Prompt user to set_env_variables.sh + remove global scope imports from runner files (#243)

Author: jan-grzybek-ampere

.github/workflows/test.yml

@@ -28,6 +28,10 @@ jobs:
         run:
           python3 -m flake8
 
+      - name: Ensure runner files don't do imports in global scope and check if env checking codeblock prepended
+        run:
+          python3 -m unittest tests.test_imports
+
       - name: Git checkout w/ submodules
         uses: actions/checkout@v4
         with:

computer_vision/classification/alexnet/run.py

@@ -1,14 +1,25 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copyright (c) 2024, Ampere Computing LLC
-import argparse
-import torch
-import torchvision
-from utils.benchmark import run_model
-from utils.cv.imagenet import ImageNet
-from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
+try:
+    from utils import misc  # noqa
+except ModuleNotFoundError:
+    import os
+    import sys
+    filename = "set_env_variables.sh"
+    directory = os.path.realpath(__file__).split("/")[:-1]
+    for idx in range(1, len(directory) - 1):
+        subdir = "/".join(directory[:-idx])
+        if filename in os.listdir(subdir):
+            print(f"\nPlease run \033[91m'source {os.path.join(subdir, filename)}'\033[0m first.")
+            break
+    else:
+        print(f"\n\033[91mFAIL: Couldn't find {filename}, are you running this script as part of Ampere Model Library?"
+              f"\033[0m")
+    sys.exit(1)
 
 
 def parse_args():
+    import argparse
     parser = argparse.ArgumentParser(description="Run AlexNet model.")
     parser.add_argument("-p", "--precision",
                         type=str, choices=["fp32"], required=True,
@@ -38,6 +49,10 @@ def parse_args():
 
 
 def run_pytorch_fp(model_name, batch_size, num_runs, timeout, images_path, labels_path, disable_jit_freeze=False):
+    import torch
+    import torchvision
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.pytorch import PyTorchRunner
 
     def run_single_pass(pytorch_runner, imagenet):
@@ -64,6 +79,7 @@ def run_pytorch_fp32(model_name, batch_size, num_runs, timeout, images_path, lab
 
 
 def main():
+    from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
     args = parse_args()
     download_ampere_imagenet()
 

computer_vision/classification/densenet_121/run.py

@@ -1,14 +1,26 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copyright (c) 2024, Ampere Computing LLC
-import argparse
-import torch
-import torchvision
-from utils.benchmark import run_model
-from utils.cv.imagenet import ImageNet
-from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
+
+try:
+    from utils import misc  # noqa
+except ModuleNotFoundError:
+    import os
+    import sys
+    filename = "set_env_variables.sh"
+    directory = os.path.realpath(__file__).split("/")[:-1]
+    for idx in range(1, len(directory) - 1):
+        subdir = "/".join(directory[:-idx])
+        if filename in os.listdir(subdir):
+            print(f"\nPlease run \033[91m'source {os.path.join(subdir, filename)}'\033[0m first.")
+            break
+    else:
+        print(f"\n\033[91mFAIL: Couldn't find {filename}, are you running this script as part of Ampere Model Library?"
+              f"\033[0m")
+    sys.exit(1)
 
 
 def parse_args():
+    import argparse
     parser = argparse.ArgumentParser(description="Run DenseNet 121 model.")
     parser.add_argument("-m", "--model_path",
                         type=str,
@@ -41,6 +53,10 @@ def parse_args():
 
 
 def run_pytorch_fp(model_name, batch_size, num_runs, timeout, images_path, labels_path, disable_jit_freeze=False):
+    import torch
+    import torchvision
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.pytorch import PyTorchRunner
 
     def run_single_pass(pytorch_runner, imagenet):
@@ -63,6 +79,8 @@ def run_single_pass(pytorch_runner, imagenet):
 
 
 def run_ort_fp(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.ort import OrtRunner
 
     def run_single_pass(ort_runner, imagenet):
@@ -94,6 +112,7 @@ def run_ort_fp32(model_path, batch_size, num_runs, timeout, images_path, labels_
 
 
 def main():
+    from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
     args = parse_args()
     download_ampere_imagenet()
 

computer_vision/classification/densenet_169/run.py

@@ -1,12 +1,25 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copyright (c) 2024, Ampere Computing LLC
-import argparse
-from utils.benchmark import run_model
-from utils.cv.imagenet import ImageNet
-from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
+try:
+    from utils import misc  # noqa
+except ModuleNotFoundError:
+    import os
+    import sys
+    filename = "set_env_variables.sh"
+    directory = os.path.realpath(__file__).split("/")[:-1]
+    for idx in range(1, len(directory) - 1):
+        subdir = "/".join(directory[:-idx])
+        if filename in os.listdir(subdir):
+            print(f"\nPlease run \033[91m'source {os.path.join(subdir, filename)}'\033[0m first.")
+            break
+    else:
+        print(f"\n\033[91mFAIL: Couldn't find {filename}, are you running this script as part of Ampere Model Library?"
+              f"\033[0m")
+    sys.exit(1)
 
 
 def parse_args():
+    import argparse
     parser = argparse.ArgumentParser(description="Run ResNet-50 v1.5 model.")
     parser.add_argument("-m", "--model_path",
                         type=str,
@@ -37,6 +50,8 @@ def parse_args():
 
 
 def run_tf_fp(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.tf import TFFrozenModelRunner
 
     def run_single_pass(tf_runner, imagenet):
@@ -58,6 +73,8 @@ def run_single_pass(tf_runner, imagenet):
 
 
 def run_tflite(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.tflite import TFLiteRunner
 
     def run_single_pass(tflite_runner, imagenet):
@@ -92,6 +109,7 @@ def run_tflite_int8(model_path, batch_size, num_runs, timeout, images_path, labe
 
 
 def main():
+    from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
     args = parse_args()
     download_ampere_imagenet()
 

computer_vision/classification/googlenet/run.py

@@ -1,17 +1,25 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copyright (c) 2024, Ampere Computing LLC
-import argparse
-import os
-import warnings
-import torch
-import torchvision
-from utils.benchmark import run_model
-from utils.cv.imagenet import ImageNet
-from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
-warnings.filterwarnings("ignore")
+try:
+    from utils import misc  # noqa
+except ModuleNotFoundError:
+    import os
+    import sys
+    filename = "set_env_variables.sh"
+    directory = os.path.realpath(__file__).split("/")[:-1]
+    for idx in range(1, len(directory) - 1):
+        subdir = "/".join(directory[:-idx])
+        if filename in os.listdir(subdir):
+            print(f"\nPlease run \033[91m'source {os.path.join(subdir, filename)}'\033[0m first.")
+            break
+    else:
+        print(f"\n\033[91mFAIL: Couldn't find {filename}, are you running this script as part of Ampere Model Library?"
+              f"\033[0m")
+    sys.exit(1)
 
 
 def parse_args():
+    import argparse
     parser = argparse.ArgumentParser(description="Run GoogLeNet model.")
     parser.add_argument("-p", "--precision",
                         type=str, choices=["fp32"], required=True,
@@ -41,6 +49,11 @@ def parse_args():
 
 
 def run_pytorch_fp(model_name, batch_size, num_runs, timeout, images_path, labels_path, disable_jit_freeze=False):
+    import os
+    import torch
+    import torchvision
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.pytorch import PyTorchRunner
 
     def run_single_pass(pytorch_runner, imagenet):
@@ -69,6 +82,7 @@ def run_pytorch_fp32(model_name, batch_size, num_runs, timeout, images_path, lab
 
 
 def main():
+    from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
     args = parse_args()
     download_ampere_imagenet()
 

computer_vision/classification/inception_resnet_v2/run.py

@@ -1,12 +1,25 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copyright (c) 2024, Ampere Computing LLC
-import argparse
-from utils.benchmark import run_model
-from utils.cv.imagenet import ImageNet
-from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
+try:
+    from utils import misc  # noqa
+except ModuleNotFoundError:
+    import os
+    import sys
+    filename = "set_env_variables.sh"
+    directory = os.path.realpath(__file__).split("/")[:-1]
+    for idx in range(1, len(directory) - 1):
+        subdir = "/".join(directory[:-idx])
+        if filename in os.listdir(subdir):
+            print(f"\nPlease run \033[91m'source {os.path.join(subdir, filename)}'\033[0m first.")
+            break
+    else:
+        print(f"\n\033[91mFAIL: Couldn't find {filename}, are you running this script as part of Ampere Model Library?"
+              f"\033[0m")
+    sys.exit(1)
 
 
 def parse_args():
+    import argparse
     parser = argparse.ArgumentParser(description="Run Inception ResNet v2 model.")
     parser.add_argument("-m", "--model_path",
                         type=str,
@@ -37,6 +50,8 @@ def parse_args():
 
 
 def run_tf_fp(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.tf import TFFrozenModelRunner
 
     def run_single_pass(tf_runner, imagenet):
@@ -58,6 +73,8 @@ def run_single_pass(tf_runner, imagenet):
 
 
 def run_tflite(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.tflite import TFLiteRunner
 
     def run_single_pass(tflite_runner, imagenet):
@@ -92,6 +109,7 @@ def run_tflite_int8(model_path, batch_size, num_runs, timeout, images_path, labe
 
 
 def main():
+    from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
     args = parse_args()
     download_ampere_imagenet()
 

computer_vision/classification/inception_v2/run.py

@@ -1,12 +1,25 @@
 # SPDX-License-Identifier: Apache-2.0
 # Copyright (c) 2024, Ampere Computing LLC
-import argparse
-from utils.benchmark import run_model
-from utils.cv.imagenet import ImageNet
-from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
+try:
+    from utils import misc  # noqa
+except ModuleNotFoundError:
+    import os
+    import sys
+    filename = "set_env_variables.sh"
+    directory = os.path.realpath(__file__).split("/")[:-1]
+    for idx in range(1, len(directory) - 1):
+        subdir = "/".join(directory[:-idx])
+        if filename in os.listdir(subdir):
+            print(f"\nPlease run \033[91m'source {os.path.join(subdir, filename)}'\033[0m first.")
+            break
+    else:
+        print(f"\n\033[91mFAIL: Couldn't find {filename}, are you running this script as part of Ampere Model Library?"
+              f"\033[0m")
+    sys.exit(1)
 
 
 def parse_args():
+    import argparse
     parser = argparse.ArgumentParser(description="Run Inception v2 model.")
     parser.add_argument("-m", "--model_path",
                         type=str,
@@ -37,6 +50,8 @@ def parse_args():
 
 
 def run_tf_fp(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.tf import TFFrozenModelRunner
 
     def run_single_pass(tf_runner, imagenet):
@@ -58,6 +73,8 @@ def run_single_pass(tf_runner, imagenet):
 
 
 def run_tflite(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.tflite import TFLiteRunner
 
     def run_single_pass(tflite_runner, imagenet):
@@ -80,6 +97,8 @@ def run_single_pass(tflite_runner, imagenet):
 
 
 def run_ort_fp(model_path, batch_size, num_runs, timeout, images_path, labels_path):
+    from utils.benchmark import run_model
+    from utils.cv.imagenet import ImageNet
     from utils.ort import OrtRunner
 
     def run_single_pass(ort_runner, imagenet):
@@ -117,6 +136,7 @@ def run_ort_fp16(model_path, batch_size, num_runs, timeout, images_path, labels_
 
 
 def main():
+    from utils.misc import print_goodbye_message_and_die, download_ampere_imagenet
     args = parse_args()
     download_ampere_imagenet()