3775dad345
* Allow MO to generate IR with -1 in dimensions * Some fixes to support -1 for StridedSlice operation * Updated TensorArrayGatherV3 shape infer to support dynamic output shape * Several fixes to support undefined dimensions in the Broadcast,Reshape,Slice and Tile * Fixed bug in the normalization transformation of TF NMS to opset NMS * Updated shape infer functions related to StridedSlice and NMS * Updated Select shape inference function to use common shape broadcasting function supporting dynamism * Fixed operation TFResize shape infer function to work correctly for case when model is converted with --disable_nhwc_to_nchw * Dynamic Range and update asserts in NMS * Changed the way how dynamic dimensions are specified. Refactored shape inference functions and common places to use new approach * More fixes to support dynamic shapes * More fixes for support of dynamic shapes * Fixed generation of IR with dynamic dimensions * Allow reading IRs with undefined dimensions * More changes in the IE to support dynamic dimensions * Fixes for Switch, Merge, Concat shape and value infer related to dynamism * Fixed TensorArray related ops to properly handle dynamic dimensions. Fixed StridedSlice infer for case with new_axis * Fixed shape_for_layout function to generate masked array * Fixed shape inference for Convolution and Poolings to support dynamic spatial dimensions * Updated shape infer functions for CTCGreedyDecotder, CTCLoss and Enter * Fixed shape inference with dynamic dimensions for MatMul, Split, Upsample, SpaceToBatch, some fixes for the TI * Fixes for undefined dimensions support for Proposal and DetectionOutput * Fixed ExtractImagePatches, DepthToSpace and RegionYolo shape infer functions to work with partially dynamic dimensions * Changes in tf_window_op_pad_infer to better work with dynamic dimensions * Fixed output shape calculation for StridedSlice operation * More StridedSlice fixes * Fixed resolve_convolution_with_group * Fixed unit tests * Fixed unit tests * Fixed Switch op unit tests * Fixed shape inference for Upsample operation * Updated unit tests for the Concat operation * Fixed eltwise shape infer unit tests * Fixed shape infer tests for Convolution and DetectionOutput ops * Fixed Crop shape infer function tests * Fixed Slice op unit test and minor fix in the shape inference. Fixed emitter * Updated unit test for telemetry and match_shape function for dynamism * Fixed unit test for the DetectionOutput * Added support for the TF ClipByValue operation * Fixed GatherND shape inference for dynamic shapes support * Dynamic shapes support for the MO IR Reader * Fixed BlockLSTM operation to not work as an extractor * Allow to serialize IRs with partially defined shapes * Updated SelectBroadcast transformation to not check shape values * Fixed MO IR comparator * Fixed SS value propagation when slices are dynamic * Do not re-run graph clean-up for ProposalMutation * Fixed InterpolateSequenceToInterpolate transformation to support dynamic dimensions * Fixed Loop iteration count calculation and reading IteratorGetNext shapes * Fixed unit test for serialization * Fixed serialization test * Fixed RandomUniform shape infer * Fixed several transformations related to RNN to respect dynamic output shapes * Fixed Deconvolutin shape calculation for dynamic batch. Eltwise shape infer improvements * Fixed shape infer functions for ExperimentalDetectron ops, reverted changes for NonZero and removed debug prints * Fixed check for dynamism of a list, fixed value propagation for Concat op and remove redundant shape infer for reshape * Update Eltwise value propagation to use np.ma * Fixed ExpandDims shape infer function * Shape infer functions fixes and improvements * Remove Accum op from the MO * Updated activation functions shape infer * Removed unsupported operation Correlation * Fixed shape infers for several functions * Removed unsupported DataAugmentation operation * Fixed shape infer functions for several ops in extensions directory * Removed not-support operation PowerFile * Removed unsupported SpatialTransformer,SimplerNMS and PredictionHeatmap operations * More shape infer functions updates * Merge shape infer fix * Fixed typo * Fixed TensorArraySize shape infer function * Fixed VariadicSplit and Squeeze shape infer * Fixed ONNX models Parameter extractor * Updated Select value propagation for the dynamic case * Fixed ReorgYolo shape infer and test * Removed unnecessary tests * Fixed Tile shape infer * Fixed SparseFillEmptryRows unit tests * Fixed package bom * Added extractor for the TF operation Mod * Fixed value propagation for MatMul operation * Updated Parameter extender to generate shape_array when shape is partially defined only * Fixed BOM file * Fixed issue with the TF OD API models and DetectionOutput op. Now the shape infer function for the DO do not re-infer "num_classes" attribute value if it is already known * Fixed unit test for the DO infer * Fixed num classes calculation for the DO generation for Faster/Mask-RCNN models * Changed NMS op to produce static output shape * Restore dynamic output shape calculation for the NMS for NMS-5 * Fixed CellNormalizer transformation. It should work for static shapes only * RNNCell Op class fixes * Revert some changes * Updated documentation with a list of supported operations * Revert changes * Fixes for the ConstantFill op * Removed redundant SequenceLengthToMask transformation * TensorArray* ops shape infer code style and refactoring * Reverse some unnecessary changes in the ConvolutionNormalizer * Fixes and unit tests for shape_array, compare_shapes, is_fully_defined functions * Implemented shape_insert, shape_delete functions and tests for them * Modified code to use shape_delete function * Added usage of shape_insert function where necessary * Use shape_insert function in many places * Some fixes in shape inference for various ops * Updated shape_delete function to support negative indices * Changes and unit tests for the MatMul infer function * Removed strange code from the TF Merge infer function * Merge op shape infer fixes * Fixed value propagation in the transformation EltwiseInputReshape.py for the dynamic dimension case * Code cleanup * Updated GatherND to support dynamic dimensions * Minor fixes * Fixed shape_insert and shape_delete to support np.int64 and np.int32 types * Updated Upsample operation unit tests with dynamic input shapes * Minor change in the extensions/back/ConvolutionNormalizer.py to make sure that input dimensions are static * Fixed ConvertGroupedStridedSlice transformation and added unit tests * Revert debug changes * Fixed value propagation for Unsqueeze to work with partially defined input values * Typo fix * Added unit tests for the Unsqueeze op shape infer * broadcasting functions changes and unit tests * Fixed Tile value inference for partially defined input tensor * Unit tests for Split and VariadicSplit ops * Fixes for the Concat infer + unit tests * Removed redundant tf_pack shape infer * Fixed Concat value infer and added unit tests * Fixed StridedSlice shape inference for case with dynamic slices * Fixes related to StridedSlice shape infer, changes in tests * Unit tests for the eltwise shape and value infer * Fixed Pad op value propagation to allow dynamic input values to be propagated * Unit test for Pooling dynamic input shape infer * Squeeze op unit tests for dynamic input shape * Added assert to the Squeeze op shape infer for case when squeeze dimension is dynamic value * Added message to the MO when input shapes are dynamic * Convolution dynamic unit test * Removed redundant transformation GroupedConvWeightsNormalize * Removed non-ascii character from the message * Fixed typo in the BOM file * Code style and comment fixes * Fixed copy-paste issue in the DO shape infer function * Fixed setting dynamic shape in the MO command line * Added function to compare tensor with dynamic values. Fixes in the unit tests and shape infer functions * Improved Reshape shape infer + added unit tests * Fixed value propagation for Select op * Renamed several internal functions, minor code fixes. * Code style fixes * Modified condition in the _set_shape method of the Port class to not check shape if the "override_output_shape" attribute is specified * Fixed constant value propagation for ReduceOps when inputs have dynamic values. Added unit test * Fixed shape infer for the Loop for dynamic dimensions case * Fix in the NMS shape infer to avoid ragged numpy array generation. Fixed Scatter shape infer validation * Improved shapes infer for eltwise ops with respect to dynamic dimensions * Changed code comments * Renamed tensor names in the ClipByValueTFTransformation * Changed np.ma.allequal to strict_compare_tensors in the Merge op infer * Chanded np.ma.allequal with strict_compare_tensor. * Fixed Merge op value infer * Fixed debug code * Removed commented line * Updated condition to check for dynamic shapes in the Partial infer to not fail for MxNet models * Improvements to the get_shape_from_slice and is_dynamic_slice functions * Reverted change in the `normalize_slices_attr` for ellipsis mask case * Updated shape conditions in the ScatterNDBase op to support dynamic dimensions * Crop op file refactoring * Set "type" attribute to None for SparseFillEmptyRows op which is not from any opset * Removed unnecessary extractor test * Restored Crop operation type * Removed "type" attribute from the Crop operation and updated the MO code to find Crop by "op" attribute * Fixed If shape infer function to produce dynamic dimensions * Updated If shape and value infer to properly work when condition is static * Fixed fusing transformation check to work with dynamic dimensions. Change comparison in the shape_inference function to not use strict shapes comparison * Optimize imports in the LayerNorm * ConvertGroupedStridedSlice minor fixes related to dynamism support * Fixed ConvertGroupedStridedSlice to properly check if the dimension is sliced
36 lines
1016 B
Python
36 lines
1016 B
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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from mo.front.common.partial_infer.utils import shape_array
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from mo.graph.graph import Node, Graph
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from mo.ops.op import Op
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class TensorArraySize(Op):
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op = "TensorArraySizeV3"
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def __init__(self, graph: Graph, attrs: dict):
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mandatory_props = {
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'type': None,
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'op': self.op,
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'infer': TensorArraySize.array_infer,
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}
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super().__init__(graph, mandatory_props, attrs)
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@staticmethod
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def array_infer(node: Node):
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assert len(node.in_nodes()) == 2
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handle = node.in_node(0)
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ta_node = Node(node.graph, str(handle.value))
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assert ta_node.has_valid('size')
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output_value = np.array(ta_node['size'])
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for _, out_node in node.graph.out_edges(node.id):
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node.graph.node[out_node]['shape'] = shape_array(output_value.shape)
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node.graph.node[out_node]['value'] = output_value.copy()
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