diff options
Diffstat (limited to 'python/pyarmnn')
-rw-r--r-- | python/pyarmnn/examples/image_classification/example_utils.py | 2 | ||||
-rwxr-xr-x | python/pyarmnn/setup.py | 1 | ||||
-rw-r--r-- | python/pyarmnn/src/pyarmnn/__init__.py | 13 | ||||
-rw-r--r-- | python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i | 102 | ||||
-rwxr-xr-x | python/pyarmnn/swig_generate.py | 1 | ||||
-rw-r--r-- | python/pyarmnn/test/test_generated.py | 4 | ||||
-rw-r--r-- | python/pyarmnn/test/test_tf_parser.py | 133 |
7 files changed, 2 insertions, 254 deletions
diff --git a/python/pyarmnn/examples/image_classification/example_utils.py b/python/pyarmnn/examples/image_classification/example_utils.py index bd43d60da5..657f9d3559 100644 --- a/python/pyarmnn/examples/image_classification/example_utils.py +++ b/python/pyarmnn/examples/image_classification/example_utils.py @@ -72,7 +72,7 @@ def parse_command_line(desc: str = ""): parser.add_argument("-d", "--data-dir", help="Data directory which contains all the images.", action="store", default="") parser.add_argument("-m", "--model-dir", - help="Model directory which contains the model file (TF, TFLite, ONNX).", action="store", + help="Model directory which contains the model file (TFLite, ONNX).", action="store", default="") return parser.parse_args() diff --git a/python/pyarmnn/setup.py b/python/pyarmnn/setup.py index 9d9f561ef9..78868549f3 100755 --- a/python/pyarmnn/setup.py +++ b/python/pyarmnn/setup.py @@ -284,7 +284,6 @@ if __name__ == '__main__': add_parsers_ext('OnnxParser', extensions_to_build) - add_parsers_ext('TfParser', extensions_to_build) add_parsers_ext('TfLiteParser', extensions_to_build) add_parsers_ext('Deserializer', extensions_to_build) diff --git a/python/pyarmnn/src/pyarmnn/__init__.py b/python/pyarmnn/src/pyarmnn/__init__.py index 410e66be11..5cb8bfb6cd 100644 --- a/python/pyarmnn/src/pyarmnn/__init__.py +++ b/python/pyarmnn/src/pyarmnn/__init__.py @@ -22,19 +22,6 @@ except ImportError as err: raise RuntimeError(message) try: - from ._generated.pyarmnn_tfparser import ITfParser -except ImportError as err: - logger = logging.getLogger(__name__) - message = "Your ArmNN library instance does not support TF models parser functionality. " - logger.warning("%s Skipped ITfParser import.", message) - logger.debug(str(err)) - - - def ITfParser(): - """In case people try importing without having Arm NN built with this parser.""" - raise RuntimeError(message) - -try: from ._generated.pyarmnn_tfliteparser import ITfLiteParser, TfLiteParserOptions except ImportError as err: logger = logging.getLogger(__name__) diff --git a/python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i b/python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i deleted file mode 100644 index 03729abbf8..0000000000 --- a/python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i +++ /dev/null @@ -1,102 +0,0 @@ -// -// Copyright © 2020 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// -%module pyarmnn_tfparser -%{ -#define SWIG_FILE_WITH_INIT -#include "armnnTfParser/ITfParser.hpp" -#include "armnn/INetwork.hpp" -%} - -//typemap definitions and other common stuff -%include "standard_header.i" - -namespace std { - %template(BindingPointInfo) pair<int, armnn::TensorInfo>; - %template(MapStringTensorShape) map<std::string, armnn::TensorShape>; - %template(StringVector) vector<string>; -} - -namespace armnnTfParser -{ -%feature("docstring", -" -Interface for creating a parser object using TensorFlow (https://www.tensorflow.org/) frozen pb files. - -Parsers are used to automatically construct Arm NN graphs from model files. - -") ITfParser; -%nodefaultctor ITfParser; -class ITfParser -{ -public: - %feature("docstring", - " - Retrieve binding info (layer id and `TensorInfo`) for the network input identified by the given layer name. - - Args: - name (str): Name of the input. - - Returns: - tuple: (`int`, `TensorInfo`). - ") GetNetworkInputBindingInfo; - std::pair<int, armnn::TensorInfo> GetNetworkInputBindingInfo(const std::string& name); - - %feature("docstring", - " - Retrieve binding info (layer id and `TensorInfo`) for the network output identified by the given layer name. - - Args: - name (str): Name of the output. - - Returns: - tuple: (`int`, `TensorInfo`). - ") GetNetworkOutputBindingInfo; - std::pair<int, armnn::TensorInfo> GetNetworkOutputBindingInfo(const std::string& name); -}; - -%extend ITfParser { - // This is not a substitution of the default constructor of the Armnn class. It tells swig to create custom __init__ - // method for ITfParser python object that will use static factory method to do the job. - - ITfParser() { - return armnnTfParser::ITfParser::CreateRaw(); - } - - // The following does not replace a real destructor of the Armnn class. - // It creates a functions that will be called when swig object goes out of the scope to clean resources. - // so the user doesn't need to call ITfParser::Destroy himself. - // $self` is a pointer to extracted ArmNN ITfParser object. - - ~ITfParser() { - armnnTfParser::ITfParser::Destroy($self); - } - - %feature("docstring", - " - Create the network from a pb Protocol buffer file. - - Args: - graphFile (str): Path to the tf model to be parsed. - inputShapes (dict): A dict containing the input name as a key and `TensorShape` as a value. - requestedOutputs (list of str): A list of the output tensor names. - - Returns: - INetwork: Parsed network. - - Raises: - RuntimeError: If model file was not found. - ") CreateNetworkFromBinaryFile; - %newobject CreateNetworkFromBinaryFile; - armnn::INetwork* CreateNetworkFromBinaryFile(const char* graphFile, - const std::map<std::string, armnn::TensorShape>& inputShapes, - const std::vector<std::string>& requestedOutputs) { - return $self->CreateNetworkFromBinaryFile(graphFile, inputShapes, requestedOutputs).release(); - } - -} - -} -// Clear exception typemap. -%exception; diff --git a/python/pyarmnn/swig_generate.py b/python/pyarmnn/swig_generate.py index a2352c9063..e6e2b346be 100755 --- a/python/pyarmnn/swig_generate.py +++ b/python/pyarmnn/swig_generate.py @@ -108,7 +108,6 @@ if __name__ == "__main__": wrap_names = ['armnn_version', 'armnn', 'armnn_onnxparser', - 'armnn_tfparser', 'armnn_tfliteparser', 'armnn_deserializer'] diff --git a/python/pyarmnn/test/test_generated.py b/python/pyarmnn/test/test_generated.py index f27d565c2b..60d686afcb 100644 --- a/python/pyarmnn/test/test_generated.py +++ b/python/pyarmnn/test/test_generated.py @@ -9,7 +9,6 @@ import pyarmnn._generated.pyarmnn as generated_armnn import pyarmnn._generated.pyarmnn as generated_deserializer import pyarmnn._generated.pyarmnn_onnxparser as generated_onnx import pyarmnn._generated.pyarmnn_tfliteparser as generated_tflite -import pyarmnn._generated.pyarmnn_tfparser as generated_tf swig_independent_classes = ('IBackend', 'IDeviceSpec', @@ -28,8 +27,7 @@ def get_classes(swig_independent_classes: Tuple): inspect.getmembers(generated_armnn, inspect.isclass) + inspect.getmembers(generated_deserializer, inspect.isclass) + inspect.getmembers(generated_tflite, inspect.isclass) + - inspect.getmembers(generated_onnx, inspect.isclass) + - inspect.getmembers(generated_tf, inspect.isclass))) + inspect.getmembers(generated_onnx, inspect.isclass))) @pytest.mark.parametrize("class_instance", get_classes(swig_independent_classes), ids=lambda x: 'class={}'.format(x[0])) diff --git a/python/pyarmnn/test/test_tf_parser.py b/python/pyarmnn/test/test_tf_parser.py deleted file mode 100644 index 796dd71e7b..0000000000 --- a/python/pyarmnn/test/test_tf_parser.py +++ /dev/null @@ -1,133 +0,0 @@ -# Copyright © 2020 Arm Ltd. All rights reserved. -# SPDX-License-Identifier: MIT -import os - -import pytest -import pyarmnn as ann -import numpy as np - - -@pytest.fixture() -def parser(shared_data_folder): - """ - Parse and setup the test network to be used for the tests below - """ - - # create tf parser - parser = ann.ITfParser() - - # path to model - path_to_model = os.path.join(shared_data_folder, 'mock_model.pb') - - # tensor shape [1, 28, 28, 1] - tensorshape = {'input': ann.TensorShape((1, 28, 28, 1))} - - # requested_outputs - requested_outputs = ["output"] - - # parse tf binary & create network - parser.CreateNetworkFromBinaryFile(path_to_model, tensorshape, requested_outputs) - - yield parser - - -def test_tf_parser_swig_destroy(): - assert ann.ITfParser.__swig_destroy__, "There is a swig python destructor defined" - assert ann.ITfParser.__swig_destroy__.__name__ == "delete_ITfParser" - - -def test_check_tf_parser_swig_ownership(parser): - # Check to see that SWIG has ownership for parser. This instructs SWIG to take - # ownership of the return value. This allows the value to be automatically - # garbage-collected when it is no longer in use - assert parser.thisown - - -def test_tf_parser_get_network_input_binding_info(parser): - input_binding_info = parser.GetNetworkInputBindingInfo("input") - - tensor = input_binding_info[1] - assert tensor.GetDataType() == 1 - assert tensor.GetNumDimensions() == 4 - assert tensor.GetNumElements() == 28*28*1 - assert tensor.GetQuantizationOffset() == 0 - assert tensor.GetQuantizationScale() == 0 - - -def test_tf_parser_get_network_output_binding_info(parser): - output_binding_info = parser.GetNetworkOutputBindingInfo("output") - - tensor = output_binding_info[1] - assert tensor.GetDataType() == 1 - assert tensor.GetNumDimensions() == 2 - assert tensor.GetNumElements() == 10 - assert tensor.GetQuantizationOffset() == 0 - assert tensor.GetQuantizationScale() == 0 - - -def test_tf_filenotfound_exception(shared_data_folder): - parser = ann.ITfParser() - - # path to model - path_to_model = os.path.join(shared_data_folder, 'some_unknown_model.pb') - - # tensor shape [1, 1, 1, 1] - tensorshape = {'input': ann.TensorShape((1, 1, 1, 1))} - - # requested_outputs - requested_outputs = [""] - - # parse tf binary & create network - - with pytest.raises(RuntimeError) as err: - parser.CreateNetworkFromBinaryFile(path_to_model, tensorshape, requested_outputs) - - # Only check for part of the exception since the exception returns - # absolute path which will change on different machines. - assert 'failed to open' in str(err.value) - - -def test_tf_parser_end_to_end(shared_data_folder): - parser = ann.ITfParser = ann.ITfParser() - - tensorshape = {'input': ann.TensorShape((1, 28, 28, 1))} - requested_outputs = ["output"] - - network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'mock_model.pb'), - tensorshape, requested_outputs) - - input_binding_info = parser.GetNetworkInputBindingInfo("input") - - # load test image data stored in input_tf.npy - input_tensor_data = np.load(os.path.join(shared_data_folder, 'tf_parser/input_tf.npy')).astype(np.float32) - - preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')] - - options = ann.CreationOptions() - runtime = ann.IRuntime(options) - - opt_network, messages = ann.Optimize(network, preferred_backends, runtime.GetDeviceSpec(), ann.OptimizerOptions()) - - assert 0 == len(messages) - - net_id, messages = runtime.LoadNetwork(opt_network) - - assert "" == messages - - input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data]) - - outputs_binding_info = [] - - for output_name in requested_outputs: - outputs_binding_info.append(parser.GetNetworkOutputBindingInfo(output_name)) - - output_tensors = ann.make_output_tensors(outputs_binding_info) - - runtime.EnqueueWorkload(net_id, input_tensors, output_tensors) - output_vectors = ann.workload_tensors_to_ndarray(output_tensors) - - # Load golden output file for result comparison. - golden_output = np.load(os.path.join(shared_data_folder, 'tf_parser/golden_output_tf.npy')) - - # Check that output matches golden output to 4 decimal places (there are slight rounding differences after this) - np.testing.assert_almost_equal(output_vectors[0], golden_output, decimal=4) |