![]() 16:47:04.670023: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library cusolver64_11.dll ![]() 16:47:04.655237: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library curand64_10.dll 16:47:04.647980: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library cufft64_10.dll 16:47:04.638019: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library cublasLt64_11.dll 16:47:04.634109: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library cublas64_11.dll 16:47:04.618787: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library cudart64_110.dll PciBusID: 0000:01:00.0 name: GeForce GTX 1660 Ti computeCapability: 7.5ĬoreClock: 1.59GHz coreCount: 24 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 268.26GiB/s 16:47:04.610494: I tensorflow/core/common_runtime/gpu/gpu_:1733] Found device 0 with properties: 16:47:04.565562: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library nvcuda.dll 16:46:58.163220: I tensorflow/stream_executor/platform/default/dso_:53] Successfully opened dynamic library cudart64_110.dll I debugged functions, so found a suspicious part, however I can’t catch what is root cause. (3, array([b'The Lion wants food', b'The Lion wants food',Īlso read: Load CSV Data using tf.Thanks to all of your help, I can build Faster-RCNN model.īut it goes well except training step, and I hit the wall. #args = 3 and specifying int 32, string type fo the tuple values. ĭata3= tf._generator( sample_gen, (tf.int32, tf.string), args = ()) ![]() #args =2 and specifying int 32 for the tuple values. When there are multiple arrays/arrays are of different lengths : data2= tf._generator( sample_gen, (tf.int32, tf.int32), args = ()) Iter = data1.make_initializable_iterator() #To use this dataset we need the make_initializable_iterator() ![]() #Output type = int.32 as the sample_gen function returns integers when sample = 1 as defined by args Let’s create our first dataset which will look like this: data1 = tf._generator(sample_gen,(tf.int32), args = ()) Here I have defined a generator function sample_gen() with conditional outputs and called next to access its values consecutively.
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