create minimal conda env for RTX4090 to fix slow inference

cf NVlabs#9 (comment)

contact_graspnet/config_utils.py

@@ -1,5 +1,6 @@
 import os
 import yaml
+from yaml import Loader
 
 def recursive_key_value_assign(d,ks,v):
     """
@@ -37,7 +38,7 @@ def load_config(checkpoint_dir, batch_size=None, max_epoch=None, data_path=None,
     config_path = os.path.join(checkpoint_dir, 'config.yaml')
     config_path = config_path if os.path.exists(config_path) else os.path.join(os.path.dirname(__file__),'config.yaml')
     with open(config_path,'r') as f:
-        global_config = yaml.load(f)
+        global_config = yaml.load(f,Loader=Loader)
 
     for conf in arg_configs:
         k_str, v = conf.split(':')

contact_graspnet/inference.py

@@ -8,8 +8,8 @@
 
 import tensorflow.compat.v1 as tf
 tf.disable_eager_execution()
-physical_devices = tf.config.experimental.list_physical_devices('GPU')
-tf.config.experimental.set_memory_growth(physical_devices[0], True)
+# physical_devices = tf.config.experimental.list_physical_devices('GPU')
+# tf.config.experimental.set_memory_growth(physical_devices[0], True)
 
 BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 sys.path.append(os.path.join(BASE_DIR))

contact_graspnet/visualization_utils.py

@@ -51,7 +51,7 @@ def show_image(rgb, segmap):
     """
     plt.figure()
     figManager = plt.get_current_fig_manager()
-    figManager.window.showMaximized()
+    #figManager.window.showMaximized()
 
     plt.ion()
     plt.show()

environment.yaml

@@ -0,0 +1,17 @@
+name: contact-graspnet
+channels:
+  - conda-forge
+  - anaconda
+  - defaults
+dependencies:
+  - python=3.9
+  - cudatoolkit==11.8
+  - cudnn
+  - pip 
+  - pip:
+    - tensorflow==2.5 # requires python<=3.9
+    - opencv-python-headless
+    - pyyaml
+    - pyrender
+    - tqdm
+    - mayavi