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The "Bug Fixes and Other Changes" section lists more determinism-related.Replaces the TF_DETERMINISTIC_OPS environmental variable, which is now
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Which makes TensorFlow ops run deterministically at the cost of performance. Rank 2 or above by specifying the output shape in the feature config or Though the input tensor remains to be rank 2, the activations now can be Take arbitrary rank of dense and sparse tensor. tf. now has the same behaviorĪs tf._embedding_lookup which can.tf. now takes an additionalĪrgument output_shape which can specify the shape of the output.Aĭetailed version of the summary is available which prints additionallyĪll the TensorFlow OPs included in each of the TRTEngineOPs. It namely showsĮach TRTEngineOp with their input(s)' and output(s)' shape and dtype. Outputs a summary of the inference converted by TF-TRT. TrtGraphConverterV2 provides a new API called.True (default), the original behavior is preserved. save() function won't save any TRT engines that have been built. save() function inside TrtGraphConverterV2. Added a new parameter called save_gpu_specific_engines to the.
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Minimum_segment_size, maximum_cached_engines, use_calibration and conversion_params is now deprecated inside TrtGraphConverterV2 inįavor of direct arguments: max_workspace_size_bytes, precision_mode,.tf.random.categorical op for output data type tf.int64 on CPU.tf.random.uniform op for output data type tf.float32 on CPU.tf.random.normal op for output data type tf.float32 on CPU.Added TFLite builtin op support for the following TF ops:.This release contains contributions from many people at Google, as well as: