Update docsrc (sony#989)

* Automate manual parts of creating pages in docsrc Makefile.
* Remove the old API dir and use the experimental old dir as the current API in docsrs.
* Update documentation in classes that are auto-generated.
* Adapt docsrc to new API.

---------

Co-authored-by: reuvenp <reuvenp@altair-semi.com>

docsrc/Makefile

@@ -6,11 +6,13 @@ github:
 	@cp -a ../docs/html/. ../docs
 	@rm -rf ../docs/html/
 	@rm -rf ../docs/doctrees/
+	@find ../docs -type f -exec sed -i 's|_images/|images/|g' {} +
+	@find ../docs -type f -exec sed -i 's|_static/|static/|g' {} +
+	@rm -rf ../docs/images
+	@rm -rf ../docs/static
+	@mv ../docs/_images/ ../docs/images
+	@mv ../docs/_static/ ../docs/static
 
-# rm -rf ../docs/images/
-# rm -rf ../docs/statis/
-# mv ../docs/_images/ ../docs/images
-# mv ../docs/_static/ ../docs/static
 
 
 # You can set these variables from the command line, and also

docsrc/source/api/api_docs/classes/DataGenerationConfig.rst

@@ -0,0 +1,68 @@
+:orphan:
+
+.. _ug-DataGenerationConfig:
+
+================================================
+Data Generation Configuration
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.DataGenerationConfig
+    :members:
+
+
+ImageGranularity
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.ImageGranularity
+    :members:
+
+
+SchedulerType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.SchedulerType
+    :members:
+
+
+
+BatchNormAlignemntLossType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.BatchNormAlignemntLossType
+    :members:
+
+
+OutputLossType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.OutputLossType
+    :members:
+
+
+DataInitType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.DataInitType
+    :members:
+
+
+BNLayerWeightingType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.BNLayerWeightingType
+    :members:
+
+
+ImagePipelineType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.ImagePipelineType
+    :members:
+
+
+ImageNormalizationType
+================================================
+
+.. autoclass:: model_compression_toolkit.data_generation.ImageNormalizationType
+    :members:
+

docsrc/source/api/experimental_api_docs/classes/FolderImageLoader.rst → docsrc/source/api/api_docs/classes/FolderImageLoader.rst

@@ -8,7 +8,7 @@ Folder Image Loader API
 
 **The following API can be used to load a folder of images to create a representative dataset for PTQ calibration**
 
-.. autoclass:: model_compression_toolkit.FolderImageLoader
+.. autoclass:: model_compression_toolkit.core.FolderImageLoader
     :members:
 
 

docsrc/source/api/experimental_api_docs/classes/FrameworkInfo.rst → docsrc/source/api/api_docs/classes/FrameworkInfo.rst

@@ -9,7 +9,7 @@ FrameworkInfo Class
 
 **The following API can be used to pass MCT framework-related information to use when optimizing the network**
 
-.. autoclass:: model_compression_toolkit.FrameworkInfo
+.. autoclass:: model_compression_toolkit.core.FrameworkInfo
 
 
 |
@@ -19,5 +19,5 @@ ChannelAxis
 ==========================
 **Enum to select the output channels format in the model:**
 
-.. autoclass:: model_compression_toolkit.ChannelAxis
+.. autoclass:: model_compression_toolkit.core.ChannelAxis
 

docsrc/source/api/experimental_api_docs/classes/GradientPTQConfig.rst → docsrc/source/api/api_docs/classes/GradientPTQConfig.rst

@@ -2,15 +2,6 @@
 
 .. _ug-GradientPTQConfig:
 
-=================================
-GradientPTQConfigV2 Class
-=================================
-
-**The following API can be used to create a GradientPTQConfigV2 instance which can be used for post training quantization using knowledge distillation from a teacher (float model) to a student (the quantized model). This is experimental and subject to future changes.**
-
-.. autoclass:: model_compression_toolkit.gptq.GradientPTQConfigV2
-    :members:
-
 
 =================================
 GradientPTQConfig Class
@@ -31,3 +22,11 @@ GPTQHessianScoresConfig Class
 
 .. autoclass:: model_compression_toolkit.gptq.GPTQHessianScoresConfig
     :members:
+
+
+=================================
+RoundingType
+=================================
+
+.. autoclass:: model_compression_toolkit.gptq.RoundingType
+    :members:

docsrc/source/api/api_docs/classes/KPI.rst

@@ -0,0 +1,11 @@
+:orphan:
+
+.. _ug-KPI:
+
+
+KPI
+================================
+**Object to configure resources to use when searching for a configuration for the optimized model (such as in mixed-precision, pruning, etc.):**
+
+.. autoclass:: model_compression_toolkit.core.KPI
+

docsrc/source/api/api_docs/classes/MixedPrecisionQuantizationConfig.rst

@@ -0,0 +1,11 @@
+:orphan:
+
+.. _ug-MixedPrecisionQuantizationConfig:
+
+
+MixedPrecisionQuantizationConfig
+===================================
+**Class to configure the quantization process of the model when quantizing in mixed-precision:**
+
+.. autoclass:: model_compression_toolkit.core.MixedPrecisionQuantizationConfig
+

docsrc/source/api/api_docs/classes/MpDistanceWeighting.rst

@@ -0,0 +1,12 @@
+:orphan:
+
+.. _ug-MpDistanceWeighting:
+
+
+=================================
+MpDistanceWeighting
+=================================
+
+.. autoclass:: model_compression_toolkit.core.MpDistanceWeighting
+    :members:
+

docsrc/source/api/api_docs/classes/PruningConfig.rst

@@ -0,0 +1,30 @@
+:orphan:
+
+.. _ug-PruningConfig:
+
+================================================
+Pruning Configuration
+================================================
+
+.. autoclass:: model_compression_toolkit.pruning.PruningConfig
+    :members:
+
+
+ImportanceMetric
+================================================
+
+.. autoclass:: model_compression_toolkit.pruning.ImportanceMetric
+    :members:
+
+
+ChannelsFilteringStrategy
+================================================
+
+.. autoclass:: model_compression_toolkit.pruning.ChannelsFilteringStrategy
+    :members:
+
+
+
+
+
+

docsrc/source/api/api_docs/classes/PruningInfo.rst

@@ -0,0 +1,11 @@
+:orphan:
+
+.. _ug-PruningInfo:
+
+================================================
+Pruning Information
+================================================
+
+.. autoclass:: model_compression_toolkit.pruning.PruningInfo
+    :members:
+

docsrc/source/api/api_docs/classes/QuantizationConfig.rst

@@ -0,0 +1,10 @@
+:orphan:
+
+.. _ug-QuantizationConfig:
+
+
+QuantizationConfig
+==========================
+**Class to configure the quantization process of the model:**
+
+.. autoclass:: model_compression_toolkit.core.QuantizationConfig

docsrc/source/api/api_docs/classes/QuantizationErrorMethod.rst

@@ -0,0 +1,11 @@
+:orphan:
+
+.. _ug-QuantizationErrorMethod:
+
+
+QuantizationErrorMethod
+==========================
+**Enum to select a method for quantization parameters' selection:**
+
+.. autoclass:: model_compression_toolkit.core.QuantizationErrorMethod
+

docsrc/source/api/api_docs/index.rst

@@ -7,8 +7,6 @@
 API Docs
 =========
 
-.. note:: This API will be removed in future releases. Please switch to the :ref:`new API<ug-experimental_api_docs>`
-
 **Init module for MCT API.**
 
 .. code-block:: python
@@ -17,30 +15,96 @@ API Docs
 
 |
 
-Functions
-=========
-- :ref:`pytorch_post_training_quantization<ug-pytorch_post_training_quantization>`: Function to use for post training quantization of Pytorch models.
-- :ref:`pytorch_post_training_quantization_mixed_precision<ug-pytorch_post_training_quantization_mixed_precision>`: Function to use for mixed-precision post training quantization of Pytorch models (experimental).
-- :ref:`keras_post_training_quantization<ug-keras_post_training_quantization>`: Function to use for post training quantization of Keras models.
-- :ref:`keras_post_training_quantization_mixed_precision<ug-keras_post_training_quantization_mixed_precision>`: Function to use for mixed-precision post training quantization of Keras models (experimental).
-- :ref:`get_keras_gptq_config<ug-get_keras_gptq_config>`: Function to create a GradientPTQConfig instance to use for Keras models when using GPTQ (experimental).
-- :ref:`get_target_platform_capabilities<ug-get_target_platform_capabilities>`: Function to get a target platform model for Tensorflow and Pytorch.
-- :ref:`keras_kpi_data<ug-keras_kpi_data>`: Function to compute KPI data that can be used to calculate the desired target KPI for mixed-precision quantization of Keras models.
-- :ref:`pytorch_kpi_data<ug-pytorch_kpi_data>`: Function to compute KPI data that can be used to calculate the desired target KPI for mixed-precision quantization of PyTorch models.
+
+ptq
+====
+
+- :ref:`pytorch_post_training_quantization<ug-pytorch_post_training_quantization>`: A function to use for post training quantization of PyTorch models.
+- :ref:`keras_post_training_quantization<ug-keras_post_training_quantization>`: A function to use for post training quantization of Keras models.
+
+gptq
+====
+
+- :ref:`pytorch_gradient_post_training_quantization<ug-pytorch_gradient_post_training_quantization>`: A function to use for gradient-based post training quantization of Pytorch models.
+- :ref:`get_pytorch_gptq_config<ug-get_pytorch_gptq_config>`: A function to create a GradientPTQConfig instance to use for Pytorch models when using GPTQ.
+
+- :ref:`keras_gradient_post_training_quantization<ug-keras_gradient_post_training_quantization>`: A function to use for gradient-based post training quantization of Keras models.
+- :ref:`get_keras_gptq_config<ug-get_keras_gptq_config>`: A function to create a GradientPTQConfig instance to use for Keras models when using GPTQ.
+
+- :ref:`GradientPTQConfig<ug-GradientPTQConfig>`: Class to configure GradientPTQ options for gradient based post training quantization.
+
+qat
+====
+
+- :ref:`pytorch_quantization_aware_training_init_experimental<ug-pytorch_quantization_aware_training_init_experimental>`: A function to use for preparing a Pytorch model for Quantization Aware Training (experimental).
+- :ref:`pytorch_quantization_aware_training_finalize_experimental<ug-pytorch_quantization_aware_training_finalize_experimental>`: A function to finalize a Pytorch model after Quantization Aware Training to a model without QuantizeWrappers (experimental).
+- :ref:`keras_quantization_aware_training_init_experimental<ug-keras_quantization_aware_training_init_experimental>`: A function to use for preparing a Keras model for Quantization Aware Training (experimental).
+- :ref:`keras_quantization_aware_training_finalize_experimental<ug-keras_quantization_aware_training_finalize_experimental>`: A function to finalize a Keras model after Quantization Aware Training to a model without QuantizeWrappers (experimental).
+- :ref:`qat_config<ug-qat_config>`: Module to create quantization configuration for Quantization-aware Training (experimental).
+
+core
+=====
+
+- :ref:`CoreConfig<ug-CoreConfig>`: Module to contain configurations of the entire optimization process.
+- :ref:`QuantizationConfig<ug-QuantizationConfig>`: Module to configure the quantization process.
+- :ref:`QuantizationErrorMethod<ug-QuantizationErrorMethod>`: Select a method for quantization parameters' selection.
+- :ref:`MixedPrecisionQuantizationConfig<ug-MixedPrecisionQuantizationConfig>`: Module to configure the quantization process when using mixed-precision PTQ.
+- :ref:`KPI<ug-KPI>`: Module to configure resources to use when searching for a configuration for the optimized model.
+- :ref:`MpDistanceWeighting<ug-MpDistanceWeighting>`: Mixed precision distance metric weighting methods.
+- :ref:`network_editor<ug-network_editor>`: Module to modify the optimization process for troubleshooting.
+- :ref:`FolderImageLoader<ug-FolderImageLoader>`: Class to use an images directory as a representative dataset.
+- :ref:`pytorch_kpi_data<ug-pytorch_kpi_data>`: A function to compute KPI data that can be used to calculate the desired target KPI for PyTorch models.
+- :ref:`keras_kpi_data<ug-keras_kpi_data>`: A function to compute KPI data that can be used to calculate the desired target KPI for Keras models.
+
+
+data_generation
+=================
+
+- :ref:`pytorch_data_generation_experimental<ug-pytorch_data_generation_experimental>`: A function to generate data for a Pytorch model (experimental).
+- :ref:`get_pytorch_data_generation_config<ug-get_pytorch_data_generation_config>`: A function to load a DataGenerationConfig for Pytorch data generation (experimental).
+- :ref:`keras_data_generation_experimental<ug-keras_data_generation_experimental>`: A function to generate data for a Keras model (experimental).
+- :ref:`get_keras_data_generation_config<ug-get_keras_data_generation_config>`: A function to generate a DataGenerationConfig for Tensorflow data generation (experimental).
+- :ref:`DataGenerationConfig<ug-DataGenerationConfig>`: A configuration class for the data generation process (experimental).
 
 
-Modules
+pruning
+===========
+
+- :ref:`pytorch_pruning_experimental<ug-pytorch_pruning_experimental>`: A function to apply structured pruning for Pytorch models (experimental).
+- :ref:`keras_pruning_experimental<ug-keras_pruning_experimental>`: A function to apply structured pruning for Keras models (experimental).
+
+- :ref:`PruningConfig<ug-PruningConfig>`: Configuration for the pruning process (experimental).
+- :ref:`PruningInfo<ug-PruningInfo>`: Information about the pruned model such as pruned channel indices, etc. (experimental).
+
+
+exporter
 =========
-- :ref:`quantization_config<ug-quantization_config>`: Module to configure the quantization process.
-- :ref:`mixed_precision_quantization_config<ug-mixed_precision_quantization_config>`: Module to configure the quantization process when using mixed-precision PTQ.
-- :ref:`network_editor<ug-network_editor>`: Module to edit your model during the quantization process.
+
+- :ref:`exporter<ug-exporter>`: Module that enables to export a quantized model in different serialization formats.
+
+
+trainable_infrastructure
+=========================
+
+- :ref:`trainable_infrastructure<ug-trainable_infrastructure>`: Module that contains quantization abstraction and quantizers for hardware-oriented model optimization tools.
+
+
+
+set_log_folder
+================
+- :ref:`set_log_folder<ug-set_log_folder>`: Function to set the logger path directory and to enable logging.
+
+keras_load_quantized_model
+============================
+- :ref:`keras_load_quantized_model<ug-keras_load_quantized_model>`: A function to load a quantized keras model.
+
+
+target_platform
+================
 - :ref:`target_platform<ug-target_platform>`: Module to create and model hardware-related settings to optimize the model according to, by the hardware the optimized model will use during inference.
+- :ref:`get_target_platform_capabilities<ug-get_target_platform_capabilities>`: A function to get a target platform model for Tensorflow and Pytorch.
+- :ref:`DefaultDict<ug-DefaultDict>`: Util class for creating a TargetPlatformCapabilities.
 
-Classes
-=========
-- :ref:`GradientPTQConfig<ug-GradientPTQConfig>`: Class to configure GradientPTQC options for gradient based post training quantization.
-- :ref:`FolderImageLoader<ug-FolderImageLoader>`: Class to use an images directory as a representative dataset.
-- :ref:`FrameworkInfo<ug-FrameworkInfo>`: Class to wrap framework information to be used by MCT when optimizing models.
 
 Indices and tables
 ==================

docsrc/source/api/api_docs/methods/keras_data_generation_experimental.rst

@@ -0,0 +1,10 @@
+:orphan:
+
+.. _ug-keras_data_generation_experimental:
+
+
+=====================================
+Keras Data Generation
+=====================================
+
+.. autofunction:: model_compression_toolkit.data_generation.keras_data_generation_experimental

docsrc/source/api/experimental_api_docs/methods/keras_gradient_post_training_quantization_experimental.rst → docsrc/source/api/api_docs/methods/keras_gradient_post_training_quantization.rst

@@ -1,10 +1,10 @@
 :orphan:
 
-.. _ug-keras_gradient_post_training_quantization_experimental:
+.. _ug-keras_gradient_post_training_quantization:
 
 
 ================================================
 Keras Gradient Based Post Training Quantization
 ================================================
 
-.. autofunction:: model_compression_toolkit.gptq.keras_gradient_post_training_quantization_experimental
+.. autofunction:: model_compression_toolkit.gptq.keras_gradient_post_training_quantization

docsrc/source/api/api_docs/methods/keras_kpi_data.rst

@@ -7,4 +7,4 @@
 Get KPI information for Keras Models
 =======================================
 
-.. autofunction:: model_compression_toolkit.keras_kpi_data
+.. autofunction:: model_compression_toolkit.core.keras_kpi_data