initial commit cpu only

inference_beit.py

@@ -1,9 +1,11 @@
 import tensorflow as tf
-gpu_devices = tf.config.experimental.list_physical_devices('GPU')
-if gpu_devices:
-    tf.config.experimental.set_memory_growth(gpu_devices[0], True)
-else:
-    print(f"TensorFlow device: {gpu_devices}")
+
+tf.config.set_visible_devices([], 'GPU')
+# gpu_devices = tf.config.experimental.list_physical_devices('GPU')
+# if gpu_devices:
+#     tf.config.experimental.set_memory_growth(gpu_devices[0], True)
+# else:
+#     print(f"TensorFlow device: {gpu_devices}")
 
 import os
 import numpy as np

inference_resnet.py

@@ -1,9 +1,11 @@
 import tensorflow as tf
-gpu_devices = tf.config.experimental.list_physical_devices('GPU')
-if gpu_devices:
-    tf.config.experimental.set_memory_growth(gpu_devices[0], True)
-else:
-    print(f"TensorFlow device: {gpu_devices}")
+
+tf.config.set_visible_devices([], 'GPU')
+# gpu_devices = tf.config.experimental.list_physical_devices('GPU')
+# if gpu_devices:
+#     tf.config.experimental.set_memory_growth(gpu_devices[0], True)
+# else:
+#     print(f"TensorFlow device: {gpu_devices}")
 
 from keras.applications import resnet
 import tensorflow.keras.layers as L

inference_sam.py

@@ -1,18 +1,21 @@
 import torch
+import tensorflow as tf
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-if device.type == "cuda":
-    torch.cuda.set_per_process_memory_fraction(0.3, device=device.index if device.index is not None else 0)
-else:
-   device = "cpu"
+device = torch.device("cpu")
 print(f"Torch device: {device}")
-
-import tensorflow as tf
-gpu_devices = tf.config.experimental.list_physical_devices('GPU')
-if gpu_devices:
-    tf.config.experimental.set_memory_growth(gpu_devices[0], True)
-else:
-    print(f"TensorFlow device: {gpu_devices}")
+# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+# if device.type == "cuda":
+#     torch.cuda.set_per_process_memory_fraction(0.3, device=device.index if device.index is not None else 0)
+# else:
+#    device = "cpu"
+# print(f"Torch device: {device}")
+
+tf.config.set_visible_devices([], 'GPU')
+# gpu_devices = tf.config.experimental.list_physical_devices('GPU')
+# if gpu_devices:
+#     tf.config.experimental.set_memory_growth(gpu_devices[0], True)
+# else:
+#     print(f"TensorFlow device: {gpu_devices}")
 
 from segment_anything import SamPredictor, sam_model_registry
 import matplotlib.pyplot as plt