* Removed a redundant image * Fixed ops specifications and other issues * converted html links to anchor links * converted html links to anchor links * Fixed a link * Fixed a link * Changed anchor links according to dev review # Conflicts: # docs/OV_Runtime_UG/Operations_specifications.md
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Andrey Zaytsev
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@@ -10,7 +10,7 @@
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OpenVINO™ provides capabilities to change model input shape during the runtime.
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It may be useful in case you would like to feed model an input that has different size than model input shape.
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In case you need to do this only once <a href="_docs_MO_DG_prepare_model_convert_model_Converting_Model.html#when-to-specify-input-shapes">prepare a model with updated shapes via Model Optimizer</a> for all the other cases follow instructions further.
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In case you need to do this only once [prepare a model with updated shapes via Model Optimizer](@ref when_to_specify_input_shapes) for all the other cases follow instructions further.
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### Set a new input shape with reshape method
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@@ -26,7 +26,7 @@ Please see the code to achieve that:
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### Set a new batch size with set_batch method
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Meaning of the model batch may vary depending on the model design.
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In order to change the batch dimension of the model, please <a href="_docs_OV_Runtime_UG_preprocessing_overview.html#declare-model-s-layout">set the ov::Layout</a> and call the `ov::set_batch` method.
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In order to change the batch dimension of the model, [set the ov::Layout](@ref declare_model_s_layout) and call the `ov::set_batch` method.
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@snippet snippets/ShapeInference.cpp set_batch
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@@ -34,7 +34,7 @@ In order to change the batch dimension of the model, please <a href="_docs_OV_Ru
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Once the input shape of `ov::Model` is set, call the `ov::Core::compile_model` method to get an `ov::CompiledModel` object for inference with updated shapes.
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There are other approaches to change model input shapes during the stage of <a href="_docs_MO_DG_prepare_model_convert_model_Converting_Model.html#when-to-specify-input-shapes">IR generation</a> or [ov::Model creation](../OV_Runtime_UG/model_representation.md).
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There are other approaches to change model input shapes during the stage of [IR generation](@ref when_to_specify_input_shapes) or [ov::Model creation](../OV_Runtime_UG/model_representation.md).
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### Dynamic Shape Notice
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@@ -80,10 +80,11 @@ To do the opposite - resize input image to the input shapes of the model, use th
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@endsphinxdirective
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Please find usage scenarios of `reshape` feature in our [samples](Samples_Overview.md) starting with [Hello Reshape Sample](../../samples/cpp/hello_reshape_ssd/README.html)
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Please find usage scenarios of `reshape` feature in our [samples](Samples_Overview.md) starting with [Hello Reshape Sample](../../samples/cpp/hello_reshape_ssd/README.md).
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Practically, some models are not ready to be reshaped. In this case, a new input shape cannot be set with the Model Optimizer or the `ov::Model::reshape` method.
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@anchor troubleshooting_reshape_errors
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### Troubleshooting Reshape Errors
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Operation semantics may impose restrictions on input shapes of the operation.
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@@ -105,9 +106,10 @@ For example, [publicly available Inception family models from TensorFlow*](https
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- Changing the model input shape may significantly affect its accuracy.
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For example, Object Detection models from TensorFlow have resizing restrictions by design.
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To keep the model valid after the reshape, choose a new input shape that satisfies conditions listed in the `pipeline.config` file.
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For details, refer to the <a href="_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_Object_Detection_API_Models.html#custom-input-shape">Tensorflow Object Detection API models resizing techniques</a>.
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For details, refer to the [Tensorflow Object Detection API models resizing techniques](@ref custom-input-shape).
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### How To Fix Non-Reshape-able Model<a name="how-to-fix-non-reshape-able-model"></a>
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@anchor how-to-fix-non-reshape-able-model
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### How To Fix Non-Reshape-able Model
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Some operators which prevent normal shape propagation can be fixed. To do so you can:
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* see if the issue can be fixed via changing the values of some operators input.
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@@ -140,7 +142,7 @@ OpenVINO provides a special mechanism that allows adding support of shape infere
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OpenVINO™ provides capabilities to change model input shape during the runtime.
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It may be useful in case you would like to feed model an input that has different size than model input shape.
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In case you need to do this only once <a href="_docs_MO_DG_prepare_model_convert_model_Converting_Model.html#when-to-specify-input-shapes">prepare a model with updated shapes via Model Optimizer</a> for all the other cases follow instructions further.
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In case you need to do this only once [prepare a model with updated shapes via Model Optimizer](@ref when_to_specify_input_shapes) for all the other cases follow instructions further.
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### Set a new input shape with reshape method
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@@ -162,7 +164,7 @@ Please see the code to achieve that:
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### Set a new batch size with set_batch method
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Meaning of the model batch may vary depending on the model design.
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In order to change the batch dimension of the model, please <a href="_docs_OV_Runtime_UG_preprocessing_overview.html#declare-model-s-layout">set the Layout</a> for inputs and call the [set_batch](api/ie_python_api/_autosummary/openvino.runtime.set_batch.html) method.
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In order to change the batch dimension of the model, [set the layout](@ref declare_model_s_layout) for inputs and call the [set_batch](api/ie_python_api/_autosummary/openvino.runtime.set_batch.html) method.
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@sphinxdirective
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@@ -176,7 +178,7 @@ In order to change the batch dimension of the model, please <a href="_docs_OV_Ru
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Once the input shape of [Model](api/ie_python_api/_autosummary/openvino.runtime.Model.html) is set, call the [compile_model](api/ie_python_api/_autosummary/openvino.runtime.compile_model.html) method to get a [CompiledModel](api/ie_python_api/_autosummary/openvino.runtime.CompiledModel.html) object for inference with updated shapes.
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There are other approaches to change model input shapes during the stage of <a href="_docs_MO_DG_prepare_model_convert_model_Converting_Model.html#when-to-specify-input-shapes">IR generation</a> or [Model creation](../OV_Runtime_UG/model_representation.md).
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There are other approaches to change model input shapes during the stage of [IR generation](@ref when_to_specify_input_shapes) or [Model creation](../OV_Runtime_UG/model_representation.md).
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### Dynamic Shape Notice
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@@ -234,19 +236,19 @@ Dictionary values (representing new shapes) could be
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@endsphinxdirective
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Please find usage scenarios of `reshape` feature in our [samples](Samples_Overview.md), starting with [Hello Reshape Sample](../../samples/python/hello_reshape_ssd/README.html)
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Please find usage scenarios of `reshape` feature in our [samples](Samples_Overview.md), starting with [Hello Reshape Sample](../../samples/python/hello_reshape_ssd/README.md).
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Practically, some models are not ready to be reshaped. In this case, a new input shape cannot be set with the Model Optimizer or the `Model.reshape` method.
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### Troubleshooting Reshape Errors <a name="troubleshooting"></a>
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### Troubleshooting Reshape Errors
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Operation semantics may impose restrictions on input shapes of the operation.
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Shape collision during shape propagation may be a sign that a new shape does not satisfy the restrictions.
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Changing the model input shape may result in intermediate operations shape collision.
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Examples of such operations:
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* <a href="_docs_ops_shape_Reshape_1.html">Reshape</a> operation with a hard-coded output shape value
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* <a href="_docs_ops_matrix_MatMul_1.html">MatMul</a> operation with the `Const` second input cannot be resized by spatial dimensions due to operation semantics
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* [Reshape](../ops/shape/Reshape_1.md) operation with a hard-coded output shape value
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* [MatMul](../ops/matrix/MatMul_1.md) operation with the `Const` second input cannot be resized by spatial dimensions due to operation semantics
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Model structure and logic should not change significantly after model reshaping.
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- The Global Pooling operation is commonly used to reduce output feature map of classification models output.
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@@ -259,9 +261,9 @@ For example, [publicly available Inception family models from TensorFlow*](https
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- Changing the model input shape may significantly affect its accuracy.
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For example, Object Detection models from TensorFlow have resizing restrictions by design.
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To keep the model valid after the reshape, choose a new input shape that satisfies conditions listed in the `pipeline.config` file.
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For details, refer to the <a href="_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_Object_Detection_API_Models.html#custom-input-shape">Tensorflow Object Detection API models resizing techniques</a>.
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For details, refer to the [Tensorflow Object Detection API models resizing techniques](@ref custom-input-shape).
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### How To Fix Non-Reshape-able Model<a name="how-to-fix-non-reshape-able-model"></a>
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### How To Fix Non-Reshape-able Model
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Some operators which prevent normal shape propagation can be fixed. To do so you can:
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* see if the issue can be fixed via changing the values of some operators input.
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