Attempting the "Hello World" Tensortflow.NET example in a docker environment running Mono yields the following error. Exactly the same code on Mono 6.12.0.93 on Mac OS X however does run flawlessly
2020-11-15 17:53:41.843832: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-11-15 17:53:41.873442: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 2712000000 Hz
2020-11-15 17:53:41.874170: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fc874d557a0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-11-15 17:53:41.874230: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
Stacktrace:
at <0xffffffff>
Assertion at method-to-ir.c:7352, condition `!sig->has_type_parameters' not met
at NumSharp.Backends.Unmanaged.UnmanagedMemoryBlock`1.FromArray (byte[],bool) [0x00037] in <6d1fbec37f814ff9b52dec21dc0ebd1a>:0
at NumSharp.Backends.Unmanaged.ArraySlice.FromArray (byte[],bool) [0x00000] in <6d1fbec37f814ff9b52dec21dc0ebd1a>:0
at NumSharp.np.array (byte[]) [0x00000] in <6d1fbec37f814ff9b52dec21dc0ebd1a>:0
at Tensorflow.Tensor.GetNDArray (Tensorflow.TF_DataType) [0x00041] in :0
at Tensorflow.Tensor.numpy () [0x00007] in :0
at Tensorflow.tensor_util.to_numpy_string (Tensorflow.Tensor) [0x00034] in :0
at Tensorflow.Eager.EagerTensor.ToString () [0x00016] in :0
Mono 5.12.0.301 Linux 4.19.76
Attempting the "Hello World" Tensortflow.NET example in a docker environment running Mono yields the following error. Exactly the same code on Mono 6.12.0.93 on Mac OS X however does run flawlessly
2020-11-15 17:53:41.843832: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2020-11-15 17:53:41.873442: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 2712000000 Hz 2020-11-15 17:53:41.874170: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fc874d557a0 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2020-11-15 17:53:41.874230: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version Stacktrace:
at <0xffffffff>
Assertion at method-to-ir.c:7352, condition `!sig->has_type_parameters' not met
at NumSharp.Backends.Unmanaged.UnmanagedMemoryBlock`1.FromArray (byte[],bool) [0x00037] in <6d1fbec37f814ff9b52dec21dc0ebd1a>:0
at NumSharp.Backends.Unmanaged.ArraySlice.FromArray (byte[],bool) [0x00000] in <6d1fbec37f814ff9b52dec21dc0ebd1a>:0
at NumSharp.np.array (byte[]) [0x00000] in <6d1fbec37f814ff9b52dec21dc0ebd1a>:0
at Tensorflow.Tensor.GetNDArray (Tensorflow.TF_DataType) [0x00041] in :0
at Tensorflow.Tensor.numpy () [0x00007] in :0
at Tensorflow.tensor_util.to_numpy_string (Tensorflow.Tensor) [0x00034] in :0
at Tensorflow.Eager.EagerTensor.ToString () [0x00016] in :0