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author | Richard Burton <richard.burton@arm.com> | 2020-04-08 16:39:05 +0100 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2020-04-10 16:11:09 +0000 |
commit | dc0c6ed9f8b993e63f492f203d7d7080ab4c835c (patch) | |
tree | ea8541990b13ebf1a038009aa6b8b4b1ea8c3f55 /python/pyarmnn/test/test_caffe_parser.py | |
parent | fe5a24beeef6e9a41366e694f41093565e748048 (diff) | |
download | armnn-dc0c6ed9f8b993e63f492f203d7d7080ab4c835c.tar.gz |
Add PyArmNN to work with ArmNN API of 20.02
* Add Swig rules for generating python wrapper
* Add documentation
* Add tests and testing data
Change-Id: If48eda08931514fa21e72214dfead2835f07237c
Signed-off-by: Richard Burton <richard.burton@arm.com>
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>
Diffstat (limited to 'python/pyarmnn/test/test_caffe_parser.py')
-rw-r--r-- | python/pyarmnn/test/test_caffe_parser.py | 131 |
1 files changed, 131 insertions, 0 deletions
diff --git a/python/pyarmnn/test/test_caffe_parser.py b/python/pyarmnn/test/test_caffe_parser.py new file mode 100644 index 0000000000..d744b907d4 --- /dev/null +++ b/python/pyarmnn/test/test_caffe_parser.py @@ -0,0 +1,131 @@ +# 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 caffe parser + parser = ann.ICaffeParser() + + # Specify path to model + path_to_model = os.path.join(shared_data_folder, 'mock_model.caffemodel') + + # Specify the tensor shape relative to the input [1, 1, 28, 28] + tensor_shape = {'Placeholder': ann.TensorShape((1, 1, 28, 28))} + + # Specify the requested_outputs + requested_outputs = ["output"] + + # Parse caffe binary & create network + parser.CreateNetworkFromBinaryFile(path_to_model, tensor_shape, requested_outputs) + + yield parser + + +def test_caffe_parser_swig_destroy(): + assert ann.ICaffeParser.__swig_destroy__, "There is a swig python destructor defined" + assert ann.ICaffeParser.__swig_destroy__.__name__ == "delete_ICaffeParser" + + +def test_check_caffe_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_get_network_input_binding_info(parser): + input_binding_info = parser.GetNetworkInputBindingInfo("Placeholder") + + tensor = input_binding_info[1] + assert tensor.GetDataType() == 1 + assert tensor.GetNumDimensions() == 4 + assert tensor.GetNumElements() == 784 + + +def test_get_network_output_binding_info(parser): + output_binding_info1 = parser.GetNetworkOutputBindingInfo("output") + + # Check the tensor info retrieved from GetNetworkOutputBindingInfo + tensor1 = output_binding_info1[1] + + assert tensor1.GetDataType() == 1 + assert tensor1.GetNumDimensions() == 2 + assert tensor1.GetNumElements() == 10 + + +def test_filenotfound_exception(shared_data_folder): + parser = ann.ICaffeParser() + + # path to model + path_to_model = os.path.join(shared_data_folder, 'some_unknown_network.caffemodel') + + # generic tensor shape [1, 1, 1, 1] + tensor_shape = {'data': ann.TensorShape((1, 1, 1, 1))} + + # requested_outputs + requested_outputs = [""] + + with pytest.raises(RuntimeError) as err: + parser.CreateNetworkFromBinaryFile(path_to_model, tensor_shape, 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 graph file' in str(err.value) + + +def test_caffe_parser_end_to_end(shared_data_folder): + parser = ann.ICaffeParser = ann.ICaffeParser() + + # Load the network specifying the inputs and outputs + input_name = "Placeholder" + tensor_shape = {input_name: ann.TensorShape((1, 1, 28, 28))} + requested_outputs = ["output"] + + network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'mock_model.caffemodel'), + tensor_shape, requested_outputs) + + # Specify preferred backend + preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')] + + input_binding_info = parser.GetNetworkInputBindingInfo(input_name) + + 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_caffe.npy + input_tensor_data = np.load(os.path.join(shared_data_folder, 'caffe_parser/input_caffe.npy')).astype(np.float32) + input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data]) + + # Load output binding info and + 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. + expected_output = np.load(os.path.join(shared_data_folder, 'caffe_parser/golden_output_caffe.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], expected_output, 4) |