Resources required for new unit tests are included for review.
Signed-off-by: Guanqun Wang gemini910621@gmail.com
Change-Id: Iead6cb5beaf824a6f467ad9da4aede5719ebe4ec
add_subdirectory(samples)
add_subdirectory(src/armnnTfLiteParser)
add_subdirectory(src/armnnSerializer)
+add_subdirectory(src/armnnDeserializer)
if (BUILD_TESTS)
add_subdirectory(tests)
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)
setup(
name='pyarmnn',
"""In case people try importing without having Arm NN built with this parser."""
raise RuntimeError(message)
+try:
+ from ._generated.pyarmnn_deserializer import IDeserializer
+except ImportError as err:
+ logger = logging.getLogger(__name__)
+ message = "Your ArmNN library instance does not have an armnn models parser funcionality. "
+ logger.warning("%s Skipped IDeserializer import.", message)
+ logger.debug(str(err))
+
+ def IDeserializer():
+ """In case people try importing without having ArmNN built with this parser."""
+ raise RuntimeError(message)
+
# Network
from ._generated.pyarmnn import Optimize, OptimizerOptions, IOptimizedNetwork, IInputSlot, \
IOutputSlot, IConnectableLayer, INetwork
--- /dev/null
+//
+// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+%module pyarmnn_deserializer
+%{
+#include "armnnDeserializer/IDeserializer.hpp"
+#include "armnn/Types.hpp"
+#include "armnn/INetwork.hpp"
+#include "armnn/Exceptions.hpp"
+#include <string>
+#include <fstream>
+#include <sstream>
+%}
+
+//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 armnnDeserializer
+{
+%feature("docstring",
+"
+Interface for creating a parser object using ArmNN files.
+
+Parsers are used to automatically construct ArmNN graphs from model files.
+
+") IDeserializer;
+%nodefaultctor IDeserializer;
+class IDeserializer
+{
+public:
+};
+
+%extend IDeserializer {
+// This is not a substitution of the default constructor of the Armnn class. It tells swig to create custom __init__
+// method for ArmNN python object that will use static factory method to do the job.
+
+ IDeserializer() {
+ return armnnDeserializer::IDeserializer::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 IDeserializer::Destroy himself.
+// $self` is a pointer to extracted ArmNN IDeserializer object.
+
+ ~IDeserializer() {
+ armnnDeserializer::IDeserializer::Destroy($self);
+ }
+
+ %feature("docstring",
+ "
+ Create the network from a armnn binary file.
+
+ Args:
+ graphFile (str): Path to the armnn model to be parsed.
+
+ Returns:
+ INetwork: Parsed network.
+
+ Raises:
+ RuntimeError: If model file was not found.
+ ") CreateNetworkFromBinaryFile;
+
+ %newobject CreateNetworkFromBinary;
+ armnn::INetwork* CreateNetworkFromBinary(const char *graphFile) {
+ std::ifstream is(graphFile, std::ifstream::binary);
+ if (!is.good()) {
+ std::string locationString = CHECK_LOCATION().AsString();
+ std::stringstream msg;
+ msg << "Cannot read the file " << graphFile << locationString;
+ throw armnn::FileNotFoundException(msg.str());
+ }
+ return $self->CreateNetworkFromBinary(is).release();
+ }
+
+// Make both GetNetworkInputBindingInfo and GetNetworkOutputBindingInfo return a std::pair like other parsers instead of struct.
+
+ %feature("docstring",
+ "
+ Retrieve binding info (layer id and tensor info) for the network input identified by the given layer name and subgraph id.
+ Args:
+ subgraphId (int): The layer id. Any value is acceptable since it is unused in the current implementation.
+ name (str): Name of the input.
+
+ Returns:
+ tuple: (`int`, `TensorInfo`).
+ ") GetNetworkInputBindingInfo;
+ std::pair<int, armnn::TensorInfo> GetNetworkInputBindingInfo(unsigned int layerId, const std::string& name){
+ armnnDeserializer::BindingPointInfo info = $self->GetNetworkInputBindingInfo(layerId, name);
+ return std::make_pair(info.m_BindingId, info.m_TensorInfo);
+ }
+
+ %feature("docstring",
+ "
+ Retrieve binding info (layer id and `TensorInfo`) for the network output identified by the given layer name and subgraph id.
+
+ Args:
+ layerId (int): The layer id. Any value is acceptable since it is unused in the current implementation.
+ name (str): Name of the output.
+
+ Returns:
+ tuple: (`int`, `TensorInfo`).
+ ") GetNetworkOutputBindingInfo;
+ std::pair<int, armnn::TensorInfo> GetNetworkOutputBindingInfo(unsigned int layerId, const std::string& name){
+ armnnDeserializer::BindingPointInfo info = $self->GetNetworkOutputBindingInfo(layerId, name);
+ return std::make_pair(info.m_BindingId, info.m_TensorInfo);
+ }
+}
+
+} // end of namespace armnnDeserializer
+
+// Clear exception typemap.
+%exception;
__verbose = args.verbose
- wrap_names = ['armnn_version',
- 'armnn',
- 'armnn_caffeparser',
- 'armnn_onnxparser',
- 'armnn_tfparser',
- 'armnn_tfliteparser']
+ wrap_names = ['armnn_version',
+ 'armnn',
+ 'armnn_caffeparser',
+ 'armnn_onnxparser',
+ 'armnn_tfparser',
+ 'armnn_tfliteparser',
+ 'armnn_deserializer']
for n in wrap_names:
generate_wrap(n, f"-I{' -I'.join(armnn_includes)} ")
--- /dev/null
+# Copyright © 2020 Arm Ltd and Contributors. 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
+ """
+ parser = ann.IDeserializer()
+ parser.CreateNetworkFromBinary(os.path.join(shared_data_folder, 'mock_model.armnn'))
+
+ yield parser
+
+
+def test_deserializer_swig_destroy():
+ assert ann.IDeserializer.__swig_destroy__, "There is a swig python destructor defined"
+ assert ann.IDeserializer.__swig_destroy__.__name__ == "delete_IDeserializer"
+
+
+def test_check_deserializer_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_deserializer_get_network_input_binding_info(parser):
+ # use 0 as a dummy value for layer_id, which is unused in the actual implementation
+ layer_id = 0
+ input_name = 'input_1'
+
+ input_binding_info = parser.GetNetworkInputBindingInfo(layer_id, input_name)
+
+ tensor = input_binding_info[1]
+ assert tensor.GetDataType() == 2
+ assert tensor.GetNumDimensions() == 4
+ assert tensor.GetNumElements() == 784
+ assert tensor.GetQuantizationOffset() == 128
+ assert tensor.GetQuantizationScale() == 0.007843137718737125
+
+
+def test_deserializer_get_network_output_binding_info(parser):
+ # use 0 as a dummy value for layer_id, which is unused in the actual implementation
+ layer_id = 0
+ output_name = "dense/Softmax"
+
+ output_binding_info1 = parser.GetNetworkOutputBindingInfo(layer_id, output_name)
+
+ # Check the tensor info retrieved from GetNetworkOutputBindingInfo
+ tensor1 = output_binding_info1[1]
+
+ assert tensor1.GetDataType() == 2
+ assert tensor1.GetNumDimensions() == 2
+ assert tensor1.GetNumElements() == 10
+ assert tensor1.GetQuantizationOffset() == 0
+ assert tensor1.GetQuantizationScale() == 0.00390625
+
+
+def test_deserializer_filenotfound_exception(shared_data_folder):
+ parser = ann.IDeserializer()
+
+ with pytest.raises(RuntimeError) as err:
+ parser.CreateNetworkFromBinary(os.path.join(shared_data_folder, 'some_unknown_network.armnn'))
+
+ # Only check for part of the exception since the exception returns
+ # absolute path which will change on different machines.
+ assert 'Cannot read the file' in str(err.value)
+
+
+def test_deserializer_end_to_end(shared_data_folder):
+ parser = ann.IDeserializer()
+
+ network = parser.CreateNetworkFromBinary(os.path.join(shared_data_folder, "mock_model.armnn"))
+
+ # use 0 as a dummy value for layer_id, which is unused in the actual implementation
+ layer_id = 0
+ input_name = 'input_1'
+ output_name = 'dense/Softmax'
+
+ input_binding_info = parser.GetNetworkInputBindingInfo(layer_id, input_name)
+
+ 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
+
+ # Load test image data stored in input_lite.npy
+ input_tensor_data = np.load(os.path.join(shared_data_folder, 'deserializer/input_lite.npy'))
+ input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data])
+
+ output_tensors = []
+ out_bind_info = parser.GetNetworkOutputBindingInfo(layer_id, output_name)
+ out_tensor_info = out_bind_info[1]
+ out_tensor_id = out_bind_info[0]
+ output_tensors.append((out_tensor_id,
+ ann.Tensor(out_tensor_info)))
+
+ runtime.EnqueueWorkload(net_id, input_tensors, output_tensors)
+
+ output_vectors = []
+ for index, out_tensor in enumerate(output_tensors):
+ output_vectors.append(out_tensor[1].get_memory_area())
+
+ # Load golden output file for result comparison.
+ expected_outputs = np.load(os.path.join(shared_data_folder, 'deserializer/golden_output_lite.npy'))
+
+ # Check that output matches golden output
+ assert (expected_outputs == output_vectors[0]).all()
-# Copyright © 2020 Arm Ltd. All rights reserved.
+# Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
# SPDX-License-Identifier: MIT
import inspect
from typing import Tuple
import pytest
import pyarmnn._generated.pyarmnn as generated_armnn
+import pyarmnn._generated.pyarmnn as generated_deserializer
import pyarmnn._generated.pyarmnn_caffeparser as generated_caffe
import pyarmnn._generated.pyarmnn_onnxparser as generated_onnx
import pyarmnn._generated.pyarmnn_tfliteparser as generated_tflite
ignored_class_names = (*swig_independent_classes, '_SwigNonDynamicMeta')
return list(filter(lambda x: x[0] not in ignored_class_names,
inspect.getmembers(generated_armnn, inspect.isclass) +
+ inspect.getmembers(generated_deserializer, inspect.isclass) +
inspect.getmembers(generated_caffe, inspect.isclass) +
inspect.getmembers(generated_tflite, inspect.isclass) +
inspect.getmembers(generated_onnx, inspect.isclass) +
--- /dev/null
+#
+# Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+# SPDX-License-Identifier: MIT
+#
+if(BUILD_ARMNN_DESERIALIZER)
+ find_program(FLATC flatc
+ HINTS ${FLATC_DIR}
+ DOC "Path to 'flatc', the flatbuffers compiler")
+ if (NOT FLATC)
+ message(SEND_ERROR "flatc not found. Specify the full path of the flatc executable with -DFLATC=<flatc path>")
+ endif()
+
+ add_custom_command(
+ # Generate an ArmnnSchema_generated.h file if it doesn't exist, or update it when necessary otherwise
+ OUTPUT ArmnnSchema_generated.h DEPENDS ${CMAKE_CURRENT_SOURCE_DIR}/../armnnSerializer/ArmnnSchema.fbs
+ COMMAND ${FLATC} -o ${CMAKE_CURRENT_BINARY_DIR} --cpp ${CMAKE_CURRENT_SOURCE_DIR}/../armnnSerializer/ArmnnSchema.fbs
+ )
+
+ set(armnn_deserializer_sources)
+ list(APPEND armnn_deserializer_sources
+ ArmnnSchema_generated.h
+ Deserializer.hpp
+ Deserializer.cpp
+ )
+
+ add_library_ex(armnnDeserializer SHARED ${armnn_deserializer_sources})
+
+ include_directories(SYSTEM "${FLATBUFFERS_INCLUDE_PATH}")
+ set_target_properties(armnnDeserializer PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${PROJECT_BINARY_DIR})
+ target_include_directories(armnnDeserializer PRIVATE ../armnn)
+ target_include_directories(armnnDeserializer PRIVATE ../armnnUtils)
+
+ # System include to suppress warnings for flatbuffers generated files
+ target_include_directories(armnnDeserializer SYSTEM PRIVATE ${CMAKE_CURRENT_BINARY_DIR})
+
+ target_link_libraries(armnnDeserializer armnn ${FLATBUFFERS_LIBRARY})
+
+ install(TARGETS armnnDeserializer
+ EXPORT armnn-targets
+ LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR}
+ ARCHIVE DESTINATION ${CMAKE_INSTALL_LIBDIR}
+ )
+ set_target_properties(armnnDeserializer PROPERTIES VERSION ${GENERIC_LIB_VERSION} SOVERSION ${GENERIC_LIB_SOVERSION} )
+endif()
projects / platform / upstream / armnn.git / commitdiff