* Generate TensorIterator without back edges from TensorFlow models * Added a check in the MarkSubgraphsWithCorrectLayout to not fail when port is not connected * Updated the 'protobuf2nx' to consume the graph protobuf message * Cleanup TI from the IRv7 specific code * Do not run some front transformations recursively * Draft support for the ONNX Loop operation when 'cond' = True * LoopToTI transformation changes * Added draft of Loop operation and parser for ONNX Loop operation body * Updated Loop body parser + added shape and type infer for the Loop operation * Fixes for ONNX Loop operation parser * Moved Loop parsing to Loop op extractor. Added generation of external edges for the Loop body ops * Added support for ThresholdedRelu using decomposition * Added support for Min ONNX operation * Draft fixes for port_map generation for the Loop * Rename transformation file and fix BOM * Fixed shape inference for Loop scan outputs (axis is not None) * Fixed shape inference for ONNX Loop operation * Refactor checks in the TensorIteratorMerge transformation * Code refactoring. Enabled commented transformations * Documentation update for ONNX Loop, ThresholdedRelu and Min * Fixed typo in the Loop front transformation where execution condition input is connected. Other refactorings * Fixed in the Loop extractor * Added printing 'internal_layer_id' attribute in the graph dumper * Updated calculation of iterations number for the Loop * Added missing code * Fixed output port shapes and types generation for Loop operation * Update function names and variable names in the Loop operation * Fixed type inference for iteration count input * Added removal of input/output ports of the Loop if they are not used * Fixed renumbering Loop operations input/output ports to keep mandatory * Fixed ThresholdedReluDecomposition transformation * Updated MO IR Reader to know about Loop operation. But it is still not supported by the MO IR Reader * Added unit test for Slice op shape infer (reverse the sequence of elements) * Reverted changes in the ONNX loader function call to protobuf2nx * Enable Reshape0DToSqueeze transformation recursively * Refactored Loop operation support implementation * Changed ThresholdedReluDecomposition to generate Const with shape [1] instead of scalar * Code style and wording fixes * Restored accidentally removed 'return' statement in the TI shape infer function * Fixed comments * Fixed comment Co-authored-by: Evgeny Lazarev <elazarev.nnov@gmail.com>
27 lines
949 B
Python
27 lines
949 B
Python
"""
|
|
Copyright (C) 2018-2020 Intel Corporation
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software
|
|
distributed under the License is distributed on an "AS IS" BASIS,
|
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
See the License for the specific language governing permissions and
|
|
limitations under the License.
|
|
"""
|
|
from mo.front.common.replacement import FrontReplacementPattern
|
|
from mo.graph.graph import Graph
|
|
from mo.middle.passes.infer import override_batch
|
|
|
|
|
|
class OverrideBatch(FrontReplacementPattern):
|
|
enabled = True
|
|
run_not_recursively = True
|
|
|
|
def find_and_replace_pattern(self, graph: Graph):
|
|
override_batch(graph, graph.graph['cmd_params'].batch)
|