GitHub #650: DelegateQuickStartGuide.md errors fix.
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: If24cad1d5d403e195d7adc539afb83cc5df134d1
diff --git a/delegate/python/test/test_external_delegate.py b/delegate/python/test/test_external_delegate.py
index f01a2d3..a8dd8e6 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 @@
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_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 @@
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 @@
# 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_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 @@
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 @@
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 @@
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]