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intel · Sep 14, 2024 · 834d073 · 834d073
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diff --git a/.../autoapi/neural_compressor/torch/algorithms/weight_only/autoround/index.rst.txt b/.../autoapi/neural_compressor/torch/algorithms/weight_only/autoround/index.rst.txt
@@ -28,7 +28,7 @@ Functions
 Module Contents
 ---------------
 
-.. py:class:: AutoRoundQuantizer(quant_config: dict = {}, enable_full_range: bool = False, batch_size: int = 8, amp: bool = True, device: str = None, lr_scheduler=None, dataset: Union[str, list, tuple, torch.utils.data.DataLoader] = 'NeelNanda/pile-10k', enable_quanted_input: bool = True, enable_minmax_tuning: bool = True, lr: float = None, minmax_lr: float = None, low_gpu_mem_usage: bool = False, iters: int = 200, seqlen: int = 2048, nsamples: int = 128, sampler: str = 'rand', seed: int = 42, nblocks: int = 1, gradient_accumulate_steps: int = 1, not_use_best_mse: bool = False, dynamic_max_gap: int = -1, data_type: str = 'int', scale_dtype: str = 'fp16', quant_block_list: list = None, act_bits: int = 32, act_group_size: int = None, act_sym: bool = None, act_dynamic: bool = True, low_cpu_mem_usage: bool = False, **kwargs)
+.. py:class:: AutoRoundQuantizer(quant_config: dict = {}, enable_full_range: bool = False, batch_size: int = 8, amp: bool = True, device: str = None, lr_scheduler=None, dataset: Union[str, list, tuple, torch.utils.data.DataLoader] = 'NeelNanda/pile-10k', enable_quanted_input: bool = True, enable_minmax_tuning: bool = True, lr: float = None, minmax_lr: float = None, low_gpu_mem_usage: bool = False, iters: int = 200, seqlen: int = 2048, nsamples: int = 128, sampler: str = 'rand', seed: int = 42, nblocks: int = 1, gradient_accumulate_steps: int = 1, not_use_best_mse: bool = False, dynamic_max_gap: int = -1, data_type: str = 'int', scale_dtype: str = 'fp16', quant_block_list: list = None, act_bits: int = 32, act_group_size: int = None, act_sym: bool = None, act_dynamic: bool = True, low_cpu_mem_usage: bool = False, export_format: str = 'itrex', **kwargs)
 
 
 

diff --git a/.../autoapi/neural_compressor/torch/algorithms/weight_only/save_load/index.rst.txt b/.../autoapi/neural_compressor/torch/algorithms/weight_only/save_load/index.rst.txt
@@ -29,14 +29,20 @@ Functions
 Module Contents
 ---------------
 
-.. py:function:: save(model, output_dir='./saved_results')
+.. py:function:: save(model, output_dir='./saved_results', format=LoadFormat.DEFAULT, **kwargs)
 
    Save the quantized model and config to the output path.
 
    :param model: raw fp32 model or prepared model.
    :type model: torch.nn.module
    :param output_dir: output path to save.
    :type output_dir: str, optional
+   :param format: The format in which to save the model. Options include "default" and "huggingface". Defaults to "default".
+   :type format: str, optional
+   :param kwargs: Additional arguments for specific formats. For example:
+                  - safe_serialization (bool): Whether to use safe serialization when saving (only applicable for 'huggingface' format). Defaults to True.
+                  - tokenizer (Tokenizer, optional): The tokenizer to be saved along with the model (only applicable for 'huggingface' format).
+                  - max_shard_size (str, optional): The maximum size for each shard (only applicable for 'huggingface' format). Defaults to "5GB".
 
 
 .. py:function:: load(model_name_or_path, original_model=None, format=LoadFormat.DEFAULT, device='cpu', **kwargs)

diff --git a/latest/_sources/autoapi/neural_compressor/torch/quantization/config/index.rst.txt b/latest/_sources/autoapi/neural_compressor/torch/quantization/config/index.rst.txt
@@ -157,7 +157,7 @@ Module Contents
    :returns: the default teq config.
 
 
-.. py:class:: AutoRoundConfig(dtype: str = 'int', bits: int = 4, use_sym: bool = False, group_size: int = 128, act_bits: int = 32, act_group_size: int = None, act_sym: bool = None, act_dynamic: bool = True, enable_full_range: bool = False, batch_size: int = 8, lr_scheduler=None, enable_quanted_input: bool = True, enable_minmax_tuning: bool = True, lr: float = None, minmax_lr: float = None, low_gpu_mem_usage: bool = False, iters: int = 200, seqlen: int = 2048, nsamples: int = 128, sampler: str = 'rand', seed: int = 42, nblocks: int = 1, gradient_accumulate_steps: int = 1, not_use_best_mse: bool = False, dynamic_max_gap: int = -1, scale_dtype: str = 'fp16', use_layer_wise: bool = False, quant_block_list: list = None, white_list: Optional[List[neural_compressor.common.utils.OP_NAME_OR_MODULE_TYPE]] = DEFAULT_WHITE_LIST)
+.. py:class:: AutoRoundConfig(dtype: str = 'int', bits: int = 4, use_sym: bool = False, group_size: int = 128, act_bits: int = 32, act_group_size: int = None, act_sym: bool = None, act_dynamic: bool = True, enable_full_range: bool = False, batch_size: int = 8, lr_scheduler=None, enable_quanted_input: bool = True, enable_minmax_tuning: bool = True, lr: float = None, minmax_lr: float = None, low_gpu_mem_usage: bool = False, iters: int = 200, seqlen: int = 2048, nsamples: int = 128, sampler: str = 'rand', seed: int = 42, nblocks: int = 1, gradient_accumulate_steps: int = 1, not_use_best_mse: bool = False, dynamic_max_gap: int = -1, scale_dtype: str = 'fp16', use_layer_wise: bool = False, quant_block_list: list = None, export_format: str = 'itrex', white_list: Optional[List[neural_compressor.common.utils.OP_NAME_OR_MODULE_TYPE]] = DEFAULT_WHITE_LIST)
 
 
 

diff --git a/latest/autoapi/neural_compressor/adaptor/mxnet_utils/index.html b/latest/autoapi/neural_compressor/adaptor/mxnet_utils/index.html
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     <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
     provided by <a href="https://readthedocs.org">Read the Docs</a>.
-   <jinja2.runtime.BlockReference object at 0x7f548cdbc130> 
+   <jinja2.runtime.BlockReference object at 0x7f75c6de3640> 
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diff --git a/latest/autoapi/neural_compressor/adaptor/ox_utils/operators/norm/index.html b/latest/autoapi/neural_compressor/adaptor/ox_utils/operators/norm/index.html
@@ -134,7 +134,7 @@ <h2>Module Contents<a class="headerlink" href="#module-contents" title="Link to
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
     <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
     provided by <a href="https://readthedocs.org">Read the Docs</a>.
-   <jinja2.runtime.BlockReference object at 0x7f548cdbf790> 
+   <jinja2.runtime.BlockReference object at 0x7f75c6de1c00> 
   <p></p><div><a href='https://www.intel.com/content/www/us/en/privacy/intel-cookie-notice.html' data-cookie-notice='true'>Cookies</a> <a href='https://www.intel.com/content/www/us/en/privacy/intel-privacy-notice.html'>| Privacy</a></div>
 
 

diff --git a/latest/autoapi/neural_compressor/adaptor/ox_utils/operators/ops/index.html b/latest/autoapi/neural_compressor/adaptor/ox_utils/operators/ops/index.html
@@ -159,7 +159,7 @@ <h2>Module Contents<a class="headerlink" href="#module-contents" title="Link to
   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
     <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
     provided by <a href="https://readthedocs.org">Read the Docs</a>.
-   <jinja2.runtime.BlockReference object at 0x7f548cdbf1c0> 
+   <jinja2.runtime.BlockReference object at 0x7f75c6de1870> 
   <p></p><div><a href='https://www.intel.com/content/www/us/en/privacy/intel-cookie-notice.html' data-cookie-notice='true'>Cookies</a> <a href='https://www.intel.com/content/www/us/en/privacy/intel-privacy-notice.html'>| Privacy</a></div>