[OVC] Fix output parsing (#19425)
* fix parsing output * use always coma backspace to separate outputs ', ' * update docstring * call parser only for ovc cli tool * docstring correction * separate docs for cli tool and convert_model; other minor changes * drop redundant arg from cli_parser_test.py * more solid test cases added * remove redundant argv.framework from cli_parser_test.py * shape correction in concat * Apply suggestions from code review fix: coma -> comma Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com> * apply review suggestions * remove extra ')' --------- Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>
This commit is contained in:
Pavel Esir
GitHub
parent
2cf8f2bc1f
commit
b8226db465
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@ -1,13 +1,14 @@
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# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import openvino.runtime as ov
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import os
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import pytest
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import tempfile
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import unittest
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from openvino.runtime import Model, Layout, PartialShape, Shape, layout_helpers, Type, Dimension
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import numpy as np
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import openvino.runtime as ov
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import pytest
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from openvino.runtime import PartialShape, Type, Dimension
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from common.mo_convert_test_class import CommonMOConvertTest
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from common.tf_layer_test_class import save_to_pb
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@ -158,6 +159,124 @@ class TestComplexParams(CommonMOConvertTest):
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ref_params.update({'input_model': tf_net_path})
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self._test(temp_dir, test_params, ref_params)
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@staticmethod
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def create_onnx_model_with_comma_in_names(temp_dir):
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import onnx
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from onnx import helper
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from onnx import TensorProto
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input_1 = helper.make_tensor_value_info('input_1', TensorProto.FLOAT, [1, 3, 2, 2])
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input_2 = helper.make_tensor_value_info('input_2', TensorProto.FLOAT, [1, 3, 2, 2])
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output = helper.make_tensor_value_info('relu_1,relu_2', TensorProto.FLOAT, [1, 3, 4, 2])
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node_def_1 = onnx.helper.make_node(
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'Relu',
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inputs=['input_1'],
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outputs=['Relu_1_data'],
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name='relu_1'
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)
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node_def_2 = onnx.helper.make_node(
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'Relu',
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inputs=['input_2'],
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outputs=['Relu_2_data'],
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name='relu_2'
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)
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node_def_3 = onnx.helper.make_node(
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'Concat',
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inputs=['Relu_1_data', 'Relu_2_data'],
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outputs=['relu_1,relu_2'],
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axis=3,
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)
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graph_def = helper.make_graph(
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[node_def_1, node_def_2, node_def_3],
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'test_model',
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[input_1, input_2],
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[output],
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)
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onnx_net = helper.make_model(graph_def, producer_name='test_model')
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model_path = temp_dir + '/test_model.onnx'
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onnx.save(onnx_net, model_path)
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return model_path
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@staticmethod
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def create_ref_graph_with_comma_in_names():
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from openvino.runtime.opset12 import relu, concat
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from openvino.runtime.op import Parameter
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import openvino as ov
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parameter1 = Parameter(ov.Type.f32, ov.Shape([1, 3, 2, 2]))
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parameter2 = Parameter(ov.Type.f32, ov.Shape([1, 3, 2, 2]))
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relu_1 = relu(parameter1)
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relu_2 = relu(parameter2)
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output = concat([relu_1, relu_2], 3)
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return ov.Model([output], [parameter1, parameter2])
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@staticmethod
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def create_onnx_model_with_several_outputs(temp_dir):
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import onnx
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from onnx import helper
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from onnx import TensorProto
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shape = [1, 3, 2, 2]
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input_1 = helper.make_tensor_value_info('input_1', TensorProto.FLOAT, shape)
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input_2 = helper.make_tensor_value_info('input_2', TensorProto.FLOAT, shape)
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concat_output = helper.make_tensor_value_info('concat', TensorProto.FLOAT, shape)
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relu_output = helper.make_tensor_value_info('Relu_1_data', TensorProto.FLOAT, shape)
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node_def_1 = onnx.helper.make_node(
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'Relu',
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inputs=['input_1'],
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outputs=['Relu_1_data'],
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name='relu_1'
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)
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node_def_2 = onnx.helper.make_node(
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'Relu',
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inputs=['input_2'],
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outputs=['Relu_2_data'],
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name='relu_2'
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)
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node_def_3 = onnx.helper.make_node(
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'Concat',
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inputs=['Relu_1_data', 'Relu_2_data'],
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outputs=['concat'],
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axis=3,
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)
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graph_def = helper.make_graph(
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[node_def_1, node_def_2, node_def_3],
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'test_model',
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[input_1, input_2],
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[relu_output, concat_output],
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)
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onnx_net = helper.make_model(graph_def, producer_name='test_model')
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model_path = temp_dir + '/test_model.onnx'
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onnx.save(onnx_net, model_path)
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return model_path
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_ovc_convert_model_with_comma_in_names(self, ie_device, precision, ir_version,
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temp_dir, use_new_frontend, use_old_api):
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onnx_net_path = self.create_onnx_model_with_comma_in_names(temp_dir)
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ref_model = self.create_ref_graph_with_comma_in_names()
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test_params = {'input_model': onnx_net_path, 'output': 'relu_1,relu_2'}
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self._test_by_ref_graph(temp_dir, test_params, ref_model, compare_tensor_names=False)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_ovc_convert_model_with_several_output(self, ie_device, precision, ir_version,
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temp_dir, use_new_frontend, use_old_api):
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onnx_net_path = self.create_onnx_model_with_several_outputs(temp_dir)
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convert_model_params = {'input_model': onnx_net_path, 'output': ['Relu_1_data', 'concat']}
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cli_tool_params = {'input_model': onnx_net_path, 'output': 'Relu_1_data,concat'}
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self._test(temp_dir, convert_model_params, cli_tool_params)
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class NegativeCases(unittest.TestCase):
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test_directory = os.path.dirname(os.path.realpath(__file__))
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@ -68,11 +68,12 @@ def convert_model(
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If data type is not specified explicitly data type is taken from the original node data type.
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:param output:
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The name of the output operation of the model or list of names. For TensorFlow*,
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do not add :0 to this name. The order of outputs in converted model is the
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same as order of specified operation names. For PaddlePaddle model represented
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as a Python object, you can specify outputs as a PaddlePaddle Python objects or
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a list of such objects.
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One or more comma-separated model outputs to be preserved in the converted model. Other outputs are removed.
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If `output` parameter is not specified then all outputs from the original model are preserved.
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Do not add :0 to the names for TensorFlow. The order of outputs in the converted model is the same as
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the order of specified names. Example: output="out_1", or output=["out_1", "out_2"].
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For PaddlePaddle model represented as a Python object, you can specify outputs as a PaddlePaddle Python
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objects or a list of such objects.
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:param example_input:
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Sample of model input in original framework.
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For PyTorch it can be torch.Tensor.
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@ -5,11 +5,11 @@ import argparse
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import datetime
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import logging as log
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import os
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import pathlib
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import sys
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import traceback
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from collections import OrderedDict
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from pathlib import Path
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from typing import Iterable, Callable
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try:
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import openvino_telemetry as tm
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@ -39,6 +39,7 @@ from openvino.tools.ovc.moc_frontend.paddle_frontend_utils import paddle_fronten
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from openvino.frontend import FrontEndManager, OpConversionFailure, TelemetryExtension
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from openvino.runtime import get_version as get_rt_version
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from openvino.runtime import Type, PartialShape
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import re
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try:
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from openvino.frontend.tensorflow.utils import create_tf_graph_iterator, type_supported_by_tf_fe, \
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@ -76,20 +77,43 @@ def print_argv(argv: argparse.Namespace):
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print('\n'.join(lines), flush=True)
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def check_iterable(iterable: Iterable, func: Callable):
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for element in iterable:
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if not func(element):
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return False
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return True
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def arguments_post_parsing(argv: argparse.Namespace):
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# TODO: This function looks similar to another one. Check for code duplicates.
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log.debug("Model Conversion API started")
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if not argv.is_python_api_used:
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log.debug('Output model name would be {}{{.xml, .bin}}'.format(argv.output_model))
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if argv.verbose:
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if is_verbose(argv):
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print_argv(argv)
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params_parsing(argv)
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argv.output = argv.output.split(',') if isinstance(argv.output, (str, pathlib.Path)) else argv.output
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log.debug("Placeholder shapes : {}".format(argv.placeholder_shapes))
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if not hasattr(argv, 'output') or argv.output is None:
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return argv
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if argv.is_python_api_used:
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error_msg = f"output '{argv.output}' is incorrect, it should be string or a list/tuple of strings"
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assert isinstance(argv.output, (str, list, tuple)), error_msg
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if isinstance(argv.output, list):
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assert check_iterable(argv.output, lambda x: isinstance(x, str)), error_msg
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else:
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argv.output = [argv.output]
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else:
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assert isinstance(argv.output, str)
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error_msg = f"output '{argv.output}' is incorrect, output names should not be empty or contain spaces"
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processed_output = re.split(r'\s*,\s*', argv.output.strip())
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assert check_iterable(processed_output, lambda x: x.find(' ') == -1), error_msg
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assert check_iterable(processed_output, lambda x: len(x) > 0), error_msg
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argv.output = processed_output
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return argv
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@ -342,7 +366,7 @@ def params_parsing(argv: argparse.Namespace):
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data_type_list.append(inp.type)
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argv.placeholder_shapes = shape_list if shape_list else None
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argv.placeholder_data_types = data_type_list if data_type_list else {}
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if argv.framework == "pytorch" and getattr(argv, "example_input", None) is not None:
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if hasattr(argv, "framework") and argv.framework == "pytorch" and getattr(argv, "example_input", None) is not None:
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extract_input_info_from_example(argv, inputs)
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@ -26,6 +26,14 @@ def get_convert_model_help_specifics():
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'If the dimension is set as an integer (like 100 in [1,100]), such a dimension is not supposed '
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'to be changed later, during a model conversion it is treated as a static value. '
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'Example with unnamed inputs: \"[1,100],[1,?]\".'},
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'output':
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{'description':
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'One or more comma-separated model outputs to be preserved in the converted model. '
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'Other outputs are removed. If `output` parameter is not specified then all outputs from '
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'the original model are preserved. '
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'Do not add :0 to the names for TensorFlow. The order of outputs in the converted model is the '
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'same as the order of specified names. '
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'Example: ovc model.onnx output=out_1,out_2'},
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'extension':
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{'description':
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'Paths or a comma-separated list of paths to libraries '
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@ -14,7 +14,7 @@ import numpy as np
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from openvino.tools.ovc.cli_parser import input_to_input_cut_info, check_positive, writable_dir, \
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readable_file_or_object, get_all_cli_parser, get_mo_convert_params
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from openvino.tools.ovc.convert_impl import pack_params_to_args_namespace
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from openvino.tools.ovc.convert_impl import pack_params_to_args_namespace, arguments_post_parsing, args_to_argv
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from openvino.tools.ovc.error import Error
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from unit_tests.ovc.unit_test_with_mocked_telemetry import UnitTestWithMockedTelemetry
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from openvino.runtime import PartialShape, Dimension, Layout
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@ -366,7 +366,7 @@ class TestPackParamsToArgsNamespace(unittest.TestCase):
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from openvino.frontend import ConversionExtension
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args = {'input_model': os.path.dirname(__file__),
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'extension': ConversionExtension("Ext", lambda x: x),
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'input': ['name', ("a", [1,2,3], ov.Type.f32)],
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'input': ['name', ("a", [1, 2, 3], ov.Type.f32)],
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'output': ["a", "b", "c"]}
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cli_parser = get_all_cli_parser()
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@ -375,12 +375,120 @@ class TestPackParamsToArgsNamespace(unittest.TestCase):
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assert argv.input_model == args['input_model']
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assert argv.extension == args['extension']
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assert argv.input == ['name', ("a", [1,2,3], ov.Type.f32)]
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assert argv.output == ["a","b","c"]
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assert argv.output == ["a", "b", "c"]
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for arg, value in vars(argv).items():
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if arg not in args and arg != 'is_python_api_used':
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assert value == cli_parser.get_default(arg)
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def test_output_post_parsing_1(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "a,b,c"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = False
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argv = arguments_post_parsing(argv)
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assert argv.output == ["a", "b", "c"]
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def test_output_post_parsing_2(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "a, b, c"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = False
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argv = arguments_post_parsing(argv)
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assert argv.output == ["a", "b", "c"]
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def test_output_post_parsing_3(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "a,b, c"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = False
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argv = arguments_post_parsing(argv)
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assert argv.output == ["a", "b", "c"]
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def test_output_post_parsing_4(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "a , b , c"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = False
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argv = arguments_post_parsing(argv)
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assert argv.output == ["a", "b", "c"]
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def test_output_post_parsing_5(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "a,b"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = True
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argv = arguments_post_parsing(argv)
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assert argv.output == ["a,b"] # post parsing should decorate single string into a list
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def test_output_post_parsing_6(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': ["first na me", "second name"]}
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argv = args_to_argv(**args)
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argv.is_python_api_used = True
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argv = arguments_post_parsing(argv)
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# when used in python api should be able to handle names with spaces
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assert argv.output == ["first na me", "second name"]
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def test_raises_output_post_parsing_1(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': ["a,b, c", 23]}
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argv = args_to_argv(**args)
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argv.is_python_api_used = True
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self.assertRaises(AssertionError, arguments_post_parsing, argv)
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def test_raises_output_post_parsing_2(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "na me, full_name"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = False
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with self.assertRaisesRegex(AssertionError, ".*output names should not be empty or contain spaces"):
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arguments_post_parsing(argv)
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def test_raises_output_post_parsing_3(self):
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args = {'input_model': os.path.dirname(__file__),
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'input': "input_1[1,2,3]",
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'output_model': os.getcwd() + "model.xml",
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'output': "a,,b,c"}
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argv = args_to_argv(**args)
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argv.is_python_api_used = False
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with self.assertRaisesRegex(AssertionError, ".*output names should not be empty or contain spaces"):
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arguments_post_parsing(argv)
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def test_not_existing_dir(self):
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args = {"input_model": "abc"}
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cli_parser = get_all_cli_parser()
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