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[MO] Clean up Model Optimizer options, help, and documentation (#10653)

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* [MO] Clean-up MO cmd-line options

Remove the following Model Optimizer deprecated options that are no longer used for several releases: disable_fusing, disable_gfusing, generate_deprecated_IR_V7,
legacy_ir_generation, keep_shape_ops, move_to_preprocess
Deprecate through CLI the following options for which functionality triggered from POT or automatically: disable_weights_compression, disable_nhwc_to_nchw,
disable_resnet_optimization, finegrain_fusing.
Correct and extend description of each MO option to be printed during model conversion.

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Correct documentation about input shapes

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Perform final corrections in documentation

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Remove legacy_ir_generation overall

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Clean-up tests from deprecated options

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Recover disable_fusing option as deprecated

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Fix keys for static_shape and extensions

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Remove extension key that does not work

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Apply feedback: remove disable_gfusing, correct docs

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Recover disable_fusing option for unit-tests

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Apply feedback for documentation

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Apply feedback about parameters use_legacy_frontend and use_new_frontend

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* DO minor fixes for indentation of MO logs

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Revert log.error for fallback message

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>

* Revert disable_weights_compression parameter for tests

Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev
2022-03-01 10:57:24 +03:00
committed by GitHub
parent 9da124544a
commit 6c78715749
8 changed files with 79 additions and 85 deletions
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56
docs/MO_DG/prepare_model/convert_model/Converting_Model.md
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@@ -24,7 +24,7 @@
To convert the model to the Intermediate Representation (IR), run Model Optimizer using the following command:
```sh
mo --input_model INPUT_MODEL --output_dir <OUTPUT_MODEL_DIR>
mo --input_model INPUT_MODEL
```
The output directory must have write permissions, so you can run Model Optimizer from the output directory or specify an output path with the `--output_dir` option.
@@ -71,12 +71,9 @@ Framework-agnostic parameters:
square brackets, for example [1,3,227,227] or
(1,227,227,3), where the order of dimensions depends
on the framework input layout of the model. For
example, [N,C,H,W] is used for Caffe* models and
[N,H,W,C] for TensorFlow* models. Model Optimizer
performs necessary transformations to convert the
shape to the layout required by Inference Engine
(N,C,H,W). The shape should not contain undefined
dimensions (? or -1) and should fit the dimensions
example, [N,C,H,W] is used for ONNX* models and
[N,H,W,C] for TensorFlow* models. The shape can contain
undefined dimensions (? or -1) and should fit the dimensions
defined in the input operation of the graph. Boundaries
of undefined dimension can be specified with ellipsis,
for example [1,1..10,128,128]. One boundary can be undefined,
@@ -156,13 +153,12 @@ Framework-agnostic parameters:
original model is in FP32 and --data_type=FP16 is
specified, all model weights and biases are compressed
to FP16.
--disable_fusing Turn off fusing of linear operations to Convolution
--disable_fusing [DEPRECATED] Turn off fusing of linear operations to Convolution.
--disable_resnet_optimization
Turn off resnet optimization
[DEPRECATED] Turn off ResNet optimization.
--finegrain_fusing FINEGRAIN_FUSING
Regex for layers/operations that won't be fused.
[DEPRECATED] Regex for layers/operations that won't be fused.
Example: --finegrain_fusing Convolution1,.*Scale.*
--disable_gfusing Turn off fusing of grouped convolutions
--enable_concat_optimization
Turn on Concat optimization.
--extensions EXTENSIONS
@@ -187,7 +183,7 @@ Framework-agnostic parameters:
to `Constant`). Changing model input shape using
the OpenVINO Runtime API in runtime may fail for such an IR.
--disable_weights_compression
Disable compression and store weights with original
[DEPRECATED] Disable compression and store weights with original
precision.
--progress Enable model conversion progress display.
--stream_output Switch model conversion progress display to a
@@ -195,8 +191,13 @@ Framework-agnostic parameters:
--transformations_config TRANSFORMATIONS_CONFIG
Use the configuration file with transformations
description.
--use_new_frontend Force the usage of new frontend API for model processing.
--use_legacy_frontend Force the usage of legacy API for model processing.
--use_new_frontend Force the usage of new Frontend of Model Optimizer for model conversion into IR.
The new Frontend is C++ based and is available for ONNX* and PaddlePaddle* models.
Model optimizer uses new Frontend for ONNX* and PaddlePaddle* by default that means
`--use_new_frontend` and `--use_legacy_frontend` options are not specified.
--use_legacy_frontend Force the usage of legacy Frontend of Model Optimizer for model conversion into IR.
The legacy Frontend is Python based and is available for TensorFlow*, ONNX*, MXNet*,
Caffe*, and Kaldi* models.
```
The sections below provide details on using particular parameters and examples of CLI commands.
@@ -218,7 +219,8 @@ There is no a universal recipe for determining the mean/scale values for a parti
* Open the model in a visualization tool and check for layers performing subtraction or multiplication (like `Sub`, `Mul`, `ScaleShift`, `Eltwise` etc) of the input data. If such layers exist, pre-processing is probably part of the model.
## When to Specify Input Shapes <a name="when_to_specify_input_shapes"></a>
There are situations when the input data shape for the model is not fixed, like for the fully-convolutional neural networks. In this case, for example, TensorFlow\* models contain `-1` values in the `shape` attribute of the `Placeholder` operation. Inference Engine does not support input layers with undefined size, so if the input shapes are not defined in the model, the Model Optimizer fails to convert the model. The solution is to provide the input shape(s) using the `--input` or `--input_shape` command line parameter for all input(s) of the model or provide the batch size using the `-b` command line parameter if the model contains just one input with undefined batch size only. In the latter case, the `Placeholder` shape for the TensorFlow\* model looks like this `[-1, 224, 224, 3]`.
There are situations when Model Optimizer is unable to deduce input shapes of the model, for example, in case of model cutting due to unsupported operations.
The solution is to provide input shapes of a static rank explicitly.
## When to Reverse Input Channels <a name="when_to_reverse_input_channels"></a>
Input data for your application can be of RGB or BRG color input order. For example, OpenVINO Samples load input images in the BGR channels order. However, the model may be trained on images loaded with the opposite order (for example, most TensorFlow\* models are trained with images in RGB order). In this case, inference results using the OpenVINO samples may be incorrect. The solution is to provide `--reverse_input_channels` command line parameter. Taking this parameter, the Model Optimizer performs first convolution or other channel dependent operation weights modification so these operations output will be like the image is passed with RGB channels order.
@@ -231,54 +233,50 @@ Resulting Intermediate Representation will not be resizable with the help of Ope
Launch the Model Optimizer for the Caffe bvlc_alexnet model with debug log level:
```sh
mo --input_model bvlc_alexnet.caffemodel --log_level DEBUG --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --log_level DEBUG
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with the output IR called `result.*` in the specified `output_dir`:
```sh
mo --input_model bvlc_alexnet.caffemodel --model_name result --output_dir /../../models/
mo --input_model bvlc_alexnet.caffemodel --model_name result --output_dir <OUTPUT_MODEL_DIR>
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with one input with scale values:
```sh
mo --input_model bvlc_alexnet.caffemodel --scale_values [59,59,59] --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --scale_values [59,59,59]
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with multiple inputs with scale values:
```sh
mo --input_model bvlc_alexnet.caffemodel --input data,rois --scale_values [59,59,59],[5,5,5] --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --input data,rois --scale_values [59,59,59],[5,5,5]
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with multiple inputs with scale and mean values specified for the particular nodes:
```sh
mo --input_model bvlc_alexnet.caffemodel --input data,rois --mean_values data[59,59,59] --scale_values rois[5,5,5] --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --input data,rois --mean_values data[59,59,59] --scale_values rois[5,5,5]
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with specified input layer, overridden input shape, scale 5, batch 8 and specified name of an output operation:
```sh
mo --input_model bvlc_alexnet.caffemodel --input "data[1 3 224 224]" --output pool5 -s 5 -b 8 --output_dir <OUTPUT_MODEL_DIR>
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with disabled fusing for linear operations to Convolution and grouped convolutions:
```sh
mo --input_model bvlc_alexnet.caffemodel --disable_fusing --disable_gfusing --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --input data --output pool5 -s 5 -b 8
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with reversed input channels order between RGB and BGR, specified mean values to be used for the input image per channel and specified data type for input tensor values:
```sh
mo --input_model bvlc_alexnet.caffemodel --reverse_input_channels --mean_values [255,255,255] --data_type FP16 --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --reverse_input_channels --mean_values [255,255,255] --data_type FP16
```
Launch the Model Optimizer for the Caffe bvlc_alexnet model with extensions listed in specified directories, specified mean_images binaryproto
file. For more information about extensions, please refer to the [OpenVINO™ Extensibility Mechanism](../../../Extensibility_UG/Intro.md).
```sh
mo --input_model bvlc_alexnet.caffemodel --extensions /home/,/some/other/path/ --mean_file /path/to/binaryproto --output_dir <OUTPUT_MODEL_DIR>
mo --input_model bvlc_alexnet.caffemodel --extensions /home/,/some/other/path/ --mean_file /path/to/binaryproto
```
Launch the Model Optimizer for TensorFlow* FaceNet* model with a placeholder freezing value.
It replaces the placeholder with a constant layer that contains the passed value.
For more information about FaceNet conversion, please refer to [this](tf_specific/Convert_FaceNet_From_Tensorflow.md) page.
```sh
mo --input_model FaceNet.pb --input "phase_train->False" --output_dir <OUTPUT_MODEL_DIR>
mo --input_model FaceNet.pb --input "phase_train->False"
```
Launch the Model Optimizer for any model with a placeholder freezing tensor of values.
It replaces the placeholder with a constant layer that contains the passed values.
@@ -287,7 +285,7 @@ Tensor here is represented in square brackets with each value separated from ano
If data type is set in the model, this tensor will be reshaped to a placeholder shape and casted to placeholder data type.
Otherwise, it will be casted to data type passed to `--data_type` parameter (by default, it is FP32).
```sh
mo --input_model FaceNet.pb --input "placeholder_layer_name->[0.1 1.2 2.3]" --output_dir <OUTPUT_MODEL_DIR>
mo --input_model FaceNet.pb --input "placeholder_layer_name->[0.1 1.2 2.3]"
```