diff options
Diffstat (limited to 'delegate/python/test/test_external_delegate.py')
| -rw-r--r-- | delegate/python/test/test_external_delegate.py | 58 |
1 files changed, 28 insertions, 30 deletions
diff --git a/delegate/python/test/test_external_delegate.py b/delegate/python/test/test_external_delegate.py index f01a2d3928..a8dd8e6d3e 100644 --- a/delegate/python/test/test_external_delegate.py +++ b/delegate/python/test/test_external_delegate.py @@ -1,4 +1,4 @@ -# Copyright © 2020 Arm Ltd and Contributors. All rights reserved. +# Copyright © 2022 Arm Ltd and Contributors. All rights reserved. # SPDX-License-Identifier: MIT import numpy as np @@ -66,7 +66,7 @@ def test_external_delegate_options_gpu_cached_network(delegate_dir, test_data_fo os.remove(binary_file) # Create blank binary file to write to. - open(binary_file, 'a').close() + open(binary_file, "a").close() assert (os.path.exists(binary_file)) assert (os.stat(binary_file).st_size == 0) @@ -102,11 +102,11 @@ def test_external_delegate_options_gpu_cached_network(delegate_dir, test_data_fo def test_external_delegate_gpu_fastmath(delegate_dir, test_data_folder): # create armnn delegate with enable-fast-math # fast-math is only enabled on Conv2d layer, so use conv2d model. - armnn_delegate = tflite.load_delegate(delegate_dir, options = {'backends': 'GpuAcc', - 'enable-fast-math': '1', + armnn_delegate = tflite.load_delegate(delegate_dir, options = {"backends": "GpuAcc", + "enable-fast-math": "1", "logging-severity": "info"}) - model_file_name = 'conv2d.tflite' + model_file_name = "conv2d.tflite" inputShape = [ 1, 5, 5, 1 ] outputShape = [ 1, 3, 3, 1 ] @@ -131,15 +131,15 @@ def test_external_delegate_gpu_fastmath(delegate_dir, test_data_folder): compare_outputs(armnn_outputs, [expected_output]) @pytest.mark.CpuAccTest -def test_external_delegate_cpu_options(capfd, delegate_dir, test_data_folder): +def test_external_delegate_cpu_options(delegate_dir, test_data_folder): # create armnn delegate with enable-fast-math and number-of-threads options # fast-math is only enabled on Conv2d layer, so use conv2d model. - armnn_delegate = tflite.load_delegate(delegate_dir, options = {'backends': 'CpuAcc', - 'enable-fast-math': '1', - 'number-of-threads': '4', + armnn_delegate = tflite.load_delegate(delegate_dir, options = {"backends": "CpuAcc", + "enable-fast-math": "1", + "number-of-threads": "4", "logging-severity": "info"}) - model_file_name = 'conv2d.tflite' + model_file_name = "conv2d.tflite" inputShape = [ 1, 5, 5, 1 ] outputShape = [ 1, 3, 3, 1 ] @@ -163,9 +163,6 @@ def test_external_delegate_cpu_options(capfd, delegate_dir, test_data_folder): # check results compare_outputs(armnn_outputs, [expected_output]) - captured = capfd.readouterr() - assert 'Set CPPScheduler to Linear mode, with 4 threads to use' in captured.out - def test_external_delegate_options_wrong_logging_level(delegate_dir): with pytest.raises(ValueError): tflite.load_delegate( @@ -174,9 +171,10 @@ def test_external_delegate_options_wrong_logging_level(delegate_dir): def test_external_delegate_options_debug(capfd, delegate_dir, test_data_folder): # create armnn delegate with debug option - armnn_delegate = tflite.load_delegate(delegate_dir, options = {'backends': 'CpuRef', 'debug-data': '1'}) + armnn_delegate = tflite.load_delegate(delegate_dir, options = {"backends": "CpuRef", + "debug-data": "1"}) - model_file_name = 'fp32_model.tflite' + model_file_name = "fp32_model.tflite" tensor_shape = [1, 2, 2, 1] @@ -192,16 +190,16 @@ def test_external_delegate_options_debug(capfd, delegate_dir, test_data_folder): compare_outputs(armnn_outputs, [expected_output]) captured = capfd.readouterr() - assert 'layerGuid' in captured.out + assert "layerGuid" in captured.out def test_external_delegate_options_fp32_to_fp16(capfd, delegate_dir, test_data_folder): # create armnn delegate with reduce-fp32-to-fp16 option - armnn_delegate = tflite.load_delegate(delegate_dir, options = {'backends': 'CpuRef', - 'debug-data': '1', - 'reduce-fp32-to-fp16': '1'}) + armnn_delegate = tflite.load_delegate(delegate_dir, options = {"backends": "CpuRef", + "debug-data": "1", + "reduce-fp32-to-fp16": "1"}) - model_file_name = 'fp32_model.tflite' + model_file_name = "fp32_model.tflite" tensor_shape = [1, 2, 2, 1] @@ -217,16 +215,16 @@ def test_external_delegate_options_fp32_to_fp16(capfd, delegate_dir, test_data_f compare_outputs(armnn_outputs, [expected_output]) captured = capfd.readouterr() - assert 'convert_fp32_to_fp16' in captured.out - assert 'convert_fp16_to_fp32' in captured.out + assert "convert_fp32_to_fp16" in captured.out + assert "convert_fp16_to_fp32" in captured.out def test_external_delegate_options_fp32_to_bf16(capfd, delegate_dir, test_data_folder): # create armnn delegate with reduce-fp32-to-bf16 option - armnn_delegate = tflite.load_delegate(delegate_dir, options = {'backends': 'CpuRef', - 'debug-data': '1', - 'reduce-fp32-to-bf16': '1'}) + armnn_delegate = tflite.load_delegate(delegate_dir, options = {"backends": "CpuRef", + "debug-data": "1", + "reduce-fp32-to-bf16": "1"}) - model_file_name = 'conv2d.tflite' + model_file_name = "conv2d.tflite" inputShape = [ 1, 5, 5, 1 ] outputShape = [ 1, 3, 3, 1 ] @@ -251,14 +249,14 @@ def test_external_delegate_options_fp32_to_bf16(capfd, delegate_dir, test_data_f compare_outputs(armnn_outputs, [expected_output]) captured = capfd.readouterr() - assert 'convert_fp32_to_bf16' in captured.out + assert "convert_fp32_to_bf16" in captured.out def test_external_delegate_options_memory_import(delegate_dir, test_data_folder): # create armnn delegate with memory-import option - armnn_delegate = tflite.load_delegate(delegate_dir, options = {'backends': 'CpuAcc,CpuRef', - 'memory-import': '1'}) + armnn_delegate = tflite.load_delegate(delegate_dir, options = {"backends": "CpuAcc,CpuRef", + "memory-import": "1"}) - model_file_name = 'fallback_model.tflite' + model_file_name = "fallback_model.tflite" tensor_shape = [1, 2, 2, 1] |