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I am using DirectML with TF in windows to be able to use my Gpus, but the memory limit is wrong !
How can I adjust the "real GPU memory instead and use my GPUs optimized ?
If anyone can help that will be great !
Thanks,
See below :
2025-01-10 10:52:57.230897: I tensorflow/c/logging.cc:34] DirectML: creating device on adapter 0 (NVIDIA RTX A5000)
2025-01-10 10:52:57.376093: I tensorflow/c/logging.cc:34] Successfully opened dynamic library Kernel32.dll
2025-01-10 10:52:57.377158: I tensorflow/c/logging.cc:34] DirectML: creating device on adapter 1 (NVIDIA RTX A5000)
2025-01-10 10:52:57.468749: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2025-01-10 10:52:57.468927: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 1, defaulting to 0. Your kernel may not have been built with NUMA support.
2025-01-10 10:52:57.470144: W tensorflow/core/common_runtime/pluggable_device/pluggable_device_bfc_allocator.cc:28] Overriding allow_growth setting because force_memory_growth was requested by the device.
2025-01-10 10:52:57.470563: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 82826 MB memory) -> physical PluggableDevice (device: 0, name: DML, pci bus id: )
2025-01-10 10:52:57.473273: W tensorflow/core/common_runtime/pluggable_device/pluggable_device_bfc_allocator.cc:28] Overriding allow_growth setting because force_memory_growth was requested by the device.
2025-01-10 10:52:57.473385: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 82826 MB memory) -> physical PluggableDevice (device: 1, name: DML, pci bus id: )
The text was updated successfully, but these errors were encountered:
Hi,
I am using DirectML with TF in windows to be able to use my Gpus, but the memory limit is wrong !
How can I adjust the "real GPU memory instead and use my GPUs optimized ?
If anyone can help that will be great !
Thanks,
See below :
2025-01-10 10:52:57.230897: I tensorflow/c/logging.cc:34] DirectML: creating device on adapter 0 (NVIDIA RTX A5000)
2025-01-10 10:52:57.376093: I tensorflow/c/logging.cc:34] Successfully opened dynamic library Kernel32.dll
2025-01-10 10:52:57.377158: I tensorflow/c/logging.cc:34] DirectML: creating device on adapter 1 (NVIDIA RTX A5000)
2025-01-10 10:52:57.468749: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2025-01-10 10:52:57.468927: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 1, defaulting to 0. Your kernel may not have been built with NUMA support.
2025-01-10 10:52:57.470144: W tensorflow/core/common_runtime/pluggable_device/pluggable_device_bfc_allocator.cc:28] Overriding allow_growth setting because force_memory_growth was requested by the device.
2025-01-10 10:52:57.470563: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 82826 MB memory) -> physical PluggableDevice (device: 0, name: DML, pci bus id: )
2025-01-10 10:52:57.473273: W tensorflow/core/common_runtime/pluggable_device/pluggable_device_bfc_allocator.cc:28] Overriding allow_growth setting because force_memory_growth was requested by the device.
2025-01-10 10:52:57.473385: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 82826 MB memory) -> physical PluggableDevice (device: 1, name: DML, pci bus id: )
The text was updated successfully, but these errors were encountered: