.ao.ns.fx.graph_passes
.. py:module:: torch.ao.ns.fx.mappings
.. py:module:: torch.ao.ns.fx.n_shadows_utils
.. py:module:: torch.ao.ns.fx.ns_types
.. py:module:: torch.ao.ns.fx.pattern_utils
.. py:module:: torch.ao.ns.fx.qconfig_multi_mapping
.. py:module:: torch.ao.ns.fx.weight_utils
.. py:module:: torch.ao.ns.fx.utils
.. py:module:: torch.ao.pruning.scheduler.base_scheduler
.. py:module:: torch.ao.pruning.scheduler.cubic_scheduler
.. py:module:: torch.ao.pruning.scheduler.lambda_scheduler
.. py:module:: torch.ao.pruning.sparsifier.base_sparsifier
.. py:module:: torch.ao.pruning.sparsifier.nearly_diagonal_sparsifier
.. py:module:: torch.ao.pruning.sparsifier.utils
.. py:module:: torch.ao.pruning.sparsifier.weight_norm_sparsifier
.. py:module:: torch.ao.quantization.backend_config.backend_config
.. py:module:: torch.ao.quantization.backend_config.executorch
.. py:module:: torch.ao.quantization.backend_config.fbgemm
.. py:module:: torch.ao.quantization.backend_config.native
.. py:module:: torch.ao.quantization.backend_config.onednn
.. py:module:: torch.ao.quantization.backend_config.qnnpack
.. py:module:: torch.ao.quantization.backend_config.tensorrt
.. py:module:: torch.ao.quantization.backend_config.utils
.. py:module:: torch.ao.quantization.backend_config.x86
.. py:module:: torch.ao.quantization.fake_quantize
.. py:module:: torch.ao.quantization.fuser_method_mappings
.. py:module:: torch.ao.quantization.fuse_modules
.. py:module:: torch.ao.quantization.fx.convert
.. py:module:: torch.ao.quantization.fx.custom_config
.. py:module:: torch.ao.quantization.fx.fuse
.. py:module:: torch.ao.quantization.fx.fuse_handler
.. py:module:: torch.ao.quantization.fx.graph_module
.. py:module:: torch.ao.quantization.fx.lower_to_fbgemm
.. py:module:: torch.ao.quantization.fx.lower_to_qnnpack
.. py:module:: torch.ao.quantization.fx.lstm_utils
.. py:module:: torch.ao.quantization.fx.match_utils
.. py:module:: torch.ao.quantization.fx.pattern_utils
.. py:module:: torch.ao.quantization.fx.prepare
.. py:module:: torch.ao.quantization.fx.qconfig_mapping_utils
.. py:module:: torch.ao.quantization.fx.quantize_handler
.. py:module:: torch.ao.quantization.fx.tracer
.. py:module:: torch.ao.quantization.fx.utils
.. py:module:: torch.ao.quantization.observer
.. py:module:: torch.ao.quantization.pt2e.duplicate_dq_pass
.. py:module:: torch.ao.quantization.pt2e.graph_utils
.. py:module:: torch.ao.quantization.pt2e.port_metadata_pass
.. py:module:: torch.ao.quantization.pt2e.prepare
.. py:module:: torch.ao.quantization.pt2e.qat_utils
.. py:module:: torch.ao.quantization.pt2e.representation.rewrite
.. py:module:: torch.ao.quantization.pt2e.utils
.. py:module:: torch.ao.quantization.pt2e.lowering
.. py:module:: torch.ao.quantization.qconfig
.. py:module:: torch.ao.quantization.qconfig_mapping
.. py:module:: torch.ao.quantization.quant_type
.. py:module:: torch.ao.quantization.quantization_mappings
.. py:module:: torch.ao.quantization.quantize_fx
.. py:module:: torch.ao.quantization.quantize_jit
.. py:module:: torch.ao.quantization.quantize_pt2e
.. py:module:: torch.ao.quantization.quantizer.composable_quantizer
.. py:module:: torch.ao.quantization.quantizer.embedding_quantizer
.. py:module:: torch.ao.quantization.quantizer.quantizer
.. py:module:: torch.ao.quantization.quantizer.utils
.. py:module:: torch.ao.quantization.quantizer.x86_inductor_quantizer
.. py:module:: torch.ao.quantization.quantizer.xpu_inductor_quantizer
.. py:module:: torch.ao.quantization.quantizer.xnnpack_quantizer
.. py:module:: torch.ao.quantization.quantizer.xnnpack_quantizer_utils
.. py:module:: torch.ao.quantization.stubs
.. py:module:: torch.nn.intrinsic.modules.fused
.. py:module:: torch.nn.intrinsic.qat.modules.conv_fused
.. py:module:: torch.nn.intrinsic.qat.modules.linear_fused
.. py:module:: torch.nn.intrinsic.qat.modules.linear_relu
.. py:module:: torch.nn.intrinsic.quantized.dynamic.modules.linear_relu
.. py:module:: torch.nn.intrinsic.quantized.modules.bn_relu
.. py:module:: torch.nn.intrinsic.quantized.modules.conv_relu
.. py:module:: torch.nn.intrinsic.quantized.modules.linear_relu
.. py:module:: torch.nn.qat.dynamic.modules.linear
.. py:module:: torch.nn.qat.modules.conv
.. py:module:: torch.nn.qat.modules.embedding_ops
.. py:module:: torch.nn.qat.modules.linear
.. py:module:: torch.nn.quantizable.modules.activation
.. py:module:: torch.nn.quantizable.modules.rnn
.. py:module:: torch.nn.quantized.dynamic.modules.conv
.. py:module:: torch.nn.quantized.dynamic.modules.linear
.. py:module:: torch.nn.quantized.dynamic.modules.rnn
.. py:module:: torch.nn.quantized.functional
.. py:module:: torch.nn.quantized.modules.activation
.. py:module:: torch.nn.quantized.modules.batchnorm
.. py:module:: torch.nn.quantized.modules.conv
.. py:module:: torch.nn.quantized.modules.dropout
.. py:module:: torch.nn.quantized.modules.embedding_ops
.. py:module:: torch.nn.quantized.modules.functional_modules
.. py:module:: torch.nn.quantized.modules.linear
.. py:module:: torch.nn.quantized.modules.normalization
.. py:module:: torch.nn.quantized.modules.rnn
.. py:module:: torch.nn.quantized.modules.utils
.. py:module:: torch.quantization.fake_quantize
.. py:module:: torch.quantization.fuse_modules
.. py:module:: torch.quantization.fuser_method_mappings
.. py:module:: torch.quantization.fx.convert
.. py:module:: torch.quantization.fx.fuse
.. py:module:: torch.quantization.fx.fusion_patterns
.. py:module:: torch.quantization.fx.graph_module
.. py:module:: torch.quantization.fx.match_utils
.. py:module:: torch.quantization.fx.pattern_utils
.. py:module:: torch.quantization.fx.prepare
.. py:module:: torch.quantization.fx.quantization_patterns
.. py:module:: torch.quantization.fx.quantization_types
.. py:module:: torch.quantization.fx.utils
.. py:module:: torch.quantization.observer
.. py:module:: torch.quantization.qconfig
.. py:module:: torch.quantization.quant_type
.. py:module:: torch.quantization.quantization_mappings
.. py:module:: torch.quantization.quantize
.. py:module:: torch.quantization.quantize_fx
.. py:module:: torch.quantization.quantize_jit
.. py:module:: torch.quantization.stubs
.. py:module:: torch.quantization.utils
.. currentmodule:: torch.ao.ns.fx.utils
.. autofunction:: torch.ao.ns.fx.utils.compute_sqnr(x, y)
.. autofunction:: torch.ao.ns.fx.utils.compute_normalized_l2_error(x, y)
.. autofunction:: torch.ao.ns.fx.utils.compute_cosine_similarity(x, y)
Reference in New Issue View Git Blame Copy Permalink